Maneuvering target tracking algorithm based on adaptive markov transition probabilitiy matrix and IMM-MGEKF

摘要：

　　This paper proposes a tracking algorithm for maneuvering targets based on the Interacting Multiple Model(IMM)and Modified Gain EKF(MGEKF)algorithm that can modify the Markov transition probability matrix in real time.The algorithm improves the error caused by the transition probability matrix determined by the prior information in the classical IMM algorithm that does not match the current model well.The simulation results show that the maneuvering target tracking performance of this algorithm is better than the conventional IMM-EKF algorithm.

关键词： interactive multi-model algorithm Kalman filter Time-varying Markov transition probability matrix

作者: Suyao Qi Chundong Qi Wenhua Wang

作者单位: School of Information and Electronics Beijing Institute of Technology Beijing,China

会议类型: 国际会议

会议名称: The 12th International Symposium Antennas, Propagation, and EM Theory(ISAPE 2018)?(第十二届天线、传播与电磁理论国际学术会议)

会议地点: 杭州

会议语种:英文

页码: 1-4

在线出版日期: 2018-12-03（万方平台首次上网日期，不代表论文的发表时间）