ALBERT

Description: The potential abilities of distributed multiple-radar architectures in the electronic counter–countermeasure are analyzed based on the difference between target echoes and deception jamming in spatial scattering properties. The deception signals received by different receivers are fully correlated, while the correlation of target echoes varies gradually with the interval of view angles. According to this difference, the thought of signal fusion is first adopted and a corresponding algorithm is proposed to discriminate the deception jamming from radar targets in the Neyman–Pearson sense. In this algorithm, active false targets are identified by correlation tests between arbitrary two targets’ complex envelopes in different receivers. To evaluate its discrimination performance, the theoretical expression for the rejection probability of false targets is derived. Simulations verify the feasibility of the new algorithm and its performance improvement over the existing data fusion-based methods. The merit of the method lies in that it can discriminate deception signals generated by arbitrary modulation and can be used in series with data fusion-based methods to improve discrimination performance further.

Description: A non-contact capacitance type liquid-level transducer for a conducting liquid consists of a short circuited non-inductive coil wound on a uniform cylinder made of insulating material, such as glass, PVC, nylon, and teflon. The cylinder is connected with a storage tank through a metallic connector and the capacitance between upper short circuited end of the coil and metallic connector varies linearly with liquid level measured from datum level. The capacitance at datum level depends on atmospheric condition and the fringe effect of other conductors. So, the transducers require frequent recalibration depending on atmospheric and environmental conditions. In the present paper, this non-contact capacitive sensor has been further modified in order to minimize this defect of non-contact capacitive sensor. Furthermore, all the conventional capacitance type-level sensors are associated with a perpendicular plate capacitance between liquid and electrode, which varies with the length of the electrode. In this paper, the effect of this perpendicular capacitor on liquid level measured has been studied and its effect is minimized. The proposed modified transducer has been designed and developed and its theory of operation has been derived. The performance of the developed transducer has been experimentally studied and the experimental results are reported in the paper. A good linear performance characteristic of the transducer with very minimum parasitic capacitance effect has been observed.

Description: Coherent radars have multiple applications; among them, they can obtain multiple pulses and improve the radar detection ability with the help of coherent integration technique. However, the coherent integration performance can be greatly influenced by the range migration (RM), and Doppler frequency migration (DFM) effects for the highly maneuvering targets. In this paper, a fast non-searching method based on adjacent correlation function (ACF) and Lv’s transform (LT), is proposed to realize the coherent integration for a maneuvering target. In particular, it first employs the ACF to correct the RM and reduce the order of DFM. Then, the coherent integration is obtained via LT. The advantage of the presented method is that it can achieve the coherent integration without any searching procedure, and thus the computational cost is reduced significantly. Finally, the simulations are provided to demonstrate the effectiveness.

Description: A new selective and sensitive Lanthanum (La) ions optical sensor based on immobilization of $N$ -(2-aminoethyl)-salicylaldimine (AESI) on a triacetylcellulose membrane was prepared. The prepared optode exhibited a linear range of 30–150 part per billion (ppb) of the La (III) ion concentration with a detection limit of 14.38 ppb. The response time of the newly designed optode was derived within 30–60 s, depending on the La (III) ion concentration, however is independent to the pH of the solution in the range of 3–5. The proposed optode indicated a low detection limit, fast response time, and also remarkable selectivity regarding to the number of transition metals ions (i.e. Ce 3+ , Cu 2+ , Cd 2+ , Cr 3+ , Zn 2+ , Hg 2+ , and Fe 2+ ). The optode was successfully regenerated with a thiourea solution, and its response which might be reversible and reproducible showed the relative standard deviation of less than 1.48%. This optode was applied for determining the La (III) ions in water samples.

Description: This paper considers the problem of emitter location in the presence of an adversary able to inject false information, where both the viewpoints of the adversary and locating network are considered. We begin by developing adversary strategies, which focus on degrading and redirecting the locating network. The locating network uses the time difference of arrival (TDOA) method and estimates the emitter location using both nonlinear least squares (LS) and the robust least median squares (LMS). Specifically, we determine the false sensor position the adversary should inject that maximally impacts the locating network by 1) minimizing the network???s accuracy, and 2) redirecting the network???s emitter location estimate. Similarly, we formulate a network???s strategy for detecting the adversary???s injection and develop a detector able to determine its presence under both adversary strategies. We present both theoretical and numerical results illustrating the effectiveness of the developed strategies.

Description: Delay/disruption tolerant networking (DTN) offers a solution to communications in ???challenged??? networks. Some work has been seen in evaluating the performance of DTN protocols based on simulated or emulated file transfer experiments. However, there is a need for a model of the performance of the DTN Licklider transmission protocol (LTP), which particularly targets reliable data transmission in deep space. In this paper, we present a performance model of LTP-based DTN data transmission in challenging communications characterized by extremely long signal propagation delay, lengthy link disruptions, and highly lossy channels that are typical of deep-space links. The model is verified by file-transfer experiments using a PC-based testbed.

Description: Modeling of the dynamics and disturbances and designing of the precise formation controller are two major problems for the inner-formation flying system (IFFS). This paper introduces a nonlinear, nonautonomous formation dynamics model for IFFS in a general elliptic orbit. This model integrates the newly developed formation dynamics and the detailed disturbance models, including atmospheric drag, solar radiation pressure, and J2 effects. Furthermore, this paper establishes a coupled self-gravitational attraction model for IFFS. After considering such a comprehensive dynamics model, the precise formation control problem of IFFS is researched in detail. By referring to the averaging system, Hurwitz matrix, Lyapunov stability theorem, Matrosov???s theory, and Barbalat???s lemma as preliminaries, four possible controllers are designed, i.e., feedback-linearization plus proportional-derivative (PD) controller, Lyapunov-based controller, virtual potential-based controller, and velocity-free virtual potential-based controller. These controllers are all analyzed by the corresponding stability theories. Some simulations are carried out to testify these controllers, and the results show the effectiveness. By comparing the convergence time and fuel consumption, the velocity-free virtual potential-based controller is proven to be a more advantageous controller.

Description: The fuel-optimal control problem of soft landing becomes a significant challenge due to the highly irregular gravitational field of an asteroid. An indirect method is used to deal with this fuel-optimal control problem. The difficult bang-bang control problem caused by the indirect method is solved through an improved fast homotopic approach. To validate the advanced homotopic method, the landing site is selected in a region where the gravitational field is especially irregular. The results show that this method is effective for the fuel-optimal control problem in an irregular gravitational field. Moreover, the trajectory designed with the fuel-optimal control is taken as a nominal descent trajectory for a sliding mode control. Monte Carlo simulations show that the desired soft landing can be achieved by tracking the fuel-optimal trajectory.

Description: In this paper, a novel framework of sparse kernel learning for support vector data description (SVDD) based anomaly detection is presented. By introducing 0-1 control variables to original features in the input space, sparse feature selection for anomaly detection is modeled as a mixed integer programming problem. Due to the prohibitively high computational complexity, it is relaxed into a quadratically constrained linear programming (QCLP) problem. The QCLP problem can then be practically solved by using an iterative optimization method, in which multiple subsets of features are iteratively found as opposed to a single subset. However, when a nonlinear kernel such as Gaussian radial basis function kernel, associated with an infinite-dimensional reproducing kernel Hilbert space (RKHS) is used in the QCLP-based iterative optimization, it is impractical to find optimal subsets of features due to a large number of possible combinations of the original features. To tackle this issue, a feature map called the empirical kernel map, which maps data points in the input space into a finite space called the empirical kernel feature space (EKFS), is used in the proposed work. The QCLP-based iterative optimization problem is solved in the EKFS instead of in the input space or the RKHS. This is possible because the geometrical properties of the EKFS and the corresponding RKHS remain the same. Now, an explicit nonlinear exploitation of the data in a finite EKFS is achievable, which results in optimal feature ranking. Comprehensive experimental results on three hyperspectral images and several machine learning datasets show that our proposed method can provide improved performance over the current state-of-the-art techniques.

