关键词: 目标跟踪, 交互式多模型, 粒子滤波, 交互式多模型无迹卡尔曼滤波（IMM-UPF）

Abstract: In maneuvering target tracking，the movement model is non-linear or the noise is uncertain and so on.To solve these problems，an Interacting Multiple Model-Unscented Particle Filter（IMM-UPF） is designed by combining Interacting Multiple Model（IMM），Particle Filter（PF） and Unscented Kalman Filter（UKF）.In this algorithm，the multiple models structure is used to track arbitrary maneuvering of the target，particle filter is used in every model to deal with the nonlinear and non-Gaussian problems，and UKF is used to produce particles，thus，the distribution of particles is closer to the posterior probability density distribution and the degradation of particle phenomenon is overcome，which enhances the accuracy of estimations for the current observations accounted.The model set of the system contains three models based on the actual movement model.At the end，the results demonstrate the efficiency of the new filtering method through the example of simulation，and the performance of IMM-UPF is better than PF，UPF algorithms.

Key words: target tracking, interacting multiple model, Particle Filter（PF）, Interacting Multiple Model-Unscented Particle Filter（IMM-UPF）