| Paper: | SS-9.4 | ||
| 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 | ||
| Title: | MANEUVERING TARGET TRACKING USING COST REFERENCE PARTICLE FILTERING | ||
| 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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