Abstract
To maneuvering target tracking with multiple passive sensors in clutter environment, a novel algorithm based on particle filter is proposed. In this algorithm, the likelihood function of particle filter in clutter is derived. Then the particle filter and Interactive Multiple Model (IMM) method are integrated. The former solves the proplem of passive target manoeuvre and the latter deals with the nonlinear problem of the measurement equation. In order to avoid the unobservability problem of passive target tracking, a nonlinear measurement model of multiple passive sensors is founded, and the algorithm can deal with the case of non-gaussian noise. Finally, the simulation results show that the proposed algorithm is effective, and its performance is superiority over the interacting multiple model-probabilistic data association filter (IMM-PDAF).
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