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  • Articles  (6,323)
  • IEEE Sensors Journal  (4,657)
  • IEEE Transactions on Aerospace and Electronic Systems  (1,666)
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  • Electrical Engineering, Measurement and Control Technology  (6,323)
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  • 1
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    IEEE Aerospace and Electronic Systems Society (2018)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2018-02-09
    Description: Provides a listing of current staff, committee members and society officers.
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    Car Detection in Aerial Images of Dense Urban Areas (2018)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2018-02-09
    Description: With the ever-increasing demand in the analysis and understanding of aerial images in order to remotely recognize targets, this paper introduces a robust system for the detection and localization of cars in images captured by air vehicles and satellites. The system adopts a sliding-window approach. It compromises a window-evaluation and a window-classification subsystems. The performance of the proposed framework was evaluated on the Vaihingen dataset. Results demonstrate its superiority to the state of the art.
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  • 3
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    Adaptive Navigation Algorithm Under Abnormal Measurements in Libration-Point Mission (2018)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2018-02-09
    Description: This paper investigates X-ray pulsar navigation for earth–moon libration-point mission. A comprehensive analysis shows that abnormal measurements are inevitable and bring quite adverse effects for navigation results. To approach this problem, a new algorithm called robust square-root cubature Kalman filter is proposed. An innovation-based adaptive scale factor is introduced to adjust measurement noise covariance so that the adverse effects of abnormal measurements can be suppressed. Effectiveness of the proposed method is demonstrated in simulation results.
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  • 4
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    FDA-MIMO Radar Range–Angle Estimation: CRLB, MSE, and Resolution Analysis (2018)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2018-02-09
    Description: Multiple-input multiple-output (MIMO) radar enjoys the advantage of increased degrees-of-freedom and spatial diversity gain, but it cannot effectively resolves the targets closely spaced in the same angle cell (but different range cells). Frequency diverse array (FDA)-MIMO radar can handle this problem by exploiting its range-dependent beampattern. FDA-MIMO radar was, thus, suggested for range–angle estimation of targets. Nevertheless, it is necessary to provide theoretical performance analysis for such a relatively new radar technique. Since multiple signal classification (MUSIC) algorithm is widely adopted in most of the FDA-MIMO literature, this paper derives the Cramér–Rao lower bound and mean square error expressions in MUSIC-based range–angle estimation algorithms for a general FDA-MIMO radar. Furthermore, the corresponding range and angle resolution thresholds in target detection and localization are also derived. Numerical results verify that the FDA-MIMO indeed outperforms conventional MIMO radar in both range–angle estimation and resolution threshold performance.
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  • 5
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    An Imaging Dictionary Based Multipath Suppression Algorithm for Through-Wall Radar Imaging (2018)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2018-02-09
    Description: This paper considers the problem of multipath ghosts elimination for the through-wall radar imaging. We formulate a discrete signal model in the presence of first-order multipath, and propose an imaging dictionary based algorithm to suppress the multipath ghosts. Specifically, first, several estimated images are obtained via two different kinds of imaging dictionaries for the focus delays related to the direct propagation path and the multipaths, respectively. We find that all the estimated images possess large values around the genuine target positions and the multipath ghosts of them do not overlap with each other. Then, based on this feature, these images are fused via incoherent multiplication image fusion method to yield a multipath ghosts free image. Finally, the simulation and real data are used to prove the validity of the proposed approach.
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  • 6
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    Data-Driven Motion Compensation Techniques for Noncooperative ISAR Imaging (2018)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2018-02-09
    Description: We consider the data-driven motion compensation problem in inverse synthetic aperture radar (ISAR) imaging. We present optimization-based ISAR techniques and propose improvements to the range alignment, time-window selection, autofocus, time–frequency-based image reconstruction, and cross-range scaling procedures. In experiments, the improvements reduced the computational burden and increased the image contrast by 50% at best and 28% on average in several test cases, including changing translational and rotational motion.
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  • 7
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    The New Search Method in Precise GNSS Positioning (2018)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2018-02-09
    Description: The paper presents a new method of searching for a fixed solution in precise positioning based on carrier phase data. The main idea is to search for a fixed solution in the coordinate domain instead of in an ambiguity domain. The dimension of the ambiguity domain depends on the number of satellites. The dimension of the coordinate domain is always three, and it does not depend on the number of satellites. It considerably reduces computational load.
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  • 8
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    A Unified Optimal Control Approach for Maximum Endurance and Maximum Range (2018)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2018-02-09
    Description: This paper proposes a unified optimal control framework that can be used to formulate and solve aircraft performance problems, such as maximum endurance and maximum range, for both propeller-driven airplanes and jet-propelled aircraft. It is proved in this paper that such problems have a common mathematical formulation and, under strict convexity assumptions, they have a unique feedback solution for the speed as a function of weight. The feedback solution yields an analytic expression for the optimal speed. For maximum endurance, the solution corresponds to the minimization of the rate of fuel consumption per unit time. For maximum range, the rate of fuel consumption per unit distance is minimized. Moreover, the optimal solution for maximum range will be interpreted geometrically using the concept of convex conjugate function and Legendre transformation. Although the optimal control framework is illustrated for maximum range and maximum endurance, it is a general approach that can be used for other aircraft performance problems.
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  • 9
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    Robust Fault-Tolerant Tracking Control for Spacecraft Proximity Operations Using Time-Varying Sliding Mode (2018)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2018-02-09
    Description: The capture of a free-floating tumbling object using an autonomous vehicle is a key technology for many future orbital missions. Spacecraft proximity operations will play an important role in guaranteeing the success of such missions. In this paper, we technically propose a tracking control scheme for proximity operations between a target and a pursuer spacecraft that ensures accurate relative position tracking as well as attitude synchronization. Specifically, an integrated six degrees of freedom dynamics model is first established to describe the relative motion of the pursuer with respect to the target. Then, a robust fault-tolerant controller is derived by combining the sliding mode control and the adaptive technique. The designed controller is proved to be not only robust against unexpected disturbances and adaptive to unknown and uncertain mass/inertia properties of the pursuer, but also able to accommodate a large class of actuator faults. In particular, by incorporating a novel time-varying forcing function into the sliding dynamics, the proposed control algorithm is able to guarantee the finite-time convergence of the translational and rotational tracking errors, and the convergence time as an explicit parameter can be assigned a priori by the designers. Furthermore, a theoretical analysis is also presented to assess the fault tolerance ability of the designed controller. Finally, numerous examples are carried out to evaluate the effectiveness and demonstrate the benefits of the overall control approach.
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  • 10
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    Angle Estimation With Polarization Filtering: A Single Snapshot Approach (2018)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2018-02-09
    Description: When a monopulse radar is subjected to main-lobe barrage interference, the target and the interference source are both located within the 3 dB beamwidth of the radar; the target returns are subsumed by the interference, which results in incorrect detection, erroneous angle measurements, and tracking error. Based on a hybrid polarimetric monopulse radar with six channels, a new approach is presented for estimating the target angle from a single snapshot in the presence of main-lobe barrage interference. By means of polarization filtering and polarization synthesis of signals from multiple channels with two orthogonal polarizations, a new pair of sum and difference signals is formed that represents the angle difference between the target and the interference source. After standard monopulse processing of these new signals and additional compensation, the estimate of the target angle is derived with low computational complexity.
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  • 11
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    Tracking-Aided Classification of Targets Using Multihypothesis Sequential Probability Ratio Test (2018)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2018-02-09
    Description: This paper deals with target classification by using both feature data and kinematic measurements. The problem is tackled by multihypothesis sequential testing with embedded target tracking. We implement an Armitage sequential test for nonmaneuvering and maneuvering targets. Both (centralized and distributed) fusion architectures are used for the embedded tracking. The contributions of the kinematic measurements to classification are analyzed, and classification performance improvement is shown analytically for a special case. Numerical results are provided to demonstrate the performance of our algorithms.
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  • 12
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    An L-Shaped Array With Nonorthogonal Axes—Its Cramér–Rao Bound for Direction Finding (2018)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2018-02-09
    Description: If a nominally L-shaped sensor-array's two legs are not exactly perpendicular, its azimuth-polar direction-of-arrival estimation would be degraded. This paper quantifies this degradation via a deterministic Cramér–Rao bound analysis of the direction-finding error variance.
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  • 13
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    MIMO Radar Calibration and Imagery for Near-Field Scattering Diagnosis (2018)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2018-02-09
    Description: Multiple-input multiple-output (MIMO) radar is an enabling technique for high-resolution imaging, which is especially useful for near-field electromagnetic scattering diagnosis of complex targets. Among others, high sidelobes and radar cross section (RCS) calibration uncertainty are the major challenges for such applications, due to array nonuniformity, imperfect channels, and antenna pattern tapering. These shortcomings prevent a MIMO radar from obtaining high-quality images with enough dynamic range and RCS accuracy. In this paper, we develop a complete solution for these problems. A novel adaptive weighting technique is proposed, where the complex weights are optimized for exact amplitude and phase error calibration of a MIMO array and for azimuth sidelobe reduction. A MIMO filtered backprojection algorithm is developed for image formation with improved RCS calibration accuracy, where propagation path-loss, antenna pattern tapering, and phase distortion due to the near-field spherical wave front are compensated. Both indoor and outdoor field test results are presented to show the high-quality images obtained using the proposed techniques, demonstrating the applicability of a MIMO radar for diagnostic RCS imaging of complex targets.
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  • 14
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    Computationally Efficient TDOA/FDOA Estimation for Unknown Communication Signals in Electronic Warfare Systems (2018)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2018-02-09
    Description: The cross ambiguity function (CAF) has been commonly used to find time difference of arrival (TDOA) and frequency difference of arrival (FDOA). In most cases, direct computation of the CAF by using a conventional method such as fast Fourier transform is too computationally intensive. Thus, a two-stage approach consisting of a coarse mode to find rough TDOA/FDOA estimates and a fine mode for precise estimation was introduced. However, there has been no methodology for selecting an interpolation factor determined by the sampling frequency and target precision which significantly affects the computational complexity. In addition, even if the computational complexity can be reduced by using the optimal interpolation factor, the huge transmission data through the datalink between sensors and the central station still remains to be an obstacle for an electronic warfare (EW) system. In this respect, we derive an optimal interpolation factor and then propose a new two-stage TDOA/FDOA estimation algorithm using a resampling block to reduce the computational complexity and the data size simultaneously in EW systems. In the proposed method, the optimal interpolation factor can be used irrespective of the sampling frequency and the target precision. Simulation results show that the optimal interpolation factor efficiently reduces the computational burden without the loss of estimation performance.
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  • 15
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    Passive Radar Detection With Noisy Reference Channel Using Principal Subspace Similarity (2018)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2018-02-09
    Description: Traditional passive radar detectors compute cross correlation of the raw data in the reference and surveillance channels. However, there is no optimality guarantee for this detector in the presence of a noisy reference. Here, we develop a new detector that utilizes a test statistic based on the cross correlation of the principal left singular vectors of the reference and surveillance signal-plus-noise matrices. This detector offers better performance by exploiting the inherent low-rank structure when the transmitted signals are a weighted periodic summation of several identical waveforms (amplitude and phase modulation), as is the case with commercial digital illuminators as well as noncooperative radar. We consider a scintillating target. We provide analytical detection performance guarantees establishing signal-to-noise ratio thresholds above which the proposed detection statistic reliably discriminates, in an asymptotic sense, the signal versus no-signal hypothesis. We validate these results using extensive numerical simulations. We demonstrate the “near constant false alarm rate (CFAR)” behavior of the proposed detector with respect to a fixed, SNR-independent threshold and contrast that with the need to adjust the detection threshold in an SNR-dependent manner to maintain CFAR for other detectors found in the literature. Extensions of the proposed detector for settings applicable to orthogonal frequency division multiplexing (OFDM), adaptive radar are discussed.
