ALBERT

Description: Apollo missions utilized Earth-based assets for navigation, since the landings took place at lunar locations in constant view from the Earth. The new exploration campaign to the lunar South Pole region will have limited Earth visibility, but the extent to which a navigation system comprised solely of Earth-based tracking stations will provide adequate navigation solutions in this region is unknown. This article presents a dilution-of-precision-(DoP-) based stationary surface navigation analysis of the performance of multiple lunar satellite constellations, Earth-based deep space network assets, and combinations thereof. Results show that kinematic and integrated solutions cannot be provided by the Earth-based deep space network stations. Also, the surface stationary navigation system needs to be operated as a two-way navigation system, or as a one-way navigation system with local terrain information, while integrating the position solution over a short duration of time with navigation signals being provided by a lunar satellite constellation.

Description: One of the capabilities that the Space Communications and Navigation (SCaN) Strategic Center for Networking, Integration, and Communications (SCENIC) user interface (UI) web application intends to provide its users is the addition of network protocol and link encryption augmentations of communication system analyses. Before any of these analyses capabilities can be modeled, the simulations of bit error rate (BER) and frame error rate (FER) against signal-to-noise ratio (SNR) have been conducted, requiring parameters from several known coding types (low-density parity-check (LDPC), convolutional, etc.), signal modulations (binary phase shift keying (BPSK), quadrature phase shift keying (QPSK), etc.), coding rates (1/2, 1/3, etc.), and frame sizes (1,280, 3,580, etc.). However, in order to extract useful information from the results of these simulations, a curve fitting technique has been applied to each resulting dataset to extend and extrapolate the curve fit of BER and FER down to 1030 using MATLAB Curve Fitting Toolbox (The MathWorks, Inc.). This is a necessary step because simulations of BER and FER were only performed to around 109 due to the extensive simulation time that would be required to obtain significant simulation results at the error levels desired. Furthermore, the fitted curve results were applied to a finer resolution for the SNR at 0.01-dB interval instead of the 0.05-dB interval limitation used in the simulation. All the possible combinations of the coding types, signal modulations, coding rates, frame sizes, and the extension of BER and FER curves would enable users to capture a wide range of link performances that directly relates to the addition of higher level networking data encapsulated in a frame. The curve fitting results also led to the modeling of the optical link error rate performance by solving for coding gain, FER_BER SNR delta, coded optical BER-SNR, and coded optical FERSNR.

Description: As the S-band spectrum becomes crowded, future space missions will need to consider moving command and telemetry services to Ka-band. NASAs Space Communications and Navigation (SCaN) Testbed provides a software-defined radio (SDR) platform that is capable of supporting investigation of this service transition. The testbed contains two S-band SDRs and one Ka-band SDR. Over the past year, SCaN Testbed has demonstrated Ka-band communications capabilities with NASAs Tracking and Data Relay Satellite System (TDRSS) using both open- and closed-loop antenna tracking profiles. A number of technical areas need to be addressed for successful transition to Ka-band. The smaller antenna beamwidth at Ka-band increases the criticality of antenna pointing, necessitating closed loop tracking algorithms and new techniques for received power estimation. Additionally, the antenna pointing routines require enhanced knowledge of spacecraft position and attitude for initial acquisition, versus an S-band antenna. Ka-band provides a number of technical advantages for bulk data transfer. Unlike at S-band, a larger bandwidth may be available for space missions, allowing increased data rates. The potential for high rate data transfer can also be extended for direct-to-ground links through use of variable or adaptive coding and modulation. Specific examples of Ka-band research from SCaN Testbeds first year of operation will be cited, such as communications link performance with TDRSS, and the effects of truss flexure on antenna pointing.

Description: In 2015, the Space Communications and Navigation (SCaN) Testbed project completed an S-Band ground station located at the NASA Glenn Research Center in Cleveland, Ohio. This S-Band ground station was developed to create a fully characterized and controllable dynamic link environment when testing novel communication techniques for Software Defined Radios and Cognitive Communication Systems. In order to provide a useful environment for potential experimenters, it was necessary to characterize various RF devices at both the component level in the laboratory and at the system level after integration. This paper will discuss some of the laboratory testing of the ground station components, with a particular focus emphasis on the near-field measurements of the antenna. It will then describe the methodology for characterizing the installed ground station at the system level via a Tracking and Data Relay Satellite (TDRS), with specific focus given to the characterization of the ground station antenna pattern, where the max TDRS transmit power limited the validity of the non-noise floor received power data to the antenna main lobe region. Finally, the paper compares the results of each test as well as provides lessons learned from this type of testing methodology.

