Previous Abstract Return to Session C4 Next Abstract

Session C4: Navigation Using Environmental Features

Mixed-Integer Moving Horizon Estimation for Terrain-Aided Navigation Using Hybrid Zonotopes
Andrew F. Thompson, Joshua A. Robbins, The Pennsylvania State University; Matthew E. Boler, Sandia National Laboratories; and Herschel C. Pangborn, The Pennsylvania State University
Location: Grand Ballroom IJ
Date/Time: Wednesday, Apr. 30, 2:35 p.m.

Terrain-aided navigation uses topological features to localize a vehicle when other sensors, such as GPS, are unavailable. An aircraft can use a pair of altimeters to make local elevation measurements and compare these readings to a terrain map. Conventional methods of achieving this include Kalman filters and particle filters. The former can be prone to errors due to linearization and multi-modal distributions, and the latter can suffer from sampling limitations. This paper proposes a moving horizon estimation method that leverages the hybrid zonotope set representation and a structure-exploiting mixed-integer solver to perform computationally-efficient and accurate state estimation. Numerical results demonstrate the efficacy of the proposed methods using terrain data from central Pennsylvania and a notional trajectory.
Index Terms—moving horizon estimation, terrain-aided navigation, hybrid zonotope

Previous Abstract Return to Session C4 Next Abstract