A Box Regularized Particle Filter for terrain navigation with highly non-linear measurements*. Issue 17 (2016)

• Record Type: Journal Article
• Authors: Merlinge, Nicolas; Dahia, Karim; Piet-Lahanier, Hélène
• Is Part Of: IFAC-PapersOnLine. Volume 49:Issue 17(2016)
• Page Start: 361
• Page End: 366
• Publication Date: 2016
• Subjects: Particle Filter -- Set-Membership Estimation -- Regularized Particle Filter -- Inertial Navigation Update -- Radar Altimeter -- Digital Terrain Elevation Data -- Monte Carlo methods; Automatic control -- Periodicals; 629.805
• DOI: 10.1016/j.ifacol.2016.09.062
• Languages: English
• ISSNs: 2405-8963

Abstract

Abstract: This paper addresses the design of a new set-membership particle filter named Box Regularized Particle Filter (BRPF) applied to terrain navigation. This algorithm combines the set-membership particle estimation (known as Box Particle Filter) with the Kernel estimation method. This approach makes possible to enhance significantly the filter's robustness while reducing the computation time (only 200 particles are needed instead of 5, 000 with a conventional Sequential Importance Resampling (SIR) Particle Filter). Numerical results are presented from 10, 000 Monte-Carlo runs.