Description: This paper deals with the swath acquisition planning problem for multisatellite Earth observation missions. Given a set of satellites and a mission time frame, the problem we solve consists of selecting a set of acquisitions from the satellites in order to cover a given region of interest during the requested time frame, optimizing a certain objective function.We show that the planning problem can be modeled as a set covering problem, using basic tools of mathematical programming. The formulation of the model requires the solution of a complex computational geometry problem, and therefore the use of heuristics and metaheuristics applies. In this paper, we discuss the efficiency of the constructive phase of a greedy randomized adaptive search procedure algorithm. Computational results comparing the heuristic algorithms with the exact approach are presented.

Description: This paper proposes an efficient method to classify inverse synthetic aperture radar (ISAR) images. The proposed method achieves invariance to translation and rotation of ISAR images by using two-dimensional (2D) Fourier transform (FT) of ISAR images, polar mapping of the 2D FT image, and a simple nearest-neighbor classifier. In simulations using ISAR images measured in a compact range, the proposed method yielded high classification ratios with small-sized data regardless of the location of the rotation center, whereas the existing method was very sensitive to the location of it.

Description: A method for fusing synthetic aperture radar (SAR) images with optical aerial images is presented. This is done in a navigation framework, in which the absolute position and orientation of the flying platform, as computed from the inertial navigation system, is corrected based on the aerial image coordinates taken as ground truth. The method is suitable for new low-price SAR systems for small unmanned vehicles. The primary application is surveillance, and to some extent it can be applied to remote sensing, where the SAR image provides complementary information by revealing reflectivity to microwave frequencies. The method is based on first applying an edge detection algorithm to the images and then optimising the most important navigation states by matching the two binary images. To get a measure of the estimation uncertainty, we embed the optimisation in a least squares framework, in which an explicit method to estimate the (relative) size of the errors is presented. The performance is demonstrated on real SAR and aerial images, leading to an error of only a few pixels (around 4 m in our case), which is a quite satisfactory performance for applications like surveillance and navigation.

Description: This paper presents a sensor-control method for choosing the best next state of the sensors that provide accurate estimation results in a multitarget tracking application. The proposed solution is formulated for a multi-Bernoulli filter and works via minimization of a new estimation-error-based cost function. Simulation results demonstrate that the proposed method can outperform the state-of-the-art methods in terms of computation time and robustness to clutter while delivering similar accuracy.

Description: The Kalman filter has always been applied to enhance the estimation of inertial measurement unit errors and to improve estimation accuracy of navigation states under practical conditions. Therefore, understanding the behaviors and limitations of optimal estimation of the navigation states is instructive and of great importance. In order to provide comprehensive information about the observability and convergence rapidity of the navigation states when implementing a Kalman filter, the basic properties of intuitive linear-algebraic characterizations of stochastic observability will be intensively investigated in this study. We have extended the utilization of the analytic stochastic observability approach for analytic optimization of strapdown inertial navigation systems multiposition stationary alignment. The advantage of analytic explicit formulation of convergence rapidity of the implemented Kalman filter by stochastic observability approach is demonstrated. Compared to numerical simulation methods, the proposed stochastic observability approach can provide analysts with much more analytic information.

Description: Localization of persons that are hidden behind a corner is important in various security situations when the first responders should not be exposed to any threat. This article demonstrates the feasibility of an ultrawideband multipath-exploitation radar for localization in such scenarios. The approach utilizes multibounce echoes of electromagnetic waves that are scattered by the closest person situated behind a corner. We assume that the person does not carry any tag and does not cooperate with the localization system. The multibounce echoes are reflected and diffracted by the surroundings and make the hidden person visible to an operator that is behind the corner. The location estimation relies only on single-channel time-of-arrival data. Measured data are first processed by a background subtraction algorithm, which reveals the multipath evoked by the person. The multipath echoes are detected by a parallel threshold-based detector. A simple global nearest-neighbor algorithm is used for tracking detected echoes and improving their range estimates. The obtained range estimates are assigned to different physical propagation paths of the electromagnetic waves. The location of the person is estimated by fusing the information of the antenna location with respect to its surroundings and the assigned range estimates. The proposed approach is experimentally verified in a scenario where data are measured in real time by an ultrawideband sensor. Experimental results demonstrate that, depending on the scenario geometry, a walking or calmly standing person can be localized up to several meters behind the corner.

Description: Inverse synthetic aperture radar (ISAR) images can be obtained using digital video broadcasting???terrestrial (DVB-T)???based passive radars. However, television broadcast???transmitted signals offer poor range resolution for imaging purposes, because they have a narrower bandwidth with respect to those transmitted by a dedicated ISAR system. To reach finer range resolutions, signals composed of multiple DVB-T channels are required. Problems arise, however, because DVB-T channels are typically widely separated in the frequency domain. The gaps between channels produce high grating lobes in the image domain when Fourier-based algorithms are used to form the ISAR image. In this paper, compressive sensing theory is investigated to address this problem because of its ability to reconstruct sparse signals by using incomplete measures. By solving an optimization problem under the constraint of signal sparsity, passive ISAR images can be obtained with strongly reduced grating lobes. Both simulation and experimental results are shown to demonstrate the validity of the proposed approach.

Description: Mechanically steered scanning radars receive measurements continuously while sweeping the surveillance region. However, most target tracking algorithms, like the multiple hypothesis tracker (MHT) and the joint probabilistic data association (JPDA) techniques, wait for the end of a scan in order to process the measurements and to estimate targets states. This is due to the fundamental assumption of one-to-one association between tracks and measurements and the 360° physical limit of a scan. Associating measurements to initialized tracks and filtering at the end of a complete scan may cause significant delays in target state update. In addition, association may become imperfect due to longer intervals between updates. This issue becomes significant when tracking high-speed targets with low scan rate sensors as in the airborne early warning (AEW) system. In this paper, we present a new dynamic sector processing algorithm using two-dimensional (2-D) assignment for scanning radars that report measurements within the duration of a scan. The full scan is dynamically and adaptively divided into sectors, which could be as small as a single detection, depending on the scanning rate, sparsity of targets, and required target state update speed. Measurement-to-track association, filtering, and target state update are done dynamically while sweeping from one region to another, i.e., continuous track update, limited only by the intermeasurement interval, becomes possible. The proposed algorithm offers low latency while maintaining estimation accuracy in track updates as well as efficient utilization of computational resources compared with standard frame-based tracking algorithms. Experimental results based on rotating radars demonstrate the advantages of the proposed technique.

Description: An iterative ESPRIT-like algorithm is devised for direction-of-departure (DOD) and direction-of-arrival (DOA) estimation in multiple-input multiple-output radar. Our proposal can handle identical DODs and DOAs, and provides autopairing of the angle parameters. Furthermore, it is proved that the multiple signal classification methodology cannot identify (MN ??? 1) targets, where M and N are the element numbers in the transmit and receive antennas, respectively. Simulation results are included to evaluate the performance of the proposed algorithm.

Description: Multiple-input multiple-output (MIMO) radar imaging suffers from performance degradation under carrier offsets across transmitters and receivers. This paper analyzes the impact of carrier offsets on imaging a sparse target, from the perspective of the MIMO point spread function (PSF). Conditions are established for successful support recovery using orthogonal matching pursuit (OMP), and the performance loss is characterized in terms of l2 distance. A sparse imaging algorithm taking into account the perturbation due to carrier offsets is also proposed, which improves upon the OMP algorithm. Numerical experiments corroborate this analysis.

