J
Jason N. Gross
Researcher at West Virginia University
Publications - 88
Citations - 1367
Jason N. Gross is an academic researcher from West Virginia University. The author has contributed to research in topics: GNSS applications & Global Positioning System. The author has an hindex of 18, co-authored 76 publications receiving 979 citations. Previous affiliations of Jason N. Gross include California Institute of Technology & Goddard Space Flight Center.
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Flight-Test Evaluation of Sensor Fusion Algorithms for Attitude Estimation
TL;DR: In this paper, several Global Positioning System/inertial navigation system (GPS/INS) algorithms are presented using both extended Kalman filter (EKF) and unscented Kalman Filter (UKF), and evaluated with respect to performance and complexity.
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GNSS Signal Authentication Via Power and Distortion Monitoring
TL;DR: A simple low-cost technique that enables civil global positioning system receivers and other civil global navigation satellite system receivers to reliably detect carry-off spoofing and jamming and can with high probability distinguish low-power spoofing from ordinary multipath is proposed.
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Robust UAV Relative Navigation With DGPS, INS, and Peer-to-Peer Radio Ranging
TL;DR: A novel sensor fusion algorithm is presented that incorporates locally processed tightly coupled GPS/INS-based absolute navigation solutions from each UAV in a relative navigation filter that estimates the baseline separation using integer-fixed relative CP-DGPS and a set of peer-to-peer ranging radios.
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Evaluation of Matrix Square Root Operations for UKF within a UAV GPS/INS Sensor Fusion Application
TL;DR: In this paper, the authors presented the first comprehensive analysis of the matrix square root calculations in the context of UKF and concluded that the Cholesky method is the best overall matrix square-root calculation for UKF applications in terms of performance and execution time.
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Onboard Wind Velocity Estimation Comparison for Unmanned Aircraft Systems
TL;DR: This paper presents a novel wind estimation approach, which is compared with existing ideas utilizing different combinations of common aircraft sensors to estimate the wind velocity in real time at the location of an aircraft.