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  • 16
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    A Fuzzy Human Pilot Model of Longitudinal Control for a Carrier Landing Task (2018)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2018-02-09
    Description: Human pilot models are tightly dependent on the specific flight tasks. For a carrier landing task, the human pilot controls the aircraft glide path by the guidance information from the Fresnel lens optical landing system (FLOLS) during the aircraft approach to the carrier. This paper focuses on the modeling of the human pilot behavior of sensing and recognizing the guidance information from the Fresnel lens of the FLOLS in longitudinal motion. A fuzzy human pilot model is built based on a fuzzy logic control theory to simulate the human pilot behavior. The simulations of carrier landing are conducted to illustrate the advantages and effectiveness of the proposed fuzzy human pilot model.
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  • 17
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    Analytic Evaluation of Fine Alignment for Velocity Aided INS (2018)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2018-02-09
    Description: Coarse attitude initialization procedure is used to determine the initial attitude of the inertial navigation system. To improve the accuracy of the attitude to a desired value, fine alignment (FA) process is employed. In stationary conditions, zero velocity updates are usually used to achieve such goal. In this paper, an analytic evaluation of the steady-state properties of the FA process is presented. The contribution of this paper is twofold: 1) closed-form analytic solutions to the error-state covariance of the FA process are derived and 2) semianalytic solutions to the convergence time of the error-state covariance are shown. With such closed-form solutions at hand, insight can be gained into the parameters involved in the FA process in preliminary design process. Simulation and field experiments are given to support the analytical expressions.
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  • 18
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    Beampattern Synthesis for Frequency Diverse Array via Reweighted $ell _1$ Iterative Phase Compensation (2018)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2018-02-09
    Description: This paper addresses the issue of beampattern synthesis with flexible magnitude response and low sidelobe in a frequency diverse array radar. It is formulated as an optimization problem in terms of $ell _1$ -norm minimization, which encourages the sparsity of array pattern. An $ell _1$ iterative phase compensation (IPC) technique is employed to transform the nonconvex constraint to phase compensation form. Then, to further reduce the sidelobe level, a reweighted $ell _1$ -IPC algorithm is devised, in which a sparsity-enhanced scheme is utilized to convert the $ell _1$ -norm to a new cost function that more closely resembles $ell _0$ -norm. Numerical results are presented to demonstrate the effectiveness of the proposed approach in different scenarios.
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  • 19
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    Boost-Phase Trajectory Inference From Space-Borne LOS Measurements With a Sieve Method (2018)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2018-02-09
    Description: Boost-phase trajectory inference is one of the major objectives of the space-borne missile early-warning system. Traditional methods can be classified as either profile-based or profile-free methods. The profile-based methods are accurate but inadaptable to the types of missiles, whereas the profile-free methods are adaptable but inaccurate. To integrate the strengths of the profile-based and profile-free methods, a multimodel trajectory inference approach is proposed. First, a general net acceleration model (GNAM) containing only type-free prior information is constructed by the method of sieves. Then, a new kind of net acceleration profile is proposed by incorporating type-dependent prior information into the GNAM. After that, the multimodel approach is proposed following the Bayesian framework. Simulations indicate that the approach is accurate in estimation and capable for type identification.
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  • 20
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    Performance Analysis of Adaptive Detectors for Point Targets in Subspace Interference and Gaussian Noise (2018)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2018-02-09
    Description: This paper investigates the statistical performance of three adaptive detectors in the presence of subspace interference and Gaussian noise. The interference is deterministic and lies in a known subspace but with unknown coordinates, while the noise is Gaussian distributed with unknown covariance matrix. For performance evaluation, we consider a more general case, namely, the case of subspace signal mismatch, where the actual signal does not completely lie in the presumed signal subspace. We derive the exact statistical distributions of the detectors, and then obtain analytical expressions for probabilities of detection and false alarm. The theoretical study reveals that the interference and signal mismatch affects the detection performance through two angles, which are the angle between the interference subspace and actual signal, and the angle between the actual signal and presumed signal subspace after they are both projected onto the interference-orthogonalized subspace. Numerical examples are provided to verify the theoretical results.
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  • 21
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    Digital Monopulse Beamforming for Achieving the CRLB for Angle Accuracy (2018)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2018-02-09
    Description: The monopulse angle-estimation technique used in digital beamforming radars is investigated from the perspective of optimizing the angle accuracy. Specifically, a digital difference beamforming taper is proposed in this paper to optimize the monopulse angle accuracy. For a fully digitized array radar with an amplitude-tapered antenna aperture for sum beampattern with low sidelobes, the monopulse angle accuracy obtained using the proposed difference taper coincides with the Cramer–Rao lower bound. The derivation of the monopulse angle accuracy with the proposed difference taper is presented and an improvement of the accuracy over the conventional monopulse accuracy is proved theoretically. The results of computer simulations using a uniform linear array is included to highlight the accuracy improvement by a factor of 1.16 (over the conventional monopulse), which is equivalent to a 1.3 dB reduction in the signal-to-noise ratio for the requisite angle accuracy.
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  • 22
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    A New Adaptive Extended Kalman Filter for Cooperative Localization (2018)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2018-02-09
    Description: To solve the problem of unknown noise covariance matrices inherent in the cooperative localization of autonomous underwater vehicles, a new adaptive extended Kalman filter is proposed. The predicted error covariance matrix and measurement noise covariance matrix are adaptively estimated based on an online expectation-maximization approach. Experimental results illustrate that, under the circumstances that are detailed in the paper, the proposed algorithm has better localization accuracy than existing state-of-the-art algorithms.
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  • 23
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    Three-Axial Helmholtz Coil Design and Validation for Aerospace Applications (2018)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2018-02-09
    Description: This paper presents the detailed design, construction, and validation of a three-axis square Helmholtz coil. It also describes the methodology used to drive each pair of coils as well as the setup to operate it in a closed-loop system using a digital PID controller. The coil will be mainly used for aerospace applications, especially to aid the development and testing of attitude determination and control systems that use the earth's magnetic field as a reference vector. Most of the system was built using commercial components, reducing cost, and complexity compared to similar commercial systems. The assembled Helmholtz coil has approximately one cubic meter and can generate magnetic fields up to 2 G/ axis, keeping a uniformity of 0.04% around 11 cm of the center, in each axis. A custom-designed voltage-controlled current source, based on the Howland current pump, was employed, requiring no complex electronic circuits. The coil was designed to be part of a hardware-in-the-loop (HiL) system, which is controlled by a dSPACE modular simulation hardware and uses a commercial fluxgate magnetometer as the reference. This setup reduces the complexity of the proposed system when compared to similar ones. This paper presents two distinct results: first, there is the validation and results of the uniformity regarding the generated field around the system's center; second, results of the setup with the closed-loop HiL simulation are shown, which includes tests of the coil when generating a dynamic magnetic field.
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  • 24
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    Information for Authors (2018)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2018-02-09
    Description: Provides instructions and guidelines to prospective authors who wish to submit manuscripts.
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  • 25
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    Utilizing Out-of-Sequence Measurement for Ambiguous Update in Particle Filtering (2018)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2018-02-09
    Description: This paper proposes a novel method to cope with local measurement ambiguity problem in particle filtering. The ambiguity of the measurement has been attributed as a crucial cause of filter degradation and divergence. Given the observation that the ambiguous measurement update is contributed by not only the shape of the measurement model but also the prior distribution of the filter estimate, we adopt a solution to the out-of-sequence measurement problem on the framework of the particle filter with sequential importance resampling. Once an ambiguous measurement update is detected, the proposed method skips the measurement update at the time step and utilizes the measurement later when the particle distribution becomes adequate for the measurement update. This strategy provides a remedy to the ambiguity problem to obtain accurate current position estimate with lower covariance. Numerical simulation is presented to demonstrate effectiveness and performance of the proposed method. Compared to other methods, such as the standard particle filter, the auxiliary particle filter, the mixture particle filter, and the receding-horizon Kalman filter, the proposed method shows better performance in terms of root-mean-square error and estimated covariance.
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    Table of contents (2018)
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    Publication Date: 2018-02-09
    Description: Presents the table of contents for this issue of this publication.
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    From the Editor-in-Chief (2018)
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    Publication Date: 2018-02-09
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    Detection of Range Migrating Targets in Compound-Gaussian Clutter (2018)
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    Publication Date: 2018-02-09
    Description: This paper deals with the problem of coherent radar detection of fast-moving targets in a high-range resolution mode. In particular, we are focusing on the spiky clutter modeled as a compound Gaussian process with rapidly varying power along range. Additionally, a fast-moving target of interest has a few range cells migration within the coherent processing interval. Two coherent CFAR detectors are proposed taking into account target migration and highly inhomogeneous clutter. Both detectors involve solution of a transcendental equation, carried out numerically in a few iterations. The performance evaluation is addressed by numerical simulations and it shows a significant improvement in detection of fast-moving targets in inhomogeneous heavy tailed radar clutter.
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    Fall Detection Using Deep Learning in Range-Doppler Radars (2018)
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    Publication Date: 2018-02-09
    Description: In this paper, we propose an approach that uses deep learning to detect a human fall. The proposed approach automatically captures the intricate properties of the radar returns. In order to minimize false alarms, we fuse information from both the time-frequency and range domains. Experimental data is used to demonstrate the superiority of the deep learning based approach in comparison with the principal component analysis method and those methods incorporating predefined physically interpreted features.
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    Spectrum Allocation for Noncooperative Radar Coexistence (2018)
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    Publication Date: 2018-02-09
    Description: Access to the electromagnetic spectrum is an ever-growing challenge for radar. Future radar will be required to mitigate RF interference from other RF sources, relocate to new frequency bands while maintaining quality of service, and share frequency bands with other RF systems. The spectrum sensing, multioptimization (SS-MO) technique was recently investigated as a possible solution to these challenges. Prior results have indicated significant improvement in the signal-to-interference plus noise ratio at the cost of a high computational complexity. However, the optimization computational cost must be manageable in real time to address the dynamically changing spectral environment. In this paper, a bioinspired filtering technique is investigated to reduce the computational complexity of SS-MO. The proposed technique is analogous to the processing of the thalamus in the human brain in that the number of samples input to SS-MO is significantly decreased, thus, resulting in a reduction in computational complexity. The performance and computational complexity of SS-MO and the proposed technique are investigated. Both techniques are used to process a variety of measured spectral data. The results indicate a significant decrease in computational complexity for the proposed approach while maintaining performance of the SS-MO technique.
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    Detection of Multiple Movers Based on Single Channel Source Separation of Their Micro-Dopplers (2018)
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    Publication Date: 2018-02-09
    Description: Studies have demonstrated the usefulness of micro-Doppler signatures for classifying dynamic radar targets such as humans, helicopters, and wind turbines. However, these classification works are based on the assumption that the propagation channel consists of only a single moving target. When multiple targets move simultaneously in the channel, the micro-Dopplers, in their radar backscatter, superimpose thereby distorting the signatures. In this paper, we propose a method to detect multiple targets that move simultaneously in the propagation channel. We first model the micro-Doppler radar signatures of different movers using dictionary learning techniques. Then, we use a sparse coding algorithm to separate the aggregate radar backscatter signal from multiple targets into their individual components. We demonstrate that the disaggregated signals are useful for accurately detecting multiple targets.
