Uav Navigation Based On Parallel Extended Kalman Filter


This paper presents an approach to deal with the accuracy of an Extended Kalman Filter (EKF) by using a more accurate continuous model, but increasing EKF's speed with parallelization. Previous work, which was based on sacrificing a continuous state model in favor of discrete equations with Fuzzy Adaptive Kalman Filter led to some interesting results did not offer sufficient accuracy improvement. Two case studies are presented: the fuzzy filter applied to fuse position signals from the Global Positioning System (GPS) and Inertial Navigation System (INS) for the autonomous mobile vehicles, and the parallel filter validated for reference trajectories of the ballistic missile with the addition of equations converting the planar equations of motion to three dimensional equations. © by the American Institute of Aeronautics and Astronautics, Inc. All rights reserved.

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AIAA Guidance, Navigation, and Control Conference and Exhibit

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Article; Proceedings Paper

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85088342511 (Scopus)

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