Description: Ambiguity functions (AFs) are obtained for a radar using matched illumination (MI) transmit signals for the detection of range-spread targets in the presence of clutter. The transmit signals are adapted to target and interference spectra and are filtered optimally in the receiver; they are designed to maximize signal-to-interference-and-noise ratio (SINR) power ratios at receiver output. In this paper, expressions for processing gains, spread AFs, and Cramer-Rao bounds on range and Doppler estimates are derived based on likelihood functions. Here, for extended targets, AFs resulting from using optimal MI constant envelope waveforms obtained via phase retrieval techniques demonstrate superior resolution characteristics compared with classic linear frequency-modulated (LFM) signals employing optimal pulse compression. For various target and clutter spectral models, simulation results show that optimally filtered MI signals provide significantly enhanced SINR behavior compared with LFM radar signals. Hopefully, these results set the stage for the induction of MI signaling and receive techniques into conventional radar signal processing and pave the way for realization of one methodology for achieving cognition in radar systems.

Description: In an effort to improve the channel utilization of a warship combat system (WCS), it is necessary to control and manage the large volume of video traffic by considering a strong self-similarity characteristic. We propose a new video traffic management method for the WCS that smooths the traffic of the closed-circuit television surveillance system (CSS) video and encodes the electro-optical tracking system (EOTS) video with low complexity in real time. First, to achieve global and local traffic smoothing for the CSS video traffic, a proper bandwidth allocation interval and a minimum bandwidth for the CSS video traffic must be determined. Second, due to the increased available bandwidth after traffic smoothing, more elaborate low-delay encoding is accomplished by selecting encoding modes adaptively to compress the EOTS video efficiently with high visual quality. The experimental results demonstrate that the proposed method is able to control the WCS traffic to be as flat as possible and to encode the EOTS video with low delay, even in combat and emergency scenarios. Hence, we show that to migrate to network-centric warfare successfully, the proposed method is much more suitable for the WCS than conventional video traffic management.

Description: In this paper, we propose multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) radar with sufficient cyclic prefix (CP), where all OFDM pulses transmitted from different transmitters share the same frequency band and are orthogonal to each other for every subcarrier in the discrete frequency domain. The orthogonality is not affected by time delays from transmitters. Thus, our proposed MIMO OFDM radar has the same range resolution as single transmitter radar and achieves full spatial diversity. Orthogonal designs are used to achieve this orthogonality across the transmitters, with which it is only needed to design OFDM pulses for the first transmitter. We also propose a joint pulse compression and pulse coherent integration for range reconstruction. In order to achieve the optimal signal-to-noise ratio (SNR) for the range reconstruction, we apply the paraunitary filterbank theory to design the OFDM pulses. We then propose a modified iterative clipping and filtering (MICF) algorithm for the designs of OFDM pulses jointly, when other important factors, such as peak-to-average power ratio (PAPR) in time domain, are also considered.With our proposed MIMO OFDM radar, there is no interference for the range reconstruction not only across the transmitters but also across the range cells in a swath called inter-range-cell interference (IRCI) free that is similar to our previously proposed CP-based OFDM radar for single transmitter. Simulations are presented to illustrate our proposed theory and show that the CP-based MIMO OFDM radar outperforms the existing frequency-band shared MIMO radar with polyphase codes and also frequency division MIMO radar.

Description: The minimum-variance filter and smoother are generalized to include Poisson-distributed measurement noise components. It is shown that the resulting filtered and smoothed estimates are unbiased. The use of the filter and smoother within expectation-maximization algorithms are described for joint estimation of the signal and Poisson noise intensity. Conditions for the monotonicity and asymptotic convergence of the Poisson intensity iterates are also established. An image restoration example is presented that demonstrates improved estimation performance at low signal-to-noise ratios.

Description: This paper proposes a new radar/sonar processing architecture that enables a low-rate time-sampling rate while still producing a high-resolution range profile over a narrow range-window. This new architecture generalizes the conventional ???stretch processing??? architecture (which employs linear frequency modulated (LFM) waveforms that suffer from high range-sidelobes), to nonlinear frequency modulated (NLFM) waveforms, which can lower the range-sidelobes without tapering. Computational results demonstrate both the estimation efficacy and the time-sampling efficiency of the proposed scheme.

Description: Free-floating manipulators are subject to dynamic singularities that complicate their Cartesian motions and restrict their workspace. In this work, the Cartesian trajectory planning of free-floating manipulators is studied. A methodology is developed in which, for given end-effector trajectories, appropriate initial system configurations are found that result in singularity avoidance during end-effector motion. The method applies to both planar and spatial systems, with and without initial angular momentum, and to any desired end-effector position and attitude trajectories.

Description: This paper investigates the problem of fusion filtering for a class of networked multisensor fusion systems with multiple uncertainties, including sensor failures, stochastic parameter uncertainties, random observation delays, and packet dropouts. A novel model is proposed to describe the random observation delays and packet dropouts, and a robust optimal fusion filter for the addressed networked multisensor fusion systems is designed using the innovation analysis method. The dimension of the designed filter is the same as that of the original system, which helps to reduce computation cost compared with the augmentation method. Moreover, robust reduced-dimension observation-fusion Kalman filters are proposed to further reduce the computation burden. Note that the designed fusion filter gain matrices can be computed off-line, as they depend only on the upper bounds of random delays and on the occurrence probabilities of delays and sensor failures. Some sufficient conditions are presented for stability and optimality of the designed fusion filters, and a steady-state fusion filter is also given for the networked multisensor fusion systems. Simulations show the effectiveness of the proposed fusion filters.

Description: Presents the 2015 author/subject index for this publication.

Description: Magnetic sensors have previously been used for position measurement only at very small distances between the magnet and the sensor. While they could potentially also be used at larger distances by exploiting nonlinear magnetic field functions, a serious challenge comes from magnetic disturbances. The presence of foreign ferromagnetic objects, variations in the Earth’s magnetic field with location, and electromagnetic disturbances can cause such position estimation systems to have significant errors. This paper enables robust large-distance position estimation using redundant sensors and real-time disturbance estimation. Adaptive estimation algorithms that auto-calibrate magnetic parameters and compensate for disturbances are developed. Experimental results with a pneumatic cylinder demonstrate that sub-millimeter accuracies in position measurement can be obtained with such a system in spite of disturbances from external ferromagnetic objects. The developed sensing principle has a large number of applications, including position estimation in pneumatic cylinders, hydraulic actuators, spool valves, and many other machinery.

Description: This letter proposes a novel method of noninvasive detection of voids in fiber reinforced plastics (FRPs). An ideal nondestructive evaluation method for the detection of subsurface defects that utilizes the capabilities of a magnetoinductive planar microstrip sensor is examined through a finite-integration-based model in this letter. A combination of magneto inductive waveguide as (MIW) and a patch radiator is used as the sensing element. The magnetoinductive waveguide increases the sensitivity of the patch to the presence of voids in the FRP.

Description: In this paper, a polarization navigation sensor is designed based on the polarization sensitivity mechanisms of insects. A new calibration model by taking full advantage of both reference angle of polarization and constant degree of polarization is presented to determine calibration parameters. Unlike existing calibration algorithms, the proposed algorithm makes the calibration problem well-posed. The results of simulations and experiments show that the proposed algorithm is more stable than the compared methods for the calibration applications of polarization navigation sensors.

