The square root sigma points Kalman filter based IMM algorithm for maneuvering target passive tracking

摘要：

A novel maneuvering target tracking algorithm of combining the standard interacting multiple model (IMM) algorithm with the square root sigma point Kalman filter (SRSPKF) is proposed. The proposed algorithm do not calculate the Jacobian matrix required by extend Kalman filter(EKF) based IMM. By revising the Interaction reinitialization step of IMM into a square root form, the proposed algorithm can propagate the Cholesky factor of state covariance matrix directly to suit SRSPKF. We explore the proposed algorithm to track maneuvering emitter with a single passive observer, which processes Doppler frequency changing rate and angle measurements concurrently, thus the observer maneuver is not necessary to