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    Blinding Guidance Against Missiles Sharing Bearings-Only Measurements (2018)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2018-02-09
    Description: A novel “blind and evade” guidance concept for an aerial target, which is exposed to a threat of two homing missiles, is presented. Each missile is assumed to measure solely its own line-of-sight (LOS) angle and share it with the other missile. Such information sharing enables the missiles to form a triangular measuring baseline relative to the target and to improve their estimation accuracy. However, if the separation angle between the two LOS vectors is small enough, the observability of such double-LOS measuring approach becomes weak. Motivated by this observation, the idea of the proposed concept is to bring the missiles on the same LOS with the target, i.e., blinding them, and then perform an appropriately timed target evasive maneuver. The target's guidance law is derived under the assumption of perfect information and formulated as an optimal control problem. Simulation results demonstrate the potential of the proposed defense concept.
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    Path Planning and Collision Avoidance for a Multi-Arm Space Maneuverable Robot (2018)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2018-02-09
    Description: In this paper, a path planning algorithm for a multi-arm space robot is proposed. The robot is capable of maneuvering on the exterior of a large space station. Based on the maneuver strategy, continuous and smooth trajectories of the manipulator end effectors are first determined via the polynomial interpolation method. Then, the kinematics describing the relation between the end effector and the joint angles as well as the platform are formulated. A Moore–Penrose pseudoinverse solution of the joint trajectories is calculated to describe the motion of the manipulators, particularly, considering the singularity avoidance. In addition, a collision detection algorithm is developed to estimate the security during operation. Constraints are formulated by considering collision avoidance, based on which a collision-free trajectory is optimized through the multiplier-penalty method. The numerical results of a triple-arm space robotic system are given to demonstrate the effectiveness of the proposed algorithms.
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    An Efficient Recursive Multiframe Track-Before-Detect Algorithm (2018)
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    Publication Date: 2018-02-09
    Description: Multiframe track-before-detect (MF-TBD) usually uses sliding-window-based batch processing, where a number $N$ of the latest data frames are jointly processed at each measurement time. The sliding window mechanism compromises the operating efficiency of MF-TBD by increasing both computational costs and memory requirements, thus, heavily restricting its application in practical problems. In this paper, an improved recursive implementation for MF-TBD is proposed. Unlike the sliding-window-based implementation, the proposed method calculates the merit function, a measure of the possibility that a state is target originated, of the current batch based on an approximated recursive relationship between the merit functions of consecutive batches. As a result, instead having to process the whole batch, at any given time only the latest frame needs to be processed. The recursive relationship is first derived for any arbitrary merit function, and then explored further with several typical merit functions that are used in MF-TBD. Both the theoretical analysis and simulation results demonstrate that the proposed method can achieve almost $N$ times reduction in computational complexity and memory requirements with negligible performance loss.
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    An INS Monitor to Detect GNSS Spoofers Capable of Tracking Vehicle Position (2018)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2018-02-09
    Description: In this paper, we describe and evaluate a new monitor that uses inertial navigation system (INS) measurements to detect spoofing attacks on global navigation satellite system (GNSS) receivers. Spoofing detection is accomplished by monitoring the Kalman filter innovations in a tightly coupled INS/GNSS mechanization. Monitor performance is evaluated against worst case spoofing attacks, including spoofers capable of tracking vehicle position. There are two main contributions of this paper. The first is a mathematical framework to quantify postmonitor spoofing integrity risk. The second is an analytical expression of the worst case sequence of spoofed GNSS signals. We then apply these to an example spoofing attack on a Boeing 747 on final approach. The results show that GNSS spoofing is easily detected, with high integrity, unless the spoofer's position-tracking devices have unrealistic, near-perfect accuracy, and no delays.
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    Maintenance of Libration Point Orbit in Elliptic Sun–Mercury Model (2018)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2018-02-09
    Description: The maintenance of the nominal multirevolution elliptic halo orbit, whose special features can benefit mercurial explorations, is first investigated through Monte–Carlo simulations in the elliptic Sun–Mercury model, and then validated in the high-fidelity ephemeris model. The receding horizon control strategy solved by the indirect Radau pseudospectral method demonstrates that the orbit can be maintained robustly with respect to very large initial deviations. Moreover, the result proves that the elliptic Sun–Mercury model is an accurate approximation.
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    ISAR Imaging Algorithm of Multiple Targets with Complex Motions Based on the Fractional Tap Length Keystone Transform (2018)
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    Publication Date: 2018-02-09
    Description: Complex motions of targets cause migration through resolution cells which leads to the inverse synthetic aperture radar (ISAR) image blurred and makes difficulties to follow-up work such as identification, recognition, and classification. In this paper, a novel ISAR imaging algorithm based on the fractional tap length keystone transform (FTLKT) is proposed for multiple targets with complex motions. In noncooperation case, different targets behave variously. For phase coupling of different orders, the proposed algorithm first employs FTLKT to achieve decoupling of the frequency and slow time variable, then detection of Doppler peaks is applied for ambiguity resolution of different targets. According to this, focused ISAR images of different targets are obtained. Simulation results demonstrate the validity of the proposed algorithm.
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    Maritime Moving Target Indication Using Passive GNSS-Based Bistatic Radar (2018)
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    Publication Date: 2018-02-09
    Description: This paper is a first introduction to the concept of using global navigation satellite systems (GNSS) as illuminators of opportunity in a passive bistatic real-time radar system for maritime target indication applications. An overview of the system concept and the signal processing algorithms for moving target indication is provided. To verify the feasibility of the system implementation as well as test the developed signal processing algorithms, an experimental test bed was developed and the appropriate experimental campaign with the new Galileo satellites and a ferry as the target was carried out. The results confirm the system concept and its potential for multistatic operation, with the ferry being detected simultaneously by two satellites.
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    Robust Fuzzy Tracking Control of Flexible Spacecraft via a T–S Fuzzy Model (2018)
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    Publication Date: 2018-02-09
    Description: This paper presents a robust fuzzy tracking controller for position and attitude control, and for vibration suppression in a flexible spacecraft. The robust fuzzy controller guarantees $H_{infty }$ tracking control performance while satisfying the actuators’ amplitude constraints. The design problem of the fuzzy tracking controller is formulated in terms of linear matrix inequalities. The stability, performance, and robustness of the proposed fuzzy controller are examined and compared with a baseline nonlinear controller such as the model-reference adaptive controller with $sigma$ -modification via numerical simulations.
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    Resonance-Based Procedure for Locating Failed Luminaires in AGL Systems (2018)
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    Publication Date: 2018-02-09
    Description: Aeronautical ground lighting (AGL) systems provide a visual reference for aircraft during airport operations. Fast detection and location of failed luminaires is an important safety concern in AGL systems. In the event of luminaire failure, AGL transformers introduce harmonic currents. Resonances can increase harmonics, worsening the problem. This paper presents analytical expressions for determining resonance frequencies in AGL systems, as well as a simple procedure based on these expressions for locating failed luminaires from measurements.
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    Model Predictive Control for the Flow Field in an Intermittent Transonic Wind Tunnel (2018)
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    Publication Date: 2018-02-09
    Description: To accurately test aircraft models, the flow field featured by the stagnation pressure and the Mach number must be kept constant at the predefined state during wind tunnel tests. The objective of this study is to design a multivariable controller to quickly reject various disturbances for the varying angle of attack (AoA) tests in a large-scale Intermittent Transonic Wind Tunnel (ITWT). First, the flow field control structure is specially designed to simplify the controller design. Next, a novel AoA model (i.e., Hammerstein model) with corresponding modeling approach is developed to characterize the influence of varying AoA on the static pressure. Finally, the flow field controller is designed in the offset-free model predictive control (MPC) framework, which uses the feedforward strategy to compensate for the varying AoA disturbance and copes with other unknown disturbances and model mismatch using the augmented model method. Simulation results and practical wind tunnel tests prove the effectiveness of the proposed modeling and control methods.
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    Asynchronous Passive Multisensor System Observability With Unknown Sensor Position (2018)
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    Publication Date: 2018-02-09
    Description: A method is derived for forming composite measurements when the line-of-sight measurements from multiple sensors are asynchronous and the position(s) of one or more passive sensors is (are) unknown. Using the composite measurement, the target position, velocity, and unknown sensor location are estimated. Additionally, general analytical observability conditions are derived.
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    Data-Dependent Clustering-CFAR Detector in Heterogeneous Environment (2018)
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    Publication Date: 2018-02-09
    Description: This paper devises a new constant false alarm rate (CFAR) detection scheme to deal with the problem of radar target detection in heterogeneous environment. The proposed scheme, called “clustering-CFAR detector,” is data dependent and composed of three stages: an adaptive clustering procedure that, exploiting the recorded measurements of the clutter environment, divides the detection area into different classes to provide auxiliary information, a dynamic reference cell selector that chooses appropriate secondary data according to the classes, and a conventional CFAR processor to make the final decision about the target presence. The performance of “clustering-CFAR detector” is analyzed by computer simulation and public radar measured data (IPIX data and MSTAR data), and compared with existing CFAR detectors. The results show that the new detector achieves a better performance in the aspects of terrain classification, control of false alarm points, and probability of detection.
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    GNSS Interference Detection Using Statistical Analysis in the Time-Frequency Domain (2018)
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    Publication Date: 2018-02-09
    Description: This paper presents a precorrelation interference detection method based on statistical analysis in the time-frequency (TF) domain for global navigation satellite system signals. In particular, the short-time Fourier transform (STFT) is considered as the TF tool due to its linear property and low computational complexity. A goodness-of-fit (GoF) test is applied to each frequency slice in the spectrogram of the received signal, which approximately follows a chi-square distribution in the absence of interference. The expected probability density function (PDF) of the observed TF-domain samples can be computed based on an interference-free signal or the noise power estimate. Two versions of the proposed technique are presented: one based on the canonical STFT with the maximum overlap size, and the other based on the block-wise STFT using nonoverlapped samples. The canonical STFT-based method shows better detection capability at the expense of degraded false alarm performance caused by the PDF distortion in the canonical STFT samples. The block-wise STFT-based method alleviates the false alarm issue but slightly weakens the detection capability. Simulations show that the proposed canonical and block-wise STFT-based methods improve the detection performance for both narrow- and wideband interference in low jammer-to-noise ratio environments when compared with the existing GoF test applied to the time-domain samples.
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    Multipath Maximum Likelihood Probabilistic Multihypothesis Tracker for Low Observable Targets (2018)
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    Publication Date: 2018-02-09
    Description: In many practical scenarios with multipath propagation, one target may generate multiple detections in one scan. Proper use of multipath-induced measurements can improve the detection of very low observable (VLO) targets. In this paper, a true multitarget tracker, the joint multipath maximum likelihood probabilistic multihypothesis tracker (JMP-ML-PMHT) is proposed to address this problem. The standard ML-PMHT is extended to incorporate multipath detections and jointly track multiple VLO targets. The Cramer–Rao lower bound with multipath detections is derived. Simulation results with an over-the-horizon-radar scenario show that the JMP-ML-PMHT can detect and track multiple VLO targets by effectively utilizing the information in multipath measurements.
