雷达科学与技术2017，Vol.15Issue(3)：241-246,6.DOI:10.3969/j.issn.1672-2337.2017.03.003
一种马尔可夫矩阵自适应的IMM-CKF算法
An IMM-CKF Target Tracking Algorithm Based on Adaptive Markov Transition Probability Matrix
摘要
Abstract
To solve the problem that the Markov transition probability matrix is constant in traditional interacting multiple model(IMM) algorithm,a new IMM-CKF target tracking algorithm,based on adaptive Markov transition probability matrix,is proposed.The proposed algorithm introduces a coefficient to adjust each element of the Markov transition probability matrix.The proposed algorithm increases the probability of matching models observably,reduces the effects of the mismatch models,and improves the final filtering resuhs at the same time.Finally,the Monte Carlo simulation results show that the proposed adaptive IMMCKF algorithm has better tracking performance compared with the traditional IMM-CKF algorithm.关键词
IMM算法/容积卡尔曼滤波/Markov概率转移矩阵/目标跟踪Key words
IMM algorithm/cubature Kalman filter/Markov transition probability matrix/target tracking分类
信息技术与安全科学引用本文复制引用
刘国情,袁俊泉,马晓岩,陈阿磊,王力宝..一种马尔可夫矩阵自适应的IMM-CKF算法[J].雷达科学与技术,2017,15(3):241-246,6.基金项目
学院科研创新基金重大基础研究专项课题(No.2014ZDJC0102) （No.2014ZDJC0102）