Description: Multihop underwater acoustic sensor networks (UASNs) suffer from low throughput caused by low channel utilization and unreasonable bandwidth allocation. The existing media access control (MAC) protocols for UASNs mainly aim to improve channel utilization but neglect to optimize bandwidth, so that they cannot achieve high throughput in miltihop networks. We propose the idea of joint bandwidth optimization and MAC in this paper. We first present a system model to optimize bandwidth for miltihop UASNs. Both the complicated interference relations between links and the different transmission demands of nodes are modeled. Thus, it can accurately reflect the characteristics of miltihop UASNs. By analyzing a 1-D linear miltihop network, we find and formulate a maximum hop number which is determined by nodes’ traffic load and channel capacity. The other finding is that an optimal scheduling needs to allocate the bandwidth based on traffic load, and the nodes with more traffic load should be allocated more bandwidth. This finding inspire us to develop a distributed traffic-based scheduling MAC protocol. This protocol can optimize bandwidth allocation by letting the older packet to be transmitted preferentially. To improve channel utilization, multiple packets are allowed to be transmitted in each data transmission round. Simulation results have confirmed that our protocol can achieve excellent performance owing to its core idea of joint bandwidth optimization and MAC.

Description: Ultrasonic guided waves (UGW) can be used to inspect and monitor a structure from a single test location. Piezoelectric transducers are commonly dry-coupled with force to the surface of the waveguide in order to excite UGWs. These UGWs propagating within the waveguide will interact and reflect from known features, thus possible damage could be detected. In this paper, the interaction of UGWs with piezoelectric transducers is reported and investigated. A Finite Element Analysis (FEA) approach has been used to conduct a parametric study in order to quantify the effect of the waveguide diameter on the guided wave response. Laboratory experiments are carried out to measure the effect of the force on the dry-coupled piezoelectric transducers and the corresponding guided wave response, including reflections and mode conversions. A test rig is used to apply and measure the force on the piezoelectric transducers. For verification, a 3D Laser Doppler Vibrometry (3D-LDV) scan is performed on the waveguide in order to quantitatively identify the modes of interest. The conclusions reached this paper, particularly with respect to the quantification of the wave mode properties, lead to useful recommendations which may contribute to field inspection scenarios.

Description: The application of solid-state nanopore technology for biosensing is a rapidly developing area of research with high commercial potential. Different synthetic materials, including silicon nitride, alumina, and polymers, are employed to fabricate single and multiple pores and offer a good platform for selective biomolecule detection. Two solid-state pore arrays, one with integrated silicon microfluidic system, were considered and an immobilization strategy suitable for detecting a single-stranded DNA (ssDNA) sequence was investigated. For the silicon nitride pores, a modification method based on the use of 3-aminopropyltriethoxysilane for silanization and 1,4-phenylene diisothiocyanate for amine crosslinking was applied to immobilize 100-nM ssDNA (amine C6) and a 100-nM limit of detection for complementary to probe ssDNA (Cy5) was estimated. The polycarbonate pores (the second type of the pore arrays) underwent surface modification based on an oxidation reduction reaction using sodium periodate and sodium borohydride and was used to immobilize 10-nM ssDNA and an estimated 100-nM limit of detection was also achieved. Linear sweep voltammetry was used to characterize the pores and a current potential profile was obtained after both immobilization of probe ssDNA and hybridization of complementary to probe ssDNA on the modified pore array surface. A decrease in current amplitude was measured after surface modification of both pore arrays, and this was attributed to the appearance of an additional layer on the pore surface reducing the pore opening and hindering the current flow. The hybridization event was also supported by contact angle measurements, where an increase in hydrophilicity was recorded at the different surface modification steps that were applied to produce the biofunctionalized nanopore. In addition, fluorescence was observed on the surfaces after hybridization, through incorporation of a CY5 fluorescent tag attached on the 5’ end of the complemen- ary to probe DNA. These results show the potential to use both silicon nitride and polycarbonate nanopores in DNA detection applications.

Description: In this paper, we are proposing a simple energy efficient on-chip temperature to frequency converter circuit. The proposed arrangement senses the temperature in terms of the proportional to absolute temperature (PTAT) current. The temperature equivalent PTAT current is then converted into frequency using the source coupled multivibrator circuit. The proposed circuit has been designed and fabricated in a standard 180-nm CMOS technology and occupies silicon area of $approx 0.058$ mm $^{2}$ . The measurements were performed on ten prototypes. The proposed architecture is capable of working in the temperature range of −40 °C to +85 °C with the supply voltage of 0.9 V ± 10%. The smart temperature sensor achieves a maximum temperature inaccuracy <±1 °C after applying single point calibration. The average power consumption is $approx 600$ nW at +85 °C for 0.9 V supply voltage.

Description: Recording shear stresses is becoming relevant in an increasing number of applications, e.g., in rehabilitation sciences, where detecting foot-sole interaction is very important. This paper describes a portable and complete system to record multiaxial shear stresses. The sensing operation itself is based on the changing coupling of light between a vertical-cavity surface-emitting laser (VCSEL) and a segmented photodiode. Applying shear stress causes lateral displacement of both optoelectronic components leading to variation in the photocurrent. By combining signals from different photodiode segments, multiaxial shear stresses can be detected. A standalone system was designed to drive the VCSEL and to readout the signals from the different photodiode segments in order to measure shear stress as well as to evaluate the sensing system performance. Furthermore, the sensor signals can be efficiently monitored and visualized on a tablet or PC in real-time using dedicated software. The design presented in this article is optimized to measure shear forces with a magnitude up to 2 N and arbitrary direction. Yet, by changing the transducer material this range can be tuned for a specific application.

Description: Microsoft Kinect sensor has been widely used in many applications since the launch of its first version. Recently, Microsoft released a new version of Kinect sensor with improved hardware. However, the accuracy assessment of the sensor remains to be answered. In this paper, we measure the depth accuracy of the newly released Kinect v2 depth sensor, and obtain a cone model to illustrate its accuracy distribution. We then evaluate the variance of the captured depth values by depth entropy. In addition, we propose a trilateration method to improve the depth accuracy with multiple Kinects simultaneously. The experimental results are provided to ascertain the proposed model and method.

Description: Online monitoring of the transformer winding using electromagnetic waves has recently been proposed for the detection of mechanical defects of transformer winding. In this paper, a new method, which uses the ultrawideband radar measurement results and is based on locus of objects in the space, is proposed for the 3-D positioning of transformer winding radial deformation location. The proposed experimental setup for this method named hyperboloid method is modeled using Computer Simulation Technology software. In this paper, Vivaldi antennas suitable for measurements in environments with multipath, are used and the analysis is performed in the time domain. The simulation results show that the exact 3-D location of the radial deformation can be detected with a good accuracy.

Description: In-field tracking of crank angles is important for analyzing outdoor cycling biomechanics, but current encoder-based methods are expensive and time-consuming. Inertial and magnetic measurement systems (IMMSs) have the potential for minimally invasive crank angle tracking, although errors due to magnetic interference and static calibration hinder performance. This paper presents a nonlinear complimentary filter, called the constrained rotational acceleration and kinematics (CRANK) filter, which estimates crank angles without magnetometer measurements or a static calibration for the crank arm IMMS. The CRANK filter removes drift errors by exploiting constraints on the kinematics of the crank arm relative to the bicycle frame. Three 5 min cycling tests were conducted using stereophotogrammetry and two IMMSs; a slow ( $sim 80$ r/min) and medium (90 r/min) cadence test on a level surface and a fast cadence test (100 r/min) with the bicycle inclined at 20° to the ground. A novel two-segment methodology for collecting ground truth data with an optical motion capture system is presented. We also provide analysis of CRANK filter performance for simulated outdoor dynamics (lateral tilt and roll). The CRANK filter achieved absolute errors (AEs) of 0.9 ± 0.6°, 1.7 ± 1.4°, and 1.8 ± 1.2° for the slow, medium, and fast tests, outperforming a commercial Kalman filter that produced AEs of $sim 10^{circ }$ . Under simulated outdoor conditions the CRANK filter was only slightly less accurate ( ${rm AEs}approx 3 {^{circ }}$ ). The CRANK filter is shown to be accurate, drift-free, easy to implement and robust against magnetic disturbances, sensor positioning, bicycle inclination, and bicycle frame dynamics.