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    Technical Areas and Editors: AESS IEEE Aerospace & Electronic Systems Society (2018)
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    Publication Date: 2018-02-09
    Description: Provides a listing of current committee members and society officers.
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    A SPR Glucose Sensor Based on Immobilized Glucose Oxidases and Silica Mesocellular Foams (2018)
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    Publication Date: 2018-02-24
    Description: An improved glucose-sensitive membrane (GSM) was prepared by immobilizing glucose oxidases (GODs) onto silica mesocellular foams and trapping them in a polyacrylamide gel. This gel was then coated on a gold/glass sheet to realize surface plasmon resonance (SPR) sensors. A series of sensing experiments was conducted to obtain the optimized parameters with the improved GSM. The experimental results showed that the improved SPR glucose sensor has a sensitivity of 0.0135 degree/(mg/dL) and a linear range of 0–160 mg/dL. This linear range is twice that obtained with the GSM by immobilizing GODs on SiO 2 nanoparticles.
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    TDLAS-Based Detection of Dissolved Methane in Power Transformer Oil and Field Application (2018)
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    Publication Date: 2018-02-24
    Description: Methane is one of the indicative gases in power transformer oil, and the detection of methane dissolved in oil with high accuracy is of great importance for dissolved gases analysis and fault diagnosis inside power transformers. Based on the Beer–Lambert spectral absorption law, dissolved methane detection with tunable diode laser absorption spectrum (TDLAS) is proposed in this paper for the advantages of high sensitivity and resolution. On the basis of wavelength modulation spectroscopy, a specialized TDLAS system was established. To meet the actual needs of field testing, the anti-vibration design of an integrated Herriott cell and a gas pressure (P)/temperature (T) setting are worked out. Photodetector, collimator, and Herriott cell are integrated into one component to reduce the effects of vibration. It is investigated that the temperature has little effect on the second harmonic amplitude in the range of 30 °C ~ 50 °C, and the vacuum pressure is reasonably set at about 1 kPa. Experimental results showed that the resolution of sensitivity could be reached as 6.8 mV/( $mu$ L/L), the maximum deviation was less than $pm 4~mu$ L/L, and the response time is less than 5 min. In the end, field application was also carried out, proving it is a prospective online sensing technique to serve oil-immersed power transformers better.
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    FPGA Implementation of Steinhart–Hart Equation for Accurate Thermistor Linearization (2018)
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    Publication Date: 2018-02-24
    Description: This paper presents fixed point operation-based Field Programmable Gate Arrays (FPGA) implementation of Steinhart–Hart Equation (SHHE) for thermistor linearization. FPGA implementation issues of SHHE are presented and their solutions are proposed and experimentally validated in a LabVIEW TM environment. Experimental temperature calibration, performed using a M/S Fluke drywell calibrator, revealed a lowest nonlinearity of 0.11% for an industrial grade thermistor in the input temperature range from −20 °C to 120 °C. Therefore, the main contribution of this work is to demonstrate the lowest nonlinearity for a wider temperature range. This work is expected to be very useful to instrumentation engineers as it employs a time-tested technique, for thermistor linearization in FPGA, leading to the lowest nonlinearity for a larger input temperature range.
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    Miniaturized Six-Degree-of-Freedom Force/Moment Transducers for Instrumented Teeth With Single Sensor Chip (2018)
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    Publication Date: 2018-02-24
    Description: This paper reports on a novel force/moment transducer small enough to replace the root of an artificial tooth. Its dimensions of 4.5 mm in diameter and 16.4 mm in height are identical to the former state-of-the-art design. However, the new design requires a significantly reduced assembly effort and imposes lower demands on the external read-out periphery. The latter improvement facilitates the simultaneous operation of a larger number of force/moment transducers. The novel design was optimized using the finite-element analysis, whose results are experimentally validated. The new design and the former state-of-the-art design are extensively tested with the same test procedure for ranges of ±3 N and ±30 Nmm. The measurement accuracies are measured to be 10, 23, and 64 mN for the forces $f_{x}$ , $f_{y}$ , and $f_{z}$ , respectively, and $161times 10^{-3},,text {Nmm}$ , $302times 10^{-3},,text {Nmm}$ , and $42times 10^{-3},,text {Nmm}$ for the moments $m_{x}$ , $m_{y}$ , and $m_{z}$ . Despite the simpler assembly effort and device handling, the accuracy is better or at least close to former designs. Especially, the more critical force measurements are significantly improved. Long-term stability tests show only little change in measurement performance of the two designs in time.
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    Surface Acoustic Wave Viscosity Sensor with Integrated Microfluidics on a PCB Platform (2018)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2018-02-24
    Description: This paper illustrates the extension of Rayleigh wave-based surface acoustic wave (SAW) viscosity and density sensor previously developed by the authors for integration with microfluidics and printed circuit board (PCB)-based electronics. The SAW device is first modeled with a microchannel and analyzed using finite-element method (FEM) software. Precise fabrication, alignment, and bonding of polydimethylsiloxane microchannels on diced $Y$ - $Z$ lithium niobate substrates are accomplished. A high-frequency PCB is built to obtain a better performance for SAW device testing. Low glycerin concentrations in deionized (DI) water are analyzed. The FEM simulation results and vector network analyzer measurements of the devices with the microchannel and PCB integration are presented. For low-frequency SAW sensor, a sensitivity of 171.9 Hz/(% glycerin) or 5.57 kHz/(kg/ $text{m}^{2}surd text{s}$ ) in frequency shifts, 0.09°/(% glycerin) or 2.92°/(kg/ $text{m}^{2}surd text{s}$ ) in phase difference, and minimum signal-to-noise ratio of 13.9 dB are achieved at peak frequency of 29.7 MHz. On the other hand, high-frequency (86.1 MHz) SAW sensor provides a sensitivity of 937.5 Hz/(% glycerin) or 37.15 kHz/(kg/ $text{m}^{mathbf {2}}surd text{s}$ ) in absolute frequency shifts, 0.37°/(% glycerin) or 14.7°/(kg/ $text{m}^{mathbf {2}}surd text{s}$ ) in phase difference, and minimum signal-to-noise ratio - f 20.5 dB.
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    Dynamic Calibration for Permanent Distributed Temperature Sensing Networks (2018)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2018-02-24
    Description: Distributed Temperature Sensing (DTS) is a technique that uses the interaction of laser pulses with silica to continuously sense temperature along the length of fiber-optic cables. The temporal and spatial resolution of DTS makes it an excellent technique for monitoring the performance of district-scale geothermal exchange borefields. A dynamic, double-ended calibration routine developed in response to site-specific challenges and constraints (i.e., more than 5 km, many splices, different fiber segments, and extended observation periods) is systematically presented and analyzed to provide novel insight on calibration considerations. Results show that different combinations of calibration baths may change calibration accuracy, and over determination in the calculation of calibration parameters provides greater accuracy. Fixing the $gamma $ calibration parameter does not appreciably change accuracy but does provide a buffer against error from variations in calibration bath temperatures. Differential attenuation varied by up to 25% between discrete fiber sections and should be calculated for each array section to prevent errors generated from applying just one attenuation coefficient value for the entire fiber array. Furthermore, dynamically calculated differential attenuation may vary systematically with time and space. In a double-ended configuration, the consideration of whether the forward, reverse, or some combination of all light data is used will affect the robustness of the calibration over time. Each of these results may assist in thoughtful consideration of calibration design at future DTS installations facing similar challenges.
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    Design and Characterization of High-Density Ultrasonic Transducer Array (2018)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2018-02-24
    Description: This paper is conducted to design, fabricate, and characterize a novel high-density large-scale ultrasonic transducer, which is based on a $64times 4$ array of 0.753 MHz piezoelectric micromachined ultrasonic transducer (pMUT) with $100~mu text{m}$ size and $120~mu text{m}$ pitch. The fill factor of the array is 69.4%, which is higher than the other arrays in reports. Sol-gel method with layer-by-layer annealing is used to fabricate isolated piezoelectric lead zirconate titanate elements into a piezoelectric layer. The membrane of the pMUT is released by backside deep silicon etching. The impedance-frequency spectrum of a $4times 5$ subarray of the transducers is characterized by HP 4294A impedance phase analyzer. As a result, the mean value resonant frequency is 0.753 MHz, in reasonable agreement with COMSOL Multiphysics simulation results. And the array shows good uniformity in resonant frequency. The equivalent circuit of the transducer is extracted from the spectrum and the admittance circle deduced from the circuit is in accordance with experimental data. The results show that the present array has a good application prospect on ultrasonic imaging.
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    Dynamic Mechanical Analysis on a PolyMethyl Methacrylate (PMMA) Polymer Optical Fiber (2018)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2018-02-24
    Description: Curvature sensors based on polymer optical fibers (POFs) present some advantages over the conventional technologies for joint angle assessment such as compactness, electromagnetic field immunity, and multiplexing capabilities. However, the polymer is a viscoelastic material, which does not have a constant response with stress or strain. In order to understand and model this effect, this paper presents the dynamic characterization of a POF. The effects of temperature, frequency, and loads on the fiber are analyzed for obtaining the influence of these parameters on the polymer dynamic Young modulus and time constant. Results show that a temperature on the range between 24 °C and 45 °C does not lead to considerable variations on the sensor output. Moreover, it is possible to estimate the storage modulus and loss factor from the frequency and temperature. The polymer time constant is defined on creep recovery experiments. Since the viscoelastic parameters are evaluated in different conditions of temperature, frequency, and load, a model for the stress behavior of the fiber is proposed. Such model leads to a root mean squared error between the modeled and measured results over 15 times lower than the one obtained with the model for bending stress without account the POF viscoelastic behavior.
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    Optical Properties and Molar Hemoglobin Concentration of Skeletal Muscles Measured In Vivo With Wearable Near Infrared Spectroscopy (2018)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2018-02-24
    Description: Near-infrared spectroscopy (NIRS) is a widely-used noninvasive optical technique for measuring concentration of hemoglobin species in human tissues. Despite its potential, NIRS has seen limited clinical application largely due to a lack of in-vivo standard reference. Hence, cross-validation studies to validate novel NIRS instrumentation against established NIRS devices are needed. This in-vivo study compared a wearable continuous-wave (CW-NIRS) oximeter against a non-wearable frequency-domain (FD-NIRS) oximeter on optical properties and hemoglobin concentrations. To measure absolute coefficients and stoichiometric hemoglobin concentrations, the CW-NIRS oximeter exploits spectral properties of water. Both CW-NIRS and FD-NIRS provided physiologically-valid measurements in skeletal muscles during normoxia, hypoxia, and hyperemia. Although absorption-scattering crosstalk was evident, absorption coefficient $mu _{a}$ and reduced scattering coefficient $mu '_{s}$ at 690nm and deoxyhemoglobin concentration (HbR) were mostly within agreement limits, and the measurements differed principally by a systematic offset. Specifically, CW-NIRS estimated larger $mu '_{s}$ values (+2 cm −1 ) and smaller $mu _{a}$ (from −0.04 to −0.08 cm −1 ) at all wavelengths. The results suggest that lower-cost, wearable CW-NIRS oximeters are a potential alternative to FD-NIRS to measure optical properties and molar concentration of oxyhemoglobin and HbR in skeletal muscles in-vivo as long as the estimated water content is reasonably accurate.
