Technical Program

Paper Detail

Session:Advances in Signal Processing for Positioning, Tracking, and Navigation
Time:Thursday, May 20, 16:30 - 16:50
Presentation: Special Session Lecture
Topic: Special Sessions: Advances in signal processing for positioning, tracking, and navigation
Authors: Mónica F. Bugallo; Stony Brook University 
 Shanshan Xu; Stony Brook University 
 Joaquín Míguez; Universidade da Coruña 
 Petar M. Djurić; Stony Brook University 
Abstract: Target tracking is a highly nonlinear problem that has been successfully addressed in recent years using sequential Monte Carlo (SMC) methods, usually called particle filters. In this paper, we investigate the application of a new class of SMC techniques, termed cost-reference particle filters (CRPFs), to tracking of a high-speed maneuvering target. The new CRPF methodology drops all probabilistic assumptions (i.e., prior probabilities, knowledge of noise distributions and likelihood functions) that are common to conventional particle filters and, as a consequence, leads to practically more robust algorithms. The advantage of the proposed CRPF over the standard SMC filter in the context of maneuvering target tracking is illustrated through computer simulations.

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