Description: Recent advances in smart devices have sustained them as a better alternative for the design of human–machine interaction (HMI), because they are equipped with accelerometer sensor, gyroscope sensor, and an advanced operating system. This paper presents a continuous hand gestures recognition technique that is capable of continuous recognition of hand gestures using three-axis accelerometer and gyroscope sensors in a smart device. To reduce the influence of unstableness of a hand making the gesture and compress the data, a gesture coding algorithm is developed. An automatic gesture spotting algorithm is developed to detect the start and end points of meaningful gesture segments. Finally, a gesture is recognized by comparing the gesture code with gesture database using dynamic time warping algorithm. In addition, a prototype system is developed to recognize the continuous hand gestures-based HMI. With the smartphone, the user is able to perform the predefined gestures and control smart appliances using the Samsung AllShare protocol.

Description: This paper presents a method to estimate steady wind and a maneuvering strategy for loitering under a strong, steady wind. The wind estimation uses Global Positioning System velocity only through a novel filter design without airspeed measurement. The wind estimate is then used to guide the aircraft to crab in a direction perpendicular to the wind, thereby avoiding large changes in flight variables if an orbit-type maneuver is attempted. The proposed method is demonstrated through flight tests.

Description: We propose biased estimators to find the direction of arrival of emitters present in the mainlobe of a spinning antenna-based electronic intelligence system. The proposed estimators were constructed by using Bayesian techniques and by performing a linear transformation and an affine transformation on the maximum likelihood estimator. From a Monte Carlo simulation and experimental results, we demonstrate that the proposed estimators outperform the limit set by the popular performance benchmark, the Cramer-Rao lower bound.

Description: A new method was proposed for chirp signal detection and estimation built on the frame-based fast Fourier transform (FFT). The proposed method uses the peak frequency difference between FFT frames to detect a chirp signal and estimate chirp rate. This approach differs from conventional methods and is easy to implement. It generates more accurate chirp rate estimation especially under a low signal-to-noise ratio. Simulation and experimental data are used to verify the proposed methods.

Description: The quasimaximum likelihood (QML) estimator of polynomial-phase signals (PPSs) is based on the maximization of the short-time Fourier transform and suffers from aliasing when signals are sampled below the Nyquist sampling rate. In this paper, a phase unwrapping procedure has been proposed as an additional step in the QML to estimate parameters of such signals. Statistical study has shown excellent performance of the proposed approach.

Description: Most advanced wireless communication systems use spectrally efficient complex modulation to pack more users into the crowded frequency spectrum. Complex modulation simultaneous modulates a signal's amplitude and phase (polar coordinates) or, equivalently, the I and Q components (rectangular coordinates).

Description: This paper investigated a room temperature resistive ammonia gas sensor based on a conductive polymer and N-doped graphene quantum dots (N-GQDs) dopant made on a transparent substrate with electrodes. The sensor fabricated with conductive polymer showed a good sensing response that increases considerably with the addition of N-GQDs. The sensing response of the poly(3,4-ethylenedioxythiophene)-poly(styrenesulfonate) (PEDOT-PSS) to NH 3 increased from 30.13% to 212.32% at 1500 ppm with the addition of 50 wt% N-GQDs. The response time of the N-GQDs doped sensor decreased to 6.8 min when compared with the sensor without N-GQDs and the stability of the sensor having combined N-GQDs and PEDOT-PSS was higher than that of the PEDOT-PSS sensor. Meanwhile, the structure and morphology of the sensing film are characterized by Fourier transform infrared spectroscopy and field emissions scanning electron microscopy.

Description: We analyze the change of angular gain and vibration frequency of the solid-state wave gyroscopes as a result of geometry perturbations due to thermal expansion. We analyze sensitivity of the device to the thermal expansion effects by an isoparametric finite-element analysis method, and we analyze the sensitivity to thermal changes in the material properties assuming a linear dependence on temperature. We quantify these sensitivities for common device geometries, and use our analysis as the basis for a local optimization problem that minimizes the temperature sensitivity as a function of device shape.

Description: A multi-components interferometer based on partially filled dual-core photonic crystal fiber (D-C PCF) was fabricated for measuring temperature and strain. The partially filled D-C PCF was prepared by manual gluing method, and the cladding air holes surrounding one core were selectively filled with refractive index liquid while remaining other air holes unfilled. A multi-components interference with a large spectrum envelope and fine interference fringes was observed in the transmission spectrum. Theoretical and experimental investigations revealed that the large spectrum envelope was originated from the interference between the fundamental modes of two cores of the PCF, while the fine interference fringes were generated by the interference between the fundamental mode and higher order modes in one core that surrounded by unfilled air holes. The proposed device can be used to monitor temperature and strain simultaneously through matrix demodulation, with a high temperature sensitivity of 5.43 nm/°C.

Description: We investigate the use of discrete-time analog joint source channel coding (JSCC) in a wireless sensor network where the source of information is wirelessly powered by the destination. Wireless energy transfer and information transmission are multiplexed via a time-switching protocol. As a fraction of the time slot is spent for energy transfer, the source samples are saved and compressed using either parametric or non-parametric $N$ : $K$ dimension compression analog JSCC to transmit the information in the remaining fraction of the time slot. We analyze both matched and unmatched source and channel bandwidths. Moreover, we investigate the time-sharing parameter that optimizes the analog system performance and show that the proposed analog scheme can outperform a fully digital system.

Description: In agricultural and food industry, the proper grading of fruits is very important to increase the profitability. In this paper, a scheme for automated grading of mango (Mangifera Indica L.) according to maturity level in terms of actual-days-to-rot and quality attributes, such as size, shape, and surface defect has been proposed. The proposed scheme works on intelligent machine vision-based techniques for grading of mangoes in four different categories, which are determined on the basis of market distance and market value. In this system, video image is captured by a charge couple device camera placed on the top of a conveyer belt carrying mangoes, thereafter several image processing techniques are applied to collect features, which are sensitive to the maturity and quality. For maturity prediction in terms of actual-days-to-rot, support vector regression has been employed and for the estimation of quality from the quality attributes, multiattribute decision making system has been adopted. Finally, fuzzy incremental learning algorithm has been used for grading based on maturity and quality. The performance accuracy achieved using this proposed system for grading of mango fruit is nearly 87%. Moreover, the repeatability of the proposed system is found to be 100%.

Description: Applications that are based on indoor location awareness have different requirements with regard to the accuracy of the estimated positions, the measurement cycle time, and the (end-to-end) delay between the start of a measurement and the availability of the position result. Moreover, the energy consumption of the mobile tags is a key parameter for the selection of an appropriate system. In this paper, we present the results of a series of real-time 3D-position measurements carried out with three respective systems. The two commercial systems, DecaWave DW1000 and Time Domain P410, are based on radio-frequency measurements, while an acoustic prototype system employs time-of-flight measurements based on audible signals. The systems were tested in stationary as well as in dynamic scenarios. Our results provide the accuracies and precisions of the individual systems, the position update rates, and the end-to-end delays. In additional measurements, we determined the individual tag power consumptions and calculated a figure of merit giving the energy consumption per position measurement.

Description: In this paper, a direct approach of designing robust weighted fusion steady-state Kalman predictors with uncertain noise variances is presented. Based on the steady-state Kalman filtering theory, using the minimax robust estimation principle, the local and six weighted fusion robust steady-state Kalman predictors are proposed based on the worst case systems with the conservative upper bounds of noise variances. They include the three robust weighted state fusers, two robust weighted measurement fusers, and a modified robust covariance intersection (CI) fuser. Their actual prediction error variances are guaranteed to have the corresponding minimal upper bounds for all admissible uncertainties. A Lyapunov equation approach for robustness analysis and the concept of the robust accuracy are presented and their robust accuracy relations are proved. A simulation example verifies the accuracy relations and robustness.

