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It is difficult to track multiple maneuvering targets of which the number is unknown and timevarying,especially when there is range ambiguity.The random finite sets(RFS)based probability hypothesis density filter(PHDF)is an effective solution to the problem of multiple targets tracking.However,when tracking multiple targets via the range ambiguous radar,the problem of range ambiguity has to be solved.In this paper,a multiple model PHDF and data association(MMPHDF-DA)based method is proposed to address multiple maneuvering targets tracking with range ambiguous radar in clutter.Firstly,by introducing the turn rate of target and the discrete pulse interval number(PIN)as components of target state vector,and modeling the incremental variable of the PIN as a three-state Markov chain,the problem of multiple maneuvering targets tracking with range ambiguity is converted into a hybrid state filtering problem.Then,by implementing a novel“track-estimate”oriented association with the filtering results of the hybrid filter,target tracks are provided at each time step.Simulation results demonstrate that the MMPHDF-DA can estimate target state as well as the PIN simultaneously,and succeeds in multiple maneuvering target tracking with range ambiguity in clutter.Simulation results also demonstrate that the MMPHDF-DA can overcome the limitation of the Chinese Remainder Theorem for range ambiguity resolving.
It is difficult to track multiple maneuvering targets of which the number is unknown and timevarying, especially when there is range ambiguity. Random number sets (RFS) based probability hypothesis density filter (PHDF) is an effective solution to the problem of multiple targets tracking The problem of range ambiguity has to be solved.In this paper, a multiple model PHDF and data association (MMPHDF-DA) based method is proposed to address multiple maneuvering targets tracking with range ambiguous radar in clutter. Firstly, by introducing the turn rate of target and the discrete pulse interval number (PIN) as components of target state vector, and modeling the incremental variable of the PIN as a three-state Markov chain, the problem of multiple maneuvering targets tracking with range ambiguity is converted into a hybrid state filtering problem. Chen, by implementing a novel “track-estimate ” oriented association with the filtering results of the hybrid filter, target tracks are provided at each time step. Simulation results demonstrate that the the MMPHDF-DA can estimate target state as well as the PIN simultaneously, and succeeds in multiple maneuvering target tracking with range ambiguity in clutter. Simulation results also demonstrate that the MMPHDF-DA can overcome the limitation of the Chinese Remainder Theorem for range ambiguity resolving.