Extended Kalman Filtering for Vision Based Terrain Relative Navigation
2019, American Institute of Aeronautics and Astronautics Inc, AIAA. All rights reserved. The paper presents an approach for navigating a space vehicle using the optimal sensor fusion of feature based observations made by vision cameras with an inertial measurement unit (IMU). The approach incorporates the use of Classical Rodrigues Parameters (CRPs) to render the relative motion model over a few time steps of interest tractable for simultaneous location and mapping. Using photogrammetric resection over a batch of N frames, the inertial position of the features tracked in the given frames are established, along with the relative navigation solution of the flight vehicle. This approach is tested experimentally onboard a small testbed, the Navigation, Estimation, Sensing, and Tracking (NEST) payload over synthetic terrain in a laboratory environment.