Description: In multitarget tracking, the problem of track labeling (assigning labels to tracks) is an ongoing research topic. The existing literature, however, lacks an appropriate measure of uncertainty related to the assigned labels that has a sound mathematical basis as well as clear practical meaning to the user. This is especially important in a situation where well separated targets move in close proximity with each other and thereafter separate again; in such a situation, it is well known that there will be confusion on target identities, also known as "mixed labeling." In this paper, we specify comprehensively the necessary assumptions for a Bayesian formulation of the multitarget tracking and labeling (MTTL) problem to be meaningful.We provide a mathematical characterization of the labeling uncertainties with clear physical interpretation.We also propose a novel labeling procedure that can be used in combination with any existing (unlabeled)MTT algorithm to obtain a Bayesian solution to the MTTL problem. One advantage of the resulting solution is that it readily provides the labeling uncertainty measures. Using the mixed labeling phenomenon in the presence of two targets as our test bed, we show with simulation results that an unlabeled multitarget sequential Monte Carlo (M-SMC) algorithm that employs sequential importance resampling (SIR) augmented with our labeling procedure performs much better than its "naive" extension, the labeled SIR M-SMC filter.

Description: Track-before-detect methods jointly detect and track one or several targets from raw sensor measurements. They often require the computation of the measurement likelihood conditional on the hidden state, which depends on the complex amplitudes of the targets. Since these amplitudes are unknown and fluctuate over time, this likelihood must be marginalized over the complex amplitude (i.e., phase and modulus). It has been demonstrated that this marginalization can be done analytically over the phase in the monotarget case. In this article, we first propose to extend the marginalization to the modulus in a monotarget setting, and we show that closed forms can be obtained for fluctuations of type Swerling 1 and 3. Second, we demonstrate that, in a multitarget setting, a closed form can be obtained for the Swerling 1 case. For Swerling 0 and 3 models, we propose some approximation to alleviate the computation. Since many articles consider the case of squared modulus measurements, we also consider this specific case in monoand multitarget settings with Swerling 0, 1, and 3 fluctuations. Finally, we compare the performance in estimation and detection for the different cases studied, and we show the gain, both in detection and estimation, of the complex measurement method over the squared modulus method, for any fluctuation model.

Description: When a bistatic inverse synthetic aperture radar (ISAR) system fails to collect complete radar cross section (RCS) datasets, bistatic ISAR (Bi-ISAR) images are usually corrupted using the conventional Fourier transform (FT)-based imaging algorithm. To overcome this problem, this paper proposes a new Bi-ISAR image reconstruction method that includes three steps: suboptimal estimation of parameters regarding the bistatic angle in the Bi-ISAR signal model via an orthogonal matching pursuit-type group-searching scheme, Bi-ISAR signal reconstruction using the estimated parameters, and Bi-ISAR image generation using the FT-based imaging algorithm applied to the reconstructed Bi-ISAR signal. To validate the reconstruction capability of the proposed method, bistatic-scattered field data using the physical optics technique as well as the point-scatterer model are used for Bi-ISAR image reconstruction. The results show that the proposed sparse-recovery-interpolation approach based on the Bi-ISAR signal model reconstruction combined with the classical FT-based algorithm can yield high reconstruction accuracy for incomplete bistatic RCS data compared to conventional numerical interpolation methods and existing direct sparse reconstruction techniques.

Description: Bistatic inverse synthetic aperture radar (ISAR) is an efficient geometric configuration of ISAR to image targets traveling along radar transmitter's line of sight, but it has the problem of defocusing and distortion because of the time-varying bistatic angle. In this paper, we derive the defocusing term and the distortion term by expanding the bistatic angle using first-order Taylor expansion. In addition, necessary constraints to neglect the defocusing term are provided via point spread function analysis, and a novel method to eliminate distortion based on linked scatterers is proposed. Simulation results validate our theoretical analysis and show the effectiveness of our method.

Description: Micro-Doppler (MD)-based target classification capabilities of automotive radars can provide high reliability and short latency to future active safety automotive features. A large number of pedestrians surrounding a vehicle in practical urban scenarios mandate prioritization of their treatment level. Distinguishing between relevant pedestrians that are crossing the street or are within the vehicle path and those that are on the sidewalks and are moving along the vehicle route can significantly minimize the number of vehicle-to-pedestrian accidents. This work proposes a novel technique for estimating a pedestrian direction of motion that treats pedestrians as complex distributed targets and utilizes their MD radar signatures. The MD signatures are shown to be indicative of pedestrian direction of motion, and a supervised regression is used to estimate the mapping between the directions of motion and the corresponding MD signatures. In order to achieve higher regression performance, a state-of-the-art sparse dictionary learning-based feature extraction algorithm was adopted from the field of computer vision by drawing a parallel between the Doppler effect and the video temporal gradient. The performance of the proposed approach is evaluated in practical automotive scenario simulations, where a walking pedestrian is observed by a multiple-input/multiple-output automotive radar with a two-dimensional rectangular array. The simulated data was generated using the statistical Boulic-Thalman human locomotion model. Accurate direction of motion estimation was achieved by using support vector regression and multilayer perceptron-based regression algorithms. The results show that the direction estimation error is less than 10° in 95% of the tested cases for pedestrian at a range of 100 m from the radar.

Description: This paper proposes a novel phase synchronization technique that enables beamforming with multiple resource-limited spacecraft in space and capitalizes on their spatial geometry. The proposed technique employs an external beacon to obviate the need for explicit time synchronization and reduces the accuracy requirements on localization. Results show that subcentimeter (subnanosecond)-level phase synchronization can be achieved with localization accuracy in the order of meters.

Description: The use of chirp signals in modern radar and ranging systems have numerous benefits. They are extensively used to improve signal-to-noise ratio and range resolution. The performance capabilities of these signals are directly related to their time-bandwidth product, i.e., the duration and bandwidth of the pulse. Ultra-wideband chirp signals are further desirable because they span a large bandwidth, making them resistant to narrowband environmental interference. The accurate detection and measurement of high chirp signals is difficult due to the necessity of a high-sampling analog-digital converter, a target measurement platform with high computational power, and a time-of-arrival (TOA) estimator with high temporal resolution. The difficulty of the problem is further compounded with the requirement that no a priori knowledge of the signal, noise, or operating environment is known. This paper presents a practical approach and implementation of a high linear chirp rate receiver and TOA estimator pair capable of detecting and measuring stationary radio frequency pulses as well as linear chirp rates up to 1.18 GHz in 400 ns. The high-resolution TOA algorithm and linear chirp receiver have been prototyped, synthesized, and placed and routed for a Virtex 6 SX475 FPGA.

Description: In this paper, an impact angle control guidance law, which considers simultaneously the impact angle and seeker's look angle constraints, is proposed for a constant speed missile against a stationary target. An optimal control theory with state variable inequality constraint is used to design the guidance law, for which a control energy performance index with the weighting function of the range-to-go is minimized. Various forms of guidance and trajectory shaping are possible by selecting a proper gain of the weighting function. To handle the seeker's look angle limits when the missile trajectory is highly curved by controlling the impact angle, the proposed guidance law generates three types of acceleration commands as the guidance phases: the first acceleration command for an initial guidance phase makes an initial seeker's look angle reach the maximum look angle; the second one for a midguidance phase maintains the maximum look angle; the final one for a terminal guidance phase intercepts the target with the desired impact angle. The performance of the proposed guidance law was investigated with nonlinear simulations for various engagement conditions.

