An algorithm based on interacting multiple models for maneuvering target tracking
Xulong Chen, Jian Gao, Xing Han · 2014
Kanlman filtering algorithm is commonly used as radar target tracking algorithm. In allusion to the problems caused by the filter divergence and inapposite model parameters of Kaiman filtering, such as low target tracking precision, this paper proposes an adaptive tracking algorithm with Markov probability, namely Interacting Multiple Models (IMM) algorithm, to improve the radar target tracking precision. IMM algorithm can efficiently track one maneuvering target and then realize the adaptive tracking of the target. Simulation results show that IMM algorithm has perfect tracking stability and high tracking precision.