Bayesian approach to multiple extended targets tracking with random hypersurface models. Issue 4 (1st April 2019)

• Record Type: Journal Article
• Authors: Gao, Lei; Jing, Zhongliang; Li, Minzhe; Pan, Han
• Is Part Of: IET radar, sonar & navigation. Volume 13:Issue 4(2019)
• Page Start: 601
• Page End: 611
• Publication Date: 2019-04-01
• Subjects: iterative methods -- target tracking -- Bayes methods; probabilistic multihypothesis tracking -- approximate measurement update -- variational Bayesian framework -- multiple extended targets -- random hypersurface models; Signal processing -- Periodicals; Radar -- Periodicals; Sonar -- Periodicals; Electronics in navigation -- Periodicals; Navigation -- Periodicals; 621.3848
• DOI: 10.1049/iet-rsn.2018.5315
• Languages: English
• ISSNs: 1751-8784

Abstract

Abstract : A Bayesian approach to multiple moving extended targets tracking is proposed for estimating the shape approximation of the extended targets in addition to their kinematics. Within this approach, the extended target extensions are modelled with random hypersurface models, and a new variant of probabilistic multi‐hypothesis tracking is used for modelling assignments of measurements to extended targets. Moreover, an approximate measurement update that arises directly from the analytical techniques of the variational Bayesian framework is derived to simultaneously estimate the posterior states iteratively including the shape and kinematics of each extended target. The performance of the proposed algorithm is demonstrated with simulated data.