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The Trajectory PHD Filter for Jump Markov System Models and Its Gaussian Mixture Implementation

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Document pages: 6 pages

Abstract: The trajectory probability hypothesis density filter (TPHD) is capable ofproducing trajectory estimates in first principle without adding labels ortags. In this paper, we propose a new TPHD filter referred as MM-TPHD for jumpMarkov system (JMS) model that the highly dynamic targets movement switchesbetween multiple models in multi-trajectory tracking. Firstly, we extend theconcept of JMS to the multi-trajectory scenario of maneuvering target andderive the TPHD recursion for the proposed JMS model. Then, we develop thelinear Gaussian Mixture (LGM) implementation of MM-TPHD recursion and alsoconsider the L-scan computationally efficient implementations. Finally,simulation results in maneuvering multi-trajectory tracking demonstrate theperformance of the proposed algorithm.

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