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    Simultaneous Measurement of Hydrogen Concentration and Temperature Based on Fiber Loop Mirror Combined With PCF (2018)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2018-02-24
    Description: Simultaneous measurement of hydrogen concentration and temperature with high sensitivity and high precision was realized by integrating a photonic crystal fiber (PCF) modal interferometer and a high-birefringence fiber loop mirror (HBFLM). The PCF was coated with sol-gel Pd/WO 3 coating, whose refractive index and volume would be changed along with the variation of surrounding hydrogen concentration or temperature, and then the resonant dip of PCF modal interferometer would shift accordingly. Meanwhile, the resonant dip of the HBFLM has a high sensitivity to surrounding temperature. By integrating PCF modal interferometer and HBFLM together, the two independent resonant dips that can be simultaneously monitored at the output spectrum of the integrated interferometers would all shift with the change of external hydrogen concentration or temperature. Finally, combined with the dual-wavelength matrix method, the hydrogen concentration and temperature could be simultaneously measured. Experimental results showed that the resonant dip of the PCF modal interferometer moved in the short wavelength direction with the increase of hydrogen concentration, and the sensitivity of the hydrogen concentration was −1.12 nm/% within the concentration range from 0% to 1%. In the process of temperature change, the HBFLM realized a higher temperature sensitivity of −1.84 nm/°C. The sensor had high sensitivity, low cost, and simple structure.
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    Rapid and Reusable Detection of Interferon-Gamma Based on Label-Free Single-Stranded DNA and Thioflavin T (2018)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2018-02-24
    Description: A novel simple and rapid detection method for interferon-gamma (IFN- $gamma$ ) was developed based on a label-free single-stranded DNA (ssDNA) and thioflavin T (ThT). The ssDNA is the aptamer of the IFN- $gamma $ . The aptamer is a G-rich oligonucleotide, and it can fold into a G-quadruplex structure in the presence of ThT, resulting in a high fluorescence emission. Upon the addition of the target, the aptamer combines with its ligand due to higher affinity and specificity, leading to the disruption of the G-quadruplex and the release of ThT. A remarkable decrease of fluorescence was observed. The proposed strategy shows a limit of detection at 1 nM in both buffer and diluted serum. Moreover, the detection of IFN- $gamma $ can be finished in several minutes and it can be used repeatedly.
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    An Angular Displacement Sensor With a Curved Two-Metal-Layer CPW Loaded by an EBG Structure (2018)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2018-02-24
    Description: This paper presents a microwave angular displacement sensor that consists of a curved two-metal-layer coplanar waveguide (TML CPW) loaded by an electromagnetic bandgap structure (two semi-cylindrical periodic air-gap structures of dielectrics, allocated at the top and bottom of the curved TML CPW). Rotating one of the dielectrics against the other one, produces a variation in the depth of the stopband at the central frequency. The magnitude change is proportional to the angle of the rotation. The curved TML CPW line with the length of 140 mm is fabricated on a $254~mu text{m}$ thick RO3010 Rogers substrate ( $varepsilon _{r} = 10.2$ and $tan delta = 0.0022$ ), which is arched in a semi-cylindrical shape with a radius of 50 mm. The periodic air-gap structures, in order to create the electromagnetic bandgap, are manufactured by laser cutting of an optically transparent polycarbonate ( $varepsilon _{r} = 2.8$ and $tan delta =0.01$ ) in semi-cylindrical shapes. The analysis, finite element method simulation, realization, and measurements have been performed for the sensor with 15 unit cells. An average sensitivity and a dynamic range of about 3 dB/deg and 5° degrees, respectively, have been obtained at 10.2 GHz. The fixed operating frequency and the wide bandwidth of the sensor (>1 GHz) will simplify the design and fabrication of the data readout circuit. The impact of the structure curvature on the sensor response is also investigated as an important practical issue.
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    Novel Approach for InSAR Sensors Imaging via Gradient-Based Algorithm for the Sparse Signal Reconstruction (2018)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2018-02-24
    Description: It is well known that the interferometric synthetic aperture radar (InSAR) can be used to realize the reconstruction of digital elevation models. In common InSAR imaging, the signal is considered complete and accurate enough to generate high-quality images. However, only the sparse aperture measurements are available in the actual imaging process, which bring great challenges to the traditional InSAR imaging algorithms. In this paper, a new method for the 3-D InSAR imaging with sparse aperture is proposed. A gradient-based algorithm is adopted to obtain the high-precision reconstructed signal received from each sparse aperture antenna. Then, the 3-D geometric reconstruction of the target can be realized through the interferometric processing on the master and slave images. Finally, the experimental results are given to substantiate the effectiveness of the proposed algorithm.
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    A System for Detection and Tracking of Human Movements Using RSSI Signals (2018)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2018-02-24
    Description: A device-free human detection and tracking system using a received signal strength indicator (RSSI) for an indoor environment is presented in this paper. The proposed system has two major functions: a wireless communication system and a human detection and tracking system. The first function is developed for measuring and collecting RSSI signals affected by human presence and movement, while the second function is developed for detecting and tracking the human using a predefined threshold and a zone selection method. The novelty of our proposed system is that the communication protocol can avoid signal interference and packet loss in the network, and the detection and tracking method can specify an actual zone that the human is present by taking an optimal predefined threshold and a level of RSSI variation in each zone into consideration. The proposed system is verified by experiments, and various human movement patterns with different directions and speeds are tested. The experimental results show that the proposed communication protocol can significantly provide communication reliability, and the proposed method can properly detect and track human movements. The packet delivery ratio indicating communication reliability is almost 100%. Detection and tracking accuracy measured by the number of times the method can detect and track the human with the correct zone is almost 100% in all cases of one man movements.
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    A Novel Graphene-Grafted Gold Nanoparticles Composite for Highly Sensitive Electrochemical Biosensing (2018)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2018-02-24
    Description: The use of affordable amendments required increasing the sensitivity and functionality of electrochemical devices is still challenging. Novel scalable, gold nanoparticles-grafted nitrogen-doped graphene nanostructured polyaniline nanocomposites were stupendously developed in this paper. The charge transfer resistance was dramatically decreased from 11000 $Omega $ (for bare fluorine doped tin oxide electrode) down to 115 $Omega $ (for the nanocomposite-modified electrode). The present nanocomposites provided a superb opportunity for the design of electrochemical biosensors with extraordinary performance via enhanced analyte sensitivity for the detection of ascorbic acid (0.640 mM detection limit at signal to noise ratio = 3, and two linear ranges of 0.96–4.66 and 5.06–9.86 mM with the sensitivity of 10.44 and $28.91~mu text{A}$ . mM $^{-1}$ . cm $^{-2}$ , respectively), and high selectivity over electroactive components interfering species, commonly found in real serum samples.
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    Recognition of Human Behavior for Assisted Living Using Dictionary Learning Approach (2018)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2018-02-24
    Description: The ambient assisted living (AAL) technology aims to provide more safety and self-sufficiency, while permitting older persons to live self-dependently in their homes. Monitoring of activities of daily living (ADL) is one of the key ideas of AAL. This becomes an interesting research idea in modern world, where condition monitoring of various ADLs and their automatic classification is a big challenge. This paper proposes a new approach for activity recognition of motion primitives relying on the sparse representation of signals, where signals are represented using a sparse combination of atoms from an over-complete dictionary. This paper intends to investigate the suitability of applying dictionary learning algorithms like K-singular value decomposition (K-SVD), which is usually used to construct an over-complete dictionary, for the effective progress of the ADL monitoring system. This paper proposes to formulate the classification approach by using SRC classifiers, based on the dictionaries learned using K-SVD algorithm. We have validated our proposed approach on a publicly available ADL data set of wrist-worn accelerometer sensor for activity recognition. Performance evaluations demonstrate that the proposed method outperforms several other competing methods.
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    Throughput in an Energy Harvesting Wireless Uplink (2018)
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    Publication Date: 2018-02-24
    Description: In this paper, throughput maximization in a wireless energy harvesting uplink is considered. For fairness, we assume that each node’s throughput cannot drop below what it achieves by direct transmission to the base station. The throughput is maximized using data relaying and by optimally assigning a role to each node, i.e., relay, source (direct transmission), or user (of a relay). Both centralized and decentralized algorithms that find the optimal assignment of each node are proposed and studied. We consider fixed and variable transmit power scenarios and address complexity issues. Our algorithms are shown to have a linear or quadratic complexity compared with the exponential complexity of the brute force approach. Compared with cooperative transmission, our approach maximizes the overall throughput of the network such that no node’s throughput is adversely affected.
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    IEEE Sensors Council Information (2018)
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    Publication Date: 2018-02-24
    Description: Presents a listing of the editorial board, board of governors, current staff, committee members, and/or society editors for this issue of the publication.
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    Multi-Sensor Information Filtering With Information-Based Sensor Selection and Outlier Rejection (2018)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2018-02-24
    Description: Nowadays, multi-sensor networks are evolving into large scale networks with limited bandwidth and energy reservoirs. Hence, reducing the number of information exchanges among the sensors is an efficient approach to meet the stringent requirements of bandwidth and energy in the context of multi-sensor state estimation. In this paper, a surprisal-based multi-sensor information filtering is proposed to allow on average a desired number of sensors with most informative measurements to participate in the information exchange, while discarding the sensors with non-informative measurements and outliers. The concept of surprisal is used to facilitate the sensors in the network to independently classify their measurements as informative, non-informative and outliers by setting upper and lower thresholds. Simulation results show that the proposed scheme ensures that on average only a desired number of sensors with the most informative measurements participate in the information exchange and achieves greater estimation accuracy compared to the method, where the sensors are selected randomly for the same number of transmissions.
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    Target Discrimination for SAR ATR Based on Scattering Center Feature and K-center One-Class Classification (2018)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2018-02-24
    Description: Target discrimination plays an important role in the typical synthetic aperture radar (SAR) automatic target recognition (ATR) system. The conventional discrimination features roughly describing the difference between the target and the clutter are useful to discriminate the target from natural clutter, but these features may not well discriminate the target from the artificial clutter. To solve the above problem, a new algorithm for target discrimination is proposed based on the scattering center feature and the K-center one-class classification in this paper. The amplitudes and locations of the scattering centers have not been used as discrimination feature to our best knowledge, even though the distributions of the scattering centers associated with the targets are different from those of the natural clutter and artificial clutter. Then, since the scattering center feature is a typical kind of point set feature, we improve the K-center one-class classification based on Hausdorff distance (HD), where HD is a distance measure for the point set feature. Experimental results based on the measured MiniSAR dataset show that the discrimination performance of the scattering center feature is better than that of the conventional discrimination features, especially for the artificial clutter.
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    A Compressive Sensing-Based CMOS Image Sensor With Second-Order $Sigma Delta$ ADCs (2018)
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    Publication Date: 2018-02-24
    Description: This paper presents a new analog-to-digital conversion scheme for a second-order $Sigma Delta $ incremental analog to digital converter (ADC) that can be employed in a compressive sensing (CS)-based CMOS image sensor (CIS) as a column-parallel ADC. The conversion scheme removes image distortion from a reconstructed image by making the ADC output codes represent an average of the ADC inputs. In addition, a new multiplexing scheme implementing a compressive sensing matrix helps to reduce hardware complexity and control compression ratio without hardware modifications. A $160times 160$ pixel CS-based CIS fabricated in $0.11~mu text{m}$ CIS process successfully demonstrates the proposed schemes.
