To eliminate the adverse impact on filter precision which was brought about by the maneuvering multi-target tracking system's strong nonlinear and motion model switching in clutters environment, a novel maneuvering multi-target tracking algorithm based on multiple model particle filter was presented. The dynamic combination of multiple model particle filter and generalized probabilistic data association method was realized in the new algorithm. The rapid expansion of computational complexity, caused by the simple combination of the interacting multiple model and particle filter, was solved by introducing model information into the sampling process of particle state. And the effective validation and utilization of echo was accomplished by generalized probabilistic data association algorithm. The concrete steps of algorithm were given, and the theory analysis and simulation results showed its validity.
