Observability Driven Path Planing for Relative Navigation of Unmanned Aerial Systems

He Bai, Clark N. Taylor

Peer Reviewed

Abstract: We consider the problem of relative navigation of two unmanned aerial systems (UAS) in GPS-denied environments. We design active path planning algorithms to maximize state observability defined in discrete time. We consider two definitions of the nonlinear observability matrix and establish their connections with Fisher information matrix and filtering Cramer-Rao lower bound, respectively. We also define a sensitivity function that correlates noise on control inputs to errors on the state estimate. We demonstrate using Monte Carlo simulations that by optimizing metrics from the state observability and sensitivity, we achieve significantly improved estimation performance over a nominal trajectory for relative navigation.
Published in: 2018 IEEE/ION Position, Location and Navigation Symposium (PLANS)
April 23 - 26, 2018
Hyatt Regency Hotel
Monterey, CA
Pages: 793 - 800
Cite this article: Bai, He, Taylor, Clark N., "Observability Driven Path Planing for Relative Navigation of Unmanned Aerial Systems," 2018 IEEE/ION Position, Location and Navigation Symposium (PLANS), Monterey, CA, April 2018, pp. 793-800.
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