Tracking multiple targets with coordinated turn maneuvers

The problem of tracking multiple maneuvering targets is considered. The usual multiple model approach is adopted in which maneuvering target motion is modeled by assuming that the target motion at each point in time can be described by one of a finite set of dynamic models. Transitions between each mode of target motion are assumed to be Markovian. Target positions are measured in polar coordinates leading to a nonlinear measurement equation. A particle filter is proposed as a solution to the problem. The proposed algorithm seeks to improve upon the performance of a previously proposed particle filter by using measurement-directed proposals and exploiting the structure of the measurement likelihood. The performance analysis focuses on targets which perform coordinated turn maneuvers. An improved model for target motion in this regime is suggested. The performance analysis, using Monte Carlo simulations, demonstrates the improved performance of the proposed algorithm compared to the previously proposed particle filter and the standard Gaussian approximation, the IMM-JPDAF.

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