Description: The Space Communications and Navigation (SCaN) Testbed project completed installation and checkout testing of a new S-Band ground station at the NASA Glenn Research Center in Cleveland, Ohio in 2015. As with all ground stations, a key alignment process must be conducted to obtain offset angles in azimuth (AZ) and elevation (EL). In telescopes with AZ-EL gimbals, this is normally done with a two-star alignment process, where telescope-based pointing vectors are derived from catalogued locations with the AZ-EL bias angles derived from the pointing vector difference. For an antenna, the process is complicated without an optical asset. For the present study, the solution was to utilize the gimbal control algorithms closed-loop tracking capability to acquire the peak received power signal automatically from two distinct NASA Tracking and Data Relay Satellite (TDRS) spacecraft, without a human making the pointing adjustments. Briefly, the TDRS satellite acts as a simulated optical source and the alignment process proceeds exactly the same way as a one-star alignment. The data reduction process, which will be discussed in the paper, results in two bias angles which are retained for future pointing determination. Finally, the paper compares the test results and provides lessons learned from the activity.

Description: The Space Communications and Navigation (SCAN) Testbed was a Software Defined Radio (SDR)-based payload launched to the International Space Station (ISS) in July of 2012. The purpose of the SCAN Testbed payload was to investigate the applicability of SDRs to NASA space missions in an operational space environment, which means that a proper model for system performance in said operational space environment is a necessary condition. The SCAN Testbed has line-of-sight connections to various ground stations with its S-Band Earth-facing Near-Earth Network Low Gain Antenna (NEN-LGA). Any previous efforts to characterize the NEN-LGA proved difficult, therefore, the NASA Glenn Research Center built its own S-Band ground station, which became operational in 2015, and has been successfully used to characterize the NEN-LGAs in-situ pattern measurements. This methodology allows for a more realistic characterization of the antenna performance, where the pattern oscillation induced by the complex ISS ground plane, as well as shadowing effects due to ISS structural blockage are included into the final performance model. This paper describes the challenges of characterizing an antenna pattern in this environment. It will also discuss the data processing, present the final antenna pattern measurements and derived model, as well as discuss various lessons learned.

Description: In 2015, the Space Communications and Navigation (SCaN) Testbed project completed an S-Band ground station located at the NASA Glenn Research Center in Cleveland, Ohio. This S-Band ground station was developed to create a fully characterized and controllable dynamic link environment when testing novel communication techniques for Software Defined Radios and Cognitive Communication Systems. In order to provide a useful environment for potential experimenters, it was necessary to characterize various RF devices at both the component level in the laboratory and at the system level after integration. This paper will discuss some of the laboratory testing of the ground station components, with a particular focus/emphasis on the near-field measurements of the antenna. It will then describe the methodology for characterizing the installed ground station at the system level via a Tracking and Data Relay Satellite (TDRS), with specific focus given to the characterization of the ground station antenna pattern, where the max TDRS transmit power limited the validity of the non-noise floor received power data to the antenna main lobe region. Finally, the paper compares the results of each test as well as provides lessons learned from this type of testing methodology.

Description: This is an overview of the guiding principles of STAT derivation from back in early 2012. This includes a functional view of STAT operations, a STAT demonstration, as well as how the STAT functional view is an excellent model, in my perspective, how the necessary functional view for the SCENIC Analysis Tool.

Description: NASA is participating in the International Committee on Global Navigation Satellite Systems (GNSS) (ICG)'s efforts towards demonstrating the benefits to the space user in the Space Service Volume (SSV) when a multi-GNSS solution space approach is utilized. The ICG Working Group: Enhancement of GNSS Performance, New Services and Capabilities has started a three phase analysis initiative as an outcome of recommendations at the ICG-10 meeting, in preparation for the ICG-11 meeting. The first phase of that increasing complexity and fidelity analysis initiative is based on a pure geometrically-derived access technique. The first phase of analysis has been completed, and the results are documented in this paper.

Description: NASA's SCENIC project aims to simplify and reduce the cost of space mission planning by replicating the analysis capabilities of commercially licensed software which are integrated with relevant analysis parameters specific to SCaN assets and SCaN supported user missions. SCENIC differs from current tools that perform similar analyses in that it 1) does not require any licensing fees, 2) will provide an all-in-one package for various analysis capabilities that normally requires add-ons or multiple tools to complete. As part of SCENIC's capabilities, the ITACA network loading analysis tool will be responsible for assessing the loading on a given network architecture and generating a network service schedule. ITACA will allow users to evaluate the quality of service of a given network architecture and determine whether or not the architecture will satisfy the mission's requirements. ITACA is currently under development, and the following improvements were made during the fall of 2017: optimization of runtime, augmentation of network asset pre-service configuration time, augmentation of Brent's method of root finding, augmentation of network asset FOV restrictions, augmentation of mission lifetimes, and the integration of a SCaN link budget calculation tool. The improvements resulted in (a) 25% reduction in runtime, (b) more accurate contact window predictions when compared to STK(Registered Trademark) contact window predictions, and (c) increased fidelity through the use of specific SCaN asset parameters.