Description: This paper presents a means of near asteroid hovering of a rigid spacecraft in the asteroid body-fixed frame with parameter variations and external disturbances. An adaptive finite-time control scheme is proposed, where the upper bounds of the parametric uncertainties and disturbances are not required for controller design. The detailed design principles and a rigorous stability analysis are provided. Finally, a body-fixed hovering maneuver is employed in numerical simulation to verify the effectiveness of the proposed strategy.

Description: Inertial measuring systems (IMSs) enable determination of 3-D position and trajectory on a base of the actual measured acceleration and angular velocity. Measurements with the inertial sensors are influenced by errors from used sensors. Because of the principle of calculation of a position based on the recursive algorithm, there is an accumulation of systematic error, which causes a rapid decreasing of the position accuracy hand in hand with a measuring time. This paper deals with the suggestion of the model for data processing, which enables to eliminate systematic errors of sensors; thereby, the position accuracy is increased. For this purpose, an optical rotational-speed sensor was introduced and the additional measurement was realized with it in combination with the two IMSs located on the common baseline. Measurements from optical rotational-speed sensor were used in a combination with the accelerometers for their higher long-term accuracy. This combination enables to eliminate errors from the accelerometers even after the first integration process. Using the pair of IMSs located on the common baseline, the requirements (constraints) of the geometric relation of two coordinate systems of these IMSs were implemented into the model for data processing. These constraints were applied for correction of the position and orientation. As a part of the suggested model, an algorithm for identification of the dynamic phases was realized. This algorithm identified an actual dynamic phase of the system on a basis of the actual measured acceleration and angular velocity. This information was used for an adjustment of the processing model.

Description: In this paper, we propose a novel method to automatically configure a pan-tilt-zoom camera network in order to maximize coverage and visual quality in complex indoor environments. Based on a suitable modeling of cameras and environment, the optimization procedure determines the most appropriate camera position and settings to fulfill a given coverage objective. To achieve this goal, we use a particle swarm optimizer with an appropriate fitness function that takes into account a number of concurrent metrics and constraints. Furthermore, the solution is found working into a simulated environment obtained with the ray-tracing software. The proposed solution has been tested in various synthetic and real environments, taking into account the presence of obstacles and other constraints. We also simulated dynamic situations, such as cameras failures, to test the capability of fast camera network reconfiguration. For the performance evaluation, and in addition to the simulation in virtual scenes, we have also conducted a validation phase in real-world scenarios, where we assessed how the introduction on the optimal configuration improves the solution of some typical computer vision tasks.

Description: In global navigation satellite system (GNSS) receivers, the acquisition process is the first stage of the signal processing module. It consists of assessing the presence of GNSS signals and providing a rough estimation of the incoming signal parameters: the Doppler frequency and the code delay. However, the presence of bit sign transitions affects receiver performance in signal acquisition detection. This article focuses on the bit transition and its impact on the acquisition performance by providing a general mathematical study and an illustration for two GNSS signals: the global positioning system legacy civil signal (GPS L1 C/A) and Galileo E1 open service (OS). This study is applicable to a terrestrial user in a constraint environment. Furthermore, the presented results are mathematical models of the probability of detection in the presence of bit sign transitions (only one potential bit sign transition per integration interval), and potential uncertainties on the Doppler frequency and code delay. These do not result from empirical acquisition of real signals.

Description: This paper investigates the problem of ground vehicle tracking with ground-moving target indicator (GMTI) radar. In practice, the movement of ground vehicles may involve several different maneuvering types (acceleration, deceleration, standstill, etc.). Consequently, the GMTI radar may lose measurements when the radial velocity of the ground vehicle is below a threshold, i.e., falling into the Doppler blind region. In this paper, to incorporate the information gathered from normal measurements and knowledge on the Doppler blindness constraint, we develop an enhanced particle filtering method for which the importance distributions are inspired by a recent noise-related Doppler blind (NRDB) filtering algorithm for GMTI tracking. Specifically, when constructing the importance distributions, the proposed particle filter takes the advantages of the efficient NRDB algorithm by applying the extended Kalman filter and its generalization for interval-censored measurements. In addition, the linearization and Gaussian approximations in the NRDB algorithm are corrected by the weighting process of the developed filtering method to achieve a more accurate GMTI tracking performance. The simulation results show that the proposed method substantially outperforms the existing methods for the GMTI tracking problem.

Description: The high-frequency vibration of radar sensors platform, whose influence is generally negligible in traditional synthetic aperture radar (SAR) imaging, has a significant influence on the high-frequency band, such as the terahertz (THz) band SAR imaging. In this paper, the high-frequency vibration of sensors platform model of THz SAR imaging is established and the effect of it is analyzed. For the vibration of platform can be viewed as a simple harmonic motion, the received signal of THz SAR in each range bin can be considered as sinusoid frequency modulation (SFM) signal. This will cause the images to be defocused in the azimuth processing. A novel algorithm for the parameters estimation of SFM signal based on the discrete sinusoid frequency modulation transform is proposed in this paper, and the simulated annealing algorithm is used to reduce the computational load simultaneously. Then, the phase errors induced by the sensors platform vibration can be compensated by the estimated parameters. The numerical results demonstrate the effectiveness of the novel algorithm proposed in this paper.

Description: We consider the problem of quantifying energy savings when a lighting control system is upgraded. A conventional approach to determine energy savings resulting from the control upgrade is using the energy consumption values over the pre-upgrade and post-upgrade time periods. However, energy consumption depends on operational factors, such as occupancy and daylight conditions, which may be different over the two periods. This may result in incorrect estimation of the energy savings. To address this problem, we consider energy performance prediction using sensor data from the lighting system. Specifically, occupancy and light sensor data in the lighting control system over the pre-upgrade period are used to construct a prediction model of the energy consumption using support vector regression. Sensor data from the post-upgrade period is then used in this model to estimate the energy consumption of the pre-upgrade control system under operating conditions in the post-upgrade period. Using data from an indoor office lighting model, we show that the proposed method provides better estimates of energy savings than the conventional approach.

Description: Many studies have reported that glaucoma patients experience mobility issues, such as walking slowly and bumping into obstacles frequently. However, little is known to date about how a person’s gait is impacted due to glaucoma. This paper presents design and development of a gait analysis approach using a shoe-integrated sensing system and accompanying machine learning techniques to quantitatively examine gait patterns in glaucoma patients. The customized sensor platform is utilized in a clinical trial conducted with nine glaucoma patients and ten age-matched healthy participants. The signal processing and machine learning algorithms automatically detect effective gait cycles and extract both steady-state and spatio-temporal gait features from the signal segments. We perform machine learning algorithms to distinguish glaucoma patients from healthy controls, and identify several prominent features with high discriminability between the two groups. The results demonstrate that classification algorithms can be used to identify the gait patterns of glaucoma patients with an accuracy higher than 94% in a 10-m-walk test. It is also demonstrated that gait features such as evenness of the sway speed along medio-lateral direction between the two feet are significantly different (p-value < 0.001) between older adults with and without glaucoma. These results suggest that emerging solutions, such as wearable sensing technologies, can be used for continuous and real-time assessment of gait and mobility problems in individuals with low vision, and may open new avenues for using changes in gait patterns for preventing life threatening situations such as falls.

Description: Cattle health monitoring on the feedlot is a crucial but nontrivial task. The conventional way of monitoring relies heavily on the cowboy’s visual surveillance, which makes the animal monitoring quality highly subjective and correlated with the obviousness of the observed traits. In order to achieve early detection of each individual animal’s illness, in this paper, a wireless sensor network system is developed to monitor the animal’s feeding and drinking behaviors. A directional antenna is used to allow one router to monitor multiple animals simultaneously, and an energy efficient mesh routing strategy is proposed to aggregate the monitoring data. The performance of the proposed system has been evaluated through numerical analysis and simulations. The contributions of this paper lie in the novelty and feasibility of using directional antenna and wireless sensor network technologies for feedlot animal health monitoring.

Description: Sets that are defined either from closed contours or from a set of points are generic descriptors for several kinds of objects in binary images. In this paper, we derive a novel model in the space of sets and design an observer for the proposed model to estimate the depth and orientation of planar objects from a camera. This problem is well known as "structure from motion." When the objects are only partially projected on the image plane of the camera, our model makes object depth and orientation estimation possible without feature tracking and matching between distinct image frames (i.e., the so-called correspondence problem), which is an advantage over the image moments-based model. However, the proposed model fails in some situations (the failures can be seen as brief instabilities), and it is not always continuous. To compensate for these drawbacks, we designed a fast observer based on L 1 control theory with a binary signal for the proposed model. Stability analysis with respect to a certain asymptotic instability ratio is also presented in this paper. The effectiveness of the proposed model and observer is demonstrated through simulations and experimental results.

Description: Presents the front cover/table of contents for this issue of this publication.

Description: A novel differential vector phase locked loop (DVPLL) is derived that takes global navigation satellite system (GNSS) code-phase and carrier-phase measurements from a base station and uses them to maintain a position with centimeter-level accuracy directly in the vector tracking loop of a rover receiver. The navigation filter uses five state variables, three position and two clock states, to create the replica code and carrier measurements for a static test. There are no individual channel states or feedback mechanisms. Closing the individual loops solely through the navigation filter makes this a purely vector method. For short baselines, where differential atmospheric errors are small, the DVPLL can be used on single-frequency data. An L1-only live-sky static test was performed using the method, resulting in a three-dimensional accuracy of 1.3 mm for a zero-baseline and 5.3 mm for an 18.5 m baseline.

Description: An adaptive actuator failure and disturbance compensation scheme is developed for attitude tracking control of spacecraft. The proposed scheme consists of a composite parameter adaptation design that incorporates an adaptive backstepping feedback control law and an adaptive feedforward actuator failure compensator; it can guarantee the overall closed-loop system stability and asymptotic tracking. Illustrative simulation results of an application to a spacecraft model show that the designed actuator failure compensation controller ensures system stability and tracking performance.

Description: Track-before-detect (TBD) is a popular incoherent energy integration technique aimed at improving detectability of weak targets. A number of studies are available in the literature demonstrating its efficacy against disturbance (whether noise or clutter), but most of them refer to synthetic data, i.e., relying on computer simulations. In this paper, we tackle the problem of assessing the TBD performance with real data and in a particularly severe clutter environment, i.e., sea-clutter. Precisely, using a set of real data from a ground-based sea-search radar, we implement TBD directly on the plot-lists coming from the radar plot extractor (this be can done with acceptable complexity by using an ad hoc dynamic programming algorithm), and demonstrate its effectiveness in reducing sea-clutter. As a further contribution, we also develop an improved decision logic for plot confirmation.

Description: The concept of more electric aircraft leads to increases in the amount of electrical loads, as well as the power consumed in the aircraft of the future. To utilize the power feeders, more symmetric, load balancing methods can be applied to swap loads between different phases of an alternating current (AC) feeder, or even between different power feeders. If the load balancing system reacts to measurement data during the flight in real time, the cable power losses and return network power losses, too, are reduced. In addition, the rate of power management interventions decreases. The load balancing problem in three-phase systems is a mixed-integer nonlinear nondifferentiable optimization problem, which is typically solved by elaborate and time-consuming nonreal-time optimization algorithms. The AC loads in aircraft have different power factors, which result in currents described by complex numbers. To determine a load swapping scheme in real time starting from a given load allocation with sparse swapping, new heuristics are presented. One heuristic is specially designed to solve the phase swapping problem by shifting single-phase loads between phases of a feeder. Another heuristic, based on the first one, is enhanced to more than one three-phase feeder and considers the swapping of single-phase and three-phase loads. The heuristics are tested by simulations of a comprehensive case study based on real measurement data from a modern passenger aircraft. To prove the efficiency of the new concepts, a test bench has been built, and several experiments successfully conducted.

Description: The probability hypothesis density (PHD) filter is an efficient algorithm for multitarget tracking in the presence of nonlinearities and/or non-Gaussian noise. The sequential Monte Carlo (SMC) and Gaussian mixture (GM) techniques are commonly used to implement the PHD filter. Recently, a new implementation of the PHD filter using B-splines with the capability to model any arbitrary density functions using only a few knots was proposed. The spline PHD (SPHD) filter was found to be more robust than the SMC-PHD filter because it does not suffer from degeneracy, and it was better than the GM-PHD implementation in terms of estimation accuracy, albeit with a higher computational complexity. In this paper, we propose a multiple model extension to the SPHD filter to track multiple maneuvering targets. Simulation results are presented to demonstrate the effectiveness of the new filter.

Description: This paper proposes an optimal control framework for the climb and descent economy modes of a flight management system (FMS) yielding a solution that can be implemented in real-time flights below the drag divergence Mach number. The problem is formulated as the optimization of a functional that trades off the fuel- and time-related costs of a flight as a function of a (crew-supplied) parameter called the cost index. The work builds on previous research of the authors for the cruise phase and extends it to the climb and descent phases of flight. More specifically, for both climb and descent, it is found that suboptimal solutions can be obtained as the positive real roots of a fifth-degree polynomial lying inside the flight envelope, which can be found using fast-converging algorithms such as Newton's method. The main contributions of this work are threefold. First, the proposed method gives physical insight because there is an analytical expression for each coefficient of the polynomial. Second, this approach eliminates the need to have a performance database in the system, thus making its implementation faster in real-time. Third, the solution exhibits the same behavior of airborne FMS units as a function of the cost index, which is justified in this paper based on Bellman's principle of optimality. This justification is an important theoretical contribution of the paper. A validation of the approximate solution is obtained using the shooting method to compute the optimal trajectories and compare them against the proposed suboptimal solution. Simulation results show that, for an Airbus A320 model and for a Gulfstream-IV aircraft model, the relative error of the suboptimal trajectories when compared to the optimal trajectories is small for climb and descent trajectories, respectively.

Description: An X-band, 15-W-class gallium nitride (GaN) solid-state power amplifier (SSPA) for the 50-kg-class ultrasmall deep-space probe PROCYON has been demonstrated in deep space for the first time. PROCYON was launched on December 3, 2014, as a subpayload of the Hayabusa 2 spacecraft. The GaN SSPA consists of three-stage, single-end amplifiers. The final-stage GaN high-power amplifier, which dominates the characteristics of the SSPA, achieves a maximum drain efficiency of 55.8% at 8.4 GHz. The fabricated SSPA using this GaN high-power amplifier has dimensions of 150 x 120 x 62 mm and weighs 1.5 kg, and its space applicability was confirmed through space environmental tests. For more than 2450 h of continuous operation in deep space, the GaN SSPA has achieved an average output power of 41.7 dBm (14.8 W), with standard deviation of 0.12 dB, maximum overall efficiency of 35.7%, and average efficiency of 33.8%. To the authors' knowledge, this is the highest efficiency of all proven X-band onboard SSPAs.

Description: In this paper, an adaptive cubature Kalman filter (ACKF) is proposed to improve the performance of the conventional cubature Kalman filter. The ACKF uses a new cubature rule that combines a third-degree spherical rule with an adaptive higher degree radial rule along the directions of larger uncertainty. More accurate and robust results can be obtained with slightly more cubature points than the conventional third-degree cubature Kalman filter (CKF). Compared with other high-degree Gaussian filters, ACKF uses much fewer points but maintains very close performance. A target tracking problem is used to demonstrate the effectiveness of the proposed filter.