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    Introducing IEEE Collabratec (2018)
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    Publication Date: 2018-02-24
    Description: Advertisement, IEEE.
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    IEEE Sensor Journal cover/frontispiece competition (2018)
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    Publication Date: 2018-02-24
    Description: Presents information on the IEEE Sensor Journal cover/frontispiece competition.
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    Gas Diffusion Cell Geometry for a Microfluidic Dissolved Inorganic Carbon Analyzer (2018)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2018-02-24
    Description: Variable gas diffusion cell geometries were tested for the extraction of dissolved inorganic carbon (DIC) from a microfluidic (tens to hundreds of microliters) seawater sample. With a focus on optimization of diffusion cell geometry, we compare five unique diffusion cell designs. Using 3-D printing technology to streamline the prototyping and testing process, we were able to conceive, design, fabricate, and thoroughly evaluate each design over the course of about one month. In total, 1043 DIC measurements were carried out in 109 experiments for the five working manifolds. We find that a small diameter, cylindrical diffusion cell design offers several advantages over its planar counterparts and a larger diameter cylindrical cell, most notably the ability to increase the ratio of the exchange membrane’s contact surface area to solution volume (the “aspect ratio”) without sacrificing channel integrity. Multiple designs approached short-term repeatability of <1%, but only the cylindrical diffusion cell design allowed for <0.2% repeatability using less than 200 $mu text{L}$ of sample.
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    WDM-VLC Receiver Sensors: Large-Scale Filter-Array Detectors With Optimized Selection Combining Methods (2018)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2018-02-24
    Description: Due to the continuous improvement of solid-state lighting technologies, multispectrum, multicolor LEDs have been used as transmitters for wavelength division multiplexing visible light communication (WDM-VLC) techniques. Although the multispectrum LEDs can emit light with different wavelengths for multichannel transmission, the overlapped spectra across the WDM channels could cause high interband multichannel interferences (IBMCI). Accordingly, the large-scale filter-array detectors (LFDs) have been adopted to WDM-VLC techniques and shown high capability for the IBMCI rejection using the maximum signal-to-interference-plus-noise ratio (SINR) combining (MSC) method. However, in the MSC method, it requires 100% filter array usage ratio, which would potentially result in costly computational complexity. In this paper, we propose two approaches, namely, conjugate gradient (CG) algorithm approach and binary particle swarm optimization (BPSO) algorithm approach, for sparse filter selection. According to both simulation and experimental results, the proposed CG algorithm approach can significantly reduce the filter array usage ratio by up to 70% while maintaining a good detector output SINR. The proposed BPSO algorithm approach can provide a near optimal detector output SINR while maintaining a good reduction of filter array usage ratio.
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    Limit of Detection for Five Common Adulterants in Milk: A Study With Different Fat Percent (2018)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2018-02-24
    Description: Milk adulteration is one of the most dishonest food preparation, which not only reduces the nutritional value but also causes various diseases to human. Some of the common adulterants are detergents, ammonium sulphate [(NH 4 ) 2 SO 4 ], sodium hydroxide (NaOH), sodium-bi-carbonate (NaHCO 3 ), and common salt (NaCl). The aim of this paper is to identify the minimum detectable limit for the above five adulterants in milk. An impedance sensor is used, which is sensitive to the ionic concentration of the measuring medium and gives different phase angle of the impedance, when immersed in different adulterated/unadulterated milk. Signal transduction circuit is designed to convert the phase angle to voltage and for display in liquid crystal display. By this detection system, the limit of detection of adulterants in milk with different fat % (from 1.5% to 20%) is studied. Commercial packet milk, ultra high temperature milk, and raw-milk (directly collected from the milk collection center) are used for the experiment. Experimental results are plotted in origin software and statistical analysis method analysis of variance is applied on experimental data for verification of the result and to check the data consistency.
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    The Inductor as a Smart Sensor for Material Identification in Domestic Induction Cooking (2018)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2018-02-24
    Description: In induction home appliances, the characterization of the physical properties of the vessel allows for better control strategies and new cooking functionalities. Current modelling techniques calculate a simple ${R}$ – ${L}$ equivalent circuit that models the inductor impedance taking into account all the physical coupling parameters, but these techniques do not allow to directly extract the physical parameters, such as vessel material. In this paper, a new methodology for online detection of the pot material is presented. On this approach, the inductor included in the hob simultaneously serves as heating element and sensor. First, harmonic impedances are calculated by spectral estimation from the currents and voltages waveforms recorded at the inductor. Then, a feature set, including four harmonic impedances and the power factor, is processed by machine learning algorithms for the identification of the pot material. The material identification system is implemented onto an embedded processor similar to those included in current induction hobs; thus, smart sensing features are incorporated onto a domestic cooker without using additional sensors, at no additional cost.
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    Multi-Sensor Image Fusion Based on Interval Type-2 Fuzzy Sets and Regional Features in Nonsubsampled Shearlet Transform Domain (2018)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2018-02-24
    Description: Multi-scale geometric analysis, one of the most often-used multi-sensor image fusion (MSIF) techniques, can offer outstanding performance during extracting the features of source image. Interval type-2 fuzzy sets (Type-2 FS) have a good prospect in image fusion field, because it can effectively address the uncertain and fuzzy problem in image fusion for selecting the high-quality pixels or coefficients of source images. We try to extend the application fields of Type-2 FS and improve the performance of MSIF; therefore, this paper presents a hybrid method by combining the local spatial frequency (LSF) with interval Type-2 FS in nonsubsampled shearlet transform (NSST) domain. NSST is used to decompose source images, and interval Type-2 FS and LSF is employed to extract the regional features of source images; so it can extract and fuse the detailed features of different source images accurately. First, NSST is performed to decompose the source images into low frequency and high frequency sub-images. Second, LSF-based fusion rule is applied to fuse low frequency sub-images. Thirdly, a novel fusion process based on interval Type-2 FS is designed to fuse high frequency sub-images. At last, inverse NSST2 (INSST) is implemented to reconstruct the fused images. The experimental and contrastive results of different image sets show that the proposed method is an effective MSIF scheme, which can achieve better fusion effect than the existing representative methods.
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    Reversible and Fast Responsive Optical Fiber Relative Humidity Sensor Based on Polyelectrolyte Self-Assembly Multilayer Film (2018)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2018-01-10
    Description: A high-performance fiber-optic relative humidity (RH) sensor was prepared by layer-by-layer self-assembly of polycation, poly (4-vinylpyridinium chloride), and polyanion, sodium alginate, on the surface of a thin-core fiber modal interferometer. The process of layer-by-layer self-assembly was monitored by UV-vis spectroscopy and surface profilometer. The morphology of the fabricated multilayer film was characterized by atomic force microscopy and field emission scanning electron microscopy. A fast, reversible, and linear response to RH with a high resolution of 0.1 nm/1% RH has been experimentally demonstrated by the proposed fiber-optic sensor.
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    Femtosecond Laser Inscribed Small-Period Long-Period Fiber Gratings With Dual-Parameter Sensing (2018)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2018-01-10
    Description: A small-period long-period grating (LPG) with a period of $40mu text{m}$ fabricated in a single-mode fiber by femtosecond laser direct writing has been demonstrated. A series of high-order Bragg resonant peaks of Bragg grating and attenuation bands of LPG can be observed simultaneously in the broadband spectrum range that exhibited different responses to surrounding refractive index, temperature, and axial strain. Meanwhile, we provided a sensitivity matrix to correct the errors caused by temperature in measurements of refractive index and strain to achieve a dual-parameter fiber sensor at high temperature.
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    A Simple Equation to Describe Cross-Sensitivity Between Temperature and Refractive Index in Fiber Bragg Gratings Refractometers (2018)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2018-01-10
    Description: In this paper, we propose a simple nonlinear equation to describe the cross-sensitivity between temperature and refractive index in fiber Bragg grating refractometers. A numerical analysis using Comsol Multiphysics software was performed to understand how the effective index changes with the temperature and refractive index. The sensor response to refractive index (from 1.33 to 1.45) and temperature (from 15 °C to 45 °C) was fitted using a surface equation. Even though the refractive index range considered being significantly large, and the sensor response being nonlinear, proper concordance between computer simulations and experiments point out that this multivariable equation is suitable to describe the Bragg wavelengths as a function of temperature and refractive index. When applied to multimode fiber Bragg gratings, the proposed equation can be used to construct a system of equations to calculate temperature and refractive index from the measured Bragg wavelengths.
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    Measurement of Oil–Water Two-Phase Flow Phase Fraction With Ultrasound Attenuation (2018)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2018-01-10
    Description: Phase fraction of oil–water two-phase flow is important to the process control and optimization. In this paper, a prediction model based on the mechanism of ultrasound attenuations in oil–water mixture is presented to estimate the phase fraction. This model consists of physical parameters of the two-phase flow and ultrasound frequency, by incorporating the scattering and attenuation of ultrasound in different flow patterns of the oil–water two-phase flow. The nonlinear relationship between ultrasound attenuation coefficient and phase fraction is corrected. An array of 16 ultrasonic transducers with 1-MHz center frequency and 20-Vpp sine acoustic signal is presented to implement this method, and a measuring system was designed and tested on a multiphase flow loop with actual flow experiments. The proposed prediction model showed a good agreement with the online phase fraction calibration in the flow experiments. The average error is 2.3% in water continuous flow, while in 2.8% in oil continuous flow. These findings and the mechanism prediction model provide basic foundations for the phase fraction estimation of oil–water two-phase flow by using the ultrasound attenuation technique.
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    Cartesian Factorized Backprojection Algorithm for High-Resolution Spotlight SAR Imaging (2018)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2018-01-10
    Description: Compared with the original backprojection (BP) algorithm, the fast factorized BP algorithm accelerates enormously. As it is known to all, 2-D image interpolations are always utilized to raise the accuracy, yet leadings to the tradeoff with the efficiency. In this paper, a novel factorized BP algorithm based on Cartesian coordinate without interpolation, is proposed for high-resolution spotlight SAR with much better efficiency and accuracy. The innovative idea is achieved by establishing two spectrum compressing filters to decrease the cross-range Nyquist sampling rate enormously, thus avoid spectrum aliasing. The proposed algorithm, termed as the Cartesian factorized BP (CFBP) algorithm, can produce images with the similar quality as the BP does, but is better than FFBP, where the interpolations accumulate errors to some extent. The CFBP is designed for spotlight mode working in both the linear and curved trajectories. Simulation results and real-data processing validate the superiorities of CFBP by the comparisons with FFBP and the original BP individually.
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    Sub-Nyquist Sampling Jamming Against Chirp-ISAR With CS-D Range Compression (2018)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2018-01-10
    Description: Compressed sensing (CS) for sparse backscattering field recovery from very limited measurements has received increasing attention among the radar imaging community. The chirp (i.e., linear frequency modulated) waveform, benefiting from a large time-bandwidth product, is widely utilized in imaging radars, such as synthetic aperture radars (SARs) and inverse SARs (ISARs). In this paper, the influence of sub-Nyquist sampling jamming on ISAR with chirp waveform is investigated, where the CS-based dechirping (CS-D) algorithm is applied to achieve range compression of the under-sampled jamming signals. The jamming signals, formed by the intercepted radar signals under the sub-Nyquist sampling theorem and scattered by the moving targets, are collected by ISAR to form a (2-D) array and the azimuth compression is done via conventional Fourier transform. The main novelty of this framework is twofold: 1) the CS-D range compression of the under-sampled jamming signals is characterized and 2) the potential of sub-Nyquist sampling jamming is demonstrated against ISAR with the CS-D range compression. Simulated trials and real data of a Yak-42 plane are used to validate the correctness of the analyses and finally, the well-focused false-target images greatly support the effectiveness of the sub-Nyquist sampling jamming idea in the countermeasures of chirp-ISAR with the CS-D range compression.
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    Three-Dimensional Bubble Shape Estimation in Two-Phase Gas-Liquid Slug Flow (2018)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2018-01-10
    Description: Wire-mesh sensors produce 3-D data of void fraction distribution at high resolution thus being an appropriate tool to investigate two-phase gas-liquid flows. Slug flow is typically found in petroleum production lines. This type of flow is characterized by the intermittent occurrence of gas bubbles and liquid slugs along the pipe. An important issue of these flows is the existence of a variety of regimes, depending on the flow rates of gas and liquid. The quantitative and qualitative information about shapes of the bubble nose and tail allows to study and to model the flow characteristics in order to increase safety and efficiency of oil production operations. In this paper, we describe two methods to estimate typical bubble shape from wire-mesh sensor data, which are based on ensemble mean and median approaches. Results from a set of two-phase flow experiments in inclined tubes, show that both approaches produce similar estimations, however since median is a type of robust estimator, contours of bubbles are better defined. 3-D images of typical bubbles, for eight different operational conditions, were generated and reveal some details about bubble shape. In addition, the bubble identification was validated by measuring the gas flow rate in comparison with reference instrumentation.
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    Accurate and Robust Displacement Measurement for FMCW Radar Vibration Monitoring (2018)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2018-01-10
    Description: Non-contact displacement measurement based on the phase-based microwave interferometry technology has attracted growing interest in recent years. In this paper, aiming to exploit the frequency-modulated continuous wave (FMCW) radar-based vibration monitoring technique, the principle and detailed procedure for extracting the displacement time series of vibration movement are illustrated. The approximate maximum likelihood approach is proposed to extract the phase history of beat signals across multiple sweep periods. Moreover, the measurement accuracy of vibration displacement extraction and several practical issues of this technique are evaluated and concerned. Both simulated and experimental validations are provided to show the effectiveness and robustness of the proposed method and approach.
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    Improving the Robustness of Prediction Model by Transfer Learning for Interference Suppression of Electronic Nose (2018)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2018-01-10
    Description: This paper gives a solution to solve the interference problem of electronic nose (e-nose), which is ill-posed due to the uncertainty and unpredictability of its instable behavior. Traditional methods for interference suppression are component correction frameworks, which are laborious or little efficient. With interference (especially background interference and sensor drift), the distribution of test data obtained in practical application is different from that of the previous training data. From the viewpoint of machine learning, a novel domain correction and adaptive extreme learning machines (DC-AELM) framework with transferring capability is proposed to solve the serious interference problem in e-nose. The framework consists of two parts: 1) DC, which makes the distributions of two domains close and 2) AELM, which realizes the knowledge transfer at the decision level and makes the robustness of the prediction model improved. This method is motivated by the idea of transfer learning, especially from the perspective of domain correction and decision-making, to realize the knowledge transfer for interference suppression. A background interference data set obtained by our designed e-nose and a public benchmark sensor drift data set are used to verify the effectiveness of the proposed DC-AELM method.
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    Generalized Co-Prime MIMO Radar for DOA Estimation With Enhanced Degrees of Freedom (2018)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2018-01-10
    Description: In this paper, we propose a generalized co-prime multiple-input multiple-output (MIMO) configuration for direction of arrival estimation. Compared with the conventional co-prime MIMO radar that requires prototype co-prime arrays for transmitter and receiver, the proposed configuration enlarges the inter-element spacing of transmitter with an integer expansion factor. By vectorizing the sample covariance matrix, the generalized sum and difference coarray (GSDC) concept is defined for exploiting the advantages of proposed configuration. The analytical expressions for the expansion factor, the maximum consecutive lags, and the number of unique lags are derived carefully. It is verified that GSDC can obtain more degrees of freedom (DOFs) with the increase of expansion factor. Specifically, with $mathcal {O}(M+N)$ sensors, GSDC can provide $mathcal {O}(M^{2}N^{2})$ DOFs, whereas the conventional one only has $mathcal {O}(MN)$ DOFs. Simulation results demonstrate the usefulness of proposed configuration utilizing both spatial smoothing and sparse representation algorithms.
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    A 10 mW, 0.4 $mu text{g}/surd $ Hz, 700 Hz $Sigma Delta $ High-Order Electromechanical Modulator for a High-Q Micromechanical Capacitive Accelerometer (2018)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2018-01-10
    Description: A switched-capacitor sigma–delta ( $Sigma Delta $ ) CMOS interface circuit for the closed-loop operation of a micromechanical capacitive accelerometer is presented in this paper. A distributed-feedback and feedforward topology is proposed to combine with a high-Q sensor element to obtain a sub- $mu text{g}/surd $ Hz noise floor. The loop stability is implemented by damping the high-Q sensor element in the operation of electrostatic feedback force and heavy phase compensation, which introduces an extra zero to compensate the loop. Besides, the low-frequency loop gain is controlled by off-chip adjusting of distributed-feedback factor to keep the balance between the loop stability and noise shaping ability. The interface circuit is designed and fabricated in a standard 0.5- $mu text{m}$ CMOS process. The chip consumes 10 mW from a single 5-V supply. The measurement results show that the noise level is lower than 400 ng/ $surd $ Hz, and the average noise equivalent acceleration density is 200 ng/ $surd $ Hz over a 700-Hz bandwidth. The input range of the accelerometer is ±0.7 g resulting in a dynamic range of 125 dB over 1-Hz bandwidth. The measured sensitivity of 2.5 V/g is shown with a dc nonlinearity of 0.17%, and the bias instability is $19~mu text{g}$ .
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    A Fiber Bragg Grating Sensor Perimeter Intrusion Localization Method Optimized by Improved Particle Swarm Optimization Algorithm (2018)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2018-01-10
    Description: Intrusion localization plays a significant role in a perimeter system. A precise intrusion localisation method using fiber Bragg grating (FBG) sensors is proposed in this paper. Based on the fixed-simply supported beam theory, FBG strain data are used to establish the intrusion deflection distribution. The intrusion localisation and force identification are realized by deflection curve analysis. In order to optimize the identifying result, an improved particle swarm optimization algorithm is introduced. The experiments and simulation results show that the proposed algorithm performs better than the traditional algorithms in detection precision and stability for intrusion signal identifying.
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    Qualitative and Quantitative Analysis of Selected Tonic Waters by Potentiometric Taste Sensor With All-Solid-State Electrodes (2018)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2018-01-10
    Description: Taste sensor with five all-solid-state electrodes (ASSE) III (third version) was used for qualitative and quantitative analysis of selected tonic waters (J.Gasco, Kinley, Jurajski, Jurajski with citrus flavor, Carrefour, Schweppes Indian Tonic, and Schweppes Bitter Lemon). The results obtained by this taste sensor analyzed with principal component analysis, agglomerative hierarchical clustering methods show that this sensor can be applied for discrimination of tonic waters with respect to their composition. Based on sensor’s results, two models for prediction of the content of quinine hydrochloride and total saccharides in selected tonic waters were developed using multivariate linear regression. The results obtained by this analysis in comparison to nominal data (experimentally determined and obtained from manufacturers’) are consistent (range of 0.1%–1.8%). It means that taste sensor with five ASSE III may be a useful tool for the qualitative and quantitative analysis of selected tonic waters.
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    Balanced 20-kA DC Distributor for Magnetized Taylor Couette Systems, Utilizing Thermostatic Controlled Water Valves With CO 2 Adsorption Charge Sensors as Current Controller (2018)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2018-01-10
    Description: A quasi-coaxial system consisting of a central current carrying copper rod and five symmetric return paths takes up to 20 kA. The installation provides a homogeneous magnetic field $mathbf {B_{varphi }}$ to a Taylor–Couette flow. One challenging part of the system is the design of the current distributor, which is supposed to divide the return current into several equally weighted lines. The individual components like the copper rods as well as all electrical contacts provide a characteristic resistance, each in the same magnitude of several $ {mu }Omega $ . By initial installation this will support an imbalance in the current distribution affecting the symmetry of the magnetic field. So the adjustment of current distribution becomes mandatory to ensure maximum field homogeneity. Controlling the outflow temperature of the required water cooling offers an indirect access to set the current by thermostatically operated valves with CO 2 adsorption charge in conjunction with the temperature dependent branch resistance. A numerical investigation proves that a stable current distribution can be achieved by a couple of paralleled thermal controlled heater valves with proportional characteristics. Finally, recent ironless Hall-effect current sensors help to calibrate the system so that the current homogeneity differs less than 1% from optimal state in a wide range of currents.
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    Human Activity Classification in Smartphones Using Accelerometer and Gyroscope Sensors (2018)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2018-01-10
    Description: Activity classification in smartphones helps us to monitor and analyze the physical activities of the user in daily life and has potential applications in healthcare systems. This paper proposes a descriptor-based approach for activity classification using built-in sensors of smartphones. Accelerometer and gyroscope sensor signals are acquired to identify the activities performed by the user. In addition, time and frequency domain signals are derived using the collected signals. In the proposed approach, two descriptors, namely, histogram of gradient and centroid signature-based Fourier descriptor, are employed to extract feature sets from these signals. Feature and score level fusion are explored for information fusion. For classification, we have studied the performance of multiclass support vector machine and $k$ -nearest neighbor classifiers. The proposed approach is evaluated on two publicly available data sets, namely, UCI HAR data set and physical activity sensor data. Our experimental results show that the feature level fusion provides better performance than the score level fusion. In addition, our approach provides considerable improvement in classifying different activities as compared with the existing works. The average activity classification accuracy achieved using the proposed method is 97.12% as against the existing work, which provided 96.33% on UCI HAR data set. On the second data set, the proposed approach attained 96.83% classification accuracy, whereas the existing work achieved 90.2%.
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    An Embedded Wireless Temperature Sensor for Orthopedic Implants (2018)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2018-01-10
    Description: A wireless and passive (battery free) temperature sensor that can be embedded inside an orthopedic implant, such as an interference screw, was developed. The sensor is based on an inductive–capacitive–resistive resonant circuit that is inductively powered so the temperature at the implant can be measured wirelessly. A potential application of this sensor is to monitor internal wound temperature for the diagnosis of local infection at the implant site. Infections pose a significant risk to patients, who receive orthopedic implants, often lead to adverse conditions including implant failure, tissue necrosis, and amputation. Current approaches for diagnosing orthopedic implant-associated infections, such as blood tests, radiographic imaging, and histological study are slow, tedious, and nonspecific. In recent years, thermographic imaging has been used to monitor local temperature at the external surgical site as a means to detect infection, but its applications are limited to surface or near-surface wounds. The described sensor will serve as an useful research tool to investigate using temperature as an indication of deep-tissue orthopedic implant infection. When fully developed, this sensor may also improve orthopedic care by allowing simple, early detection of infection at an implant site. This paper describes the design and fabrication of the sensor, as well as characterizes its performance. Experimental results indicate the temperature response of the sensor is reproducible within the tested range of 30–42 °C.
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    Simultaneous Bayesian Recognition of Locomotion and Gait Phases With Wearable Sensors (2018)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2018-01-10
    Description: Recognition of movement is a crucial process to assist humans in activities of daily living, such as walking. In this work, a high-level method for the simultaneous recognition of locomotion and gait phases using wearable sensors is presented. A Bayesian formulation is employed to iteratively accumulate evidence to reduce uncertainty, and to improve the recognition accuracy. This process uses a sequential analysis method to autonomously make decisions, whenever the recognition system perceives that there is enough evidence accumulated. We use data from three wearable sensors, attached to the thigh, shank, and foot of healthy humans. Level-ground walking, ramp ascent and descent activities are used for data collection and recognition. In addition, an approach for segmentation of the gait cycle for recognition of stance and swing phases is presented. Validation results show that the simultaneous Bayesian recognition method is capable to recognize walking activities and gait phases with mean accuracies of 99.87% and 99.20%. This process requires a mean of 25 and 13 sensor samples to make a decision for locomotion mode and gait phases, respectively. The recognition process is analyzed using different levels of confidence to show that our method is highly accurate, fast, and adaptable to specific requirements of accuracy and speed. Overall, the simultaneous Bayesian recognition method demonstrates its benefits for recognition using wearable sensors, which can be employed to provide reliable assistance to humans in their walking activities.
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    Slide: Towards Fast and Accurate Mobile Fingerprinting for Wi-Fi Indoor Positioning Systems (2018)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2018-01-10
    Description: The deployment of Wi-Fi fingerprint-based indoor positioning systems is severely hindered by the lack of an efficient and low-cost way to establish a signal fingerprint database. In this paper, we present a novel fingerprinting method, slide , that can collect fingerprints in a fast and accurate way. Slide uses a commodity flashlight and a smartphone to achieve linear positioning . This allows automatic mapping from the received signal strength to the position on a line, serving as a building block for fingerprinting in general environments. Slide also features a channel-based scanning method, which acquires fingerprint location after each Wi-Fi channel scanning, to mitigate the fingerprint misalignment problem found in the general mobile fingerprinting. Quantitative analysis and experimental results show that slide is faster than the manual fingerprinting method by up to an order of magnitude with comparable positioning accuracy, and is also more efficient than state-of-the-art mobile fingerprinting methods.
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    Topics: Electrical Engineering, Measurement and Control Technology
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    Deep-Learning-Based Earth Fault Detection Using Continuous Wavelet Transform and Convolutional Neural Network in Resonant Grounding Distribution Systems (2018)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2018-01-10
    Description: Feature extraction for fault signals is critical and difficult in all kinds of fault detection schemes. A novel simple and effective method of faulty feeder detection in resonant grounding distribution systems based on the continuous wavelet transform (CWT) and convolutional neural network (CNN) is presented in this paper. The time-frequency gray scale images are acquired by applying the CWT to the collected transient zero-sequence current signals of the faulty feeder and sound feeders. The features of the gray scale image will be extracted adaptively by the CNN, which is trained by a large number of gray scale images under various kinds of fault conditions and factors. The features extraction and the faulty feeder detection can be implemented by the trained CNN simultaneously. As a comparison, two faulty feeder detection methods based on artificial feature extraction and traditional machine learning are introduced. A practical resonant grounding distribution system is simulated in power systems computer aided design/electromagnetic transients including DC, the effectiveness and performance of the proposed faulty feeder detection method is compared and verified under different fault circumstances.
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    Smart Wearable Hand Device for Sign Language Interpretation System With Sensors Fusion (2018)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2018-01-10
    Description: Gesturing is an instinctive way of communicating to present a specific meaning or intent. Therefore, research into sign language interpretation using gestures has been explored progressively during recent decades to serve as an auxiliary tool for deaf and mute people to blend into society without barriers. In this paper, a smart sign language interpretation system using a wearable hand device is proposed to meet this purpose. This wearable system utilizes five flex-sensors, two pressure sensors, and a three-axis inertial motion sensor to distinguish the characters in the American sign language alphabet. The entire system mainly consists of three modules: 1) a wearable device with a sensor module; 2) a processing module; and 3) a display unit mobile application module. Sensor data are collected and analyzed using a built-in embedded support vector machine classifier. Subsequently, the recognized alphabet is further transmitted to a mobile device through Bluetooth low energy wireless communication. An Android-based mobile application was developed with a text-to-speech function that converts the received textinto audible voice output. Experiment results indicate that a true sign language recognition accuracy rate of 65.7% can be achieved on average in the first version without pressure sensors. A second version of the proposed wearable system with the fusion of pressure sensors on the middle finger increased the recognition accuracy rate dramatically to 98.2%. The proposed wearable system outperforms the existing method, for instance, although background lights, and other factors are crucial to a vision-based processing method, they are not for the proposed system.
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    Topics: Electrical Engineering, Measurement and Control Technology
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    A Footwear-Based Methodology for Fall Detection (2018)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2018-01-10
    Description: Automatic fall detection is an active research area since several years. Basically, this is motivated by the impact that falls have, in terms of mortality, morbidity, and social costs, which make them comparable to road traffic injuries. The early detection of a fall can be critical to reduce the mortality rate and to limit the associated health consequences. Technological solutions designed to automatically detect and notify a fall may be classified into wearable and non-wearable. Among the former ones, the use of specific devices to be worn by the subject is a very common assumption, but it fails to address user’s acceptability issues. In fact, the position of the sensor or its visibility may be perceived as a stigma associated with the primary function of fall detection. To address such an issue, this paper presents a methodology for fall detection that relies on a pair of smart shoes, equipped with force sensors and a tri-axial accelerometer, able to detect a fall and notify it to a supervising system. The instrumented footwear enables the analysis of the subject’s motion and foot orientation, recognizing abnormal configurations. The developed algorithm is not computationally intensive, and therefore, can be easily executed on board the wearable device. Laboratory tests provided satisfactory performances in falls detection and correct classification: on 544 falls and 136 activities of daily living, performed by 17 healthy subjects, a 97.1% accuracy has been achieved. Further experiments involving two elderly users demonstrate the effectiveness of the proposed method in a real-life scenario.
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    Comments on “Delay Compensation of Tilt Sensors Based on MEMS Accelerometer Using Data Fusion Technique” (2018)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2018-01-10
    Description: Experimental study presented in “Delay Compensation of Tilt Sensors Based on MEMS Accelerometer Using Data Fusion Technique” by M. Ghanbari and M. J. Yazdanpanah is commented. It seems that some of the reported results are affected by errors related to mechanical imperfections of the applied test apparatus, what might have influenced determination of parameters of models of the applied complementary and Kalman filters. Appropriate modifications of the test apparatus are proposed. An alternative method of processing the experimental data is suggested.
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    6-D Electromagnetic Tracking Approach Using Uniaxial Transmitting Coil and Tri-Axial Magneto-Resistive Sensor (2018)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2018-01-10
    Description: The real-time electromagnetic tracking method has been widely applied, despite its limitations such as a high computational cost and complex hardware components. In this paper, a simple and efficient electromagnetic tracking approach, with both 3-D and 6-D pose tracking, is proposed. This approach utilizes the geomagnetic field and the magnetic field generated by the 2.5-kHz sinusoidal signal from a uniaxial transmitting coil. By extracting both the alternating current (AC) and direct current (DC) components from the outputs of a miniature tri-axial magneto-resistive sensor, the position and orientation parameters of the sensor can be computed by using the combination of the geomagnetic orientation algorithm and the magnetic dipole model-based localization algorithm. Since the implementation of the tracking algorithm is based on a sextic equation, this proposed approach is simple and fast. Experimental results show that the root-mean-square value of the position error is 2.6±0.79 mm and the orientation error is 1.4±0.61°. This tracking approach has simple structures of both software and hardware but promising performance and applicability.
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    Capability Characterization via Ex- Vivo Experiments of a Fiber Optical Tip Force Sensing Needle for Tissue Identification (2018)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2018-01-10
    Description: This paper deals with the capability characterization of a recently developed novel fiber optical tip force sensing needle. The needle can directly measure the axial force required to penetrate a tissue at its tip, which can then be used for in vivo identification of tissues through either a robotic or a manual needle procedure. To characterize the needle’s force sensing capability, ex- vivo experiments are conducted using both phantom human tissues and swine belly tissues. Various factors relevant to tissue identification are investigated, including needle advancing rate and displacement, automated and manual modes of needle insertion, needle-tissue frictional force, and types of tissues. Furthermore, data of forces versus types of tissue are obtained for tissue identification, based on phantom and swine tissue insertions. By means of this database, two tissue identification experiments are performed, which are a multiple layered tissue and swine muscle with neoplasm tissue with the insertion being repeated 15 times per tissue. The result shows that 66.7% of the multiple layered tissue and 86.7% of the neoplasm tissue are successfully identified.
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    The WSN Monitoring System for Large Outdoor Advertising Boards Based on ZigBee and MEMS Sensor (2018)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2018-01-10
    Description: With the increase of large outdoor advertising boards, the issues of public safety raised by the collapse of outdoor advertising boards have attracted great public concern. In this paper, a wireless sensor network (WSN) monitoring system is designed for the structural health monitoring of large outdoor advertising boards. By using the WSN technology, this system can judge the security of the outdoor advertising boards and give early warnings when the boards are being in danger. The monitoring system consists of two subsystems, one is the WSN structure system based on ZigBee wireless sensor nodes with a six-axis MEMS motion sensor integrated to capture the movement information, and the other is the monitoring center system controlled by ARM microcontroller for data processing and long-distance wireless communications with remote server through a GPRS module. The simulation model of outdoor advertising board is also built to analyze the deformed shape of the advertising board structure under wind load, and the early warning judgment standard is proposed. The performance of the monitoring system is evaluated through several experiments under the condition of laboratory in different aspects of the comparison experiments. The experimental results indicate that the WSN monitoring system can real timely and accurately monitor the state of the outdoor advertising boards.
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    IMU Sensor-Based Electronic Goniometric Glove for Clinical Finger Movement Analysis (2018)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2018-01-10
    Description: Arthritis remains a disabling and painful disease, and involvement of finger joints is a major cause of disability and loss of employment. Traditional arthritis measurements require labour intensive examination by clinical staff. These manual measurements are inaccurate and open to observer variation. This paper presents the development and testing of a next generation wireless smart glove to facilitate the accurate measurement of finger movement through the integration of multiple IMU sensors, with bespoke controlling algorithms. Our main objective was to measure finger and thumb joint movement. These dynamic measurements will provide clinicians with a new and accurate way to measure loss of movement in patients with rheumatoid arthritis. Commercially available gaming gloves are not fitted with sufficient sensors for this particular application, and require calibration for each glove wearer. Unlike these state-of-the-art data gloves, the inertial measurement unit glove uses a combination of novel stretchable substrate material and nine degree of freedom inertial sensors in conjunction with complex data analytics to detect joint movement. Our novel iSEG-Glove requires minimal calibration and is therefore particularly suited to the healthcare environment. Inaccuracies may arise for wearers who have varying degrees of movement in their finger joints, variance in hand size or deformities. The developed glove is fitted with sensors to overcome these issues. This glove will help quantify joint stiffness and monitor patient progression during the arthritis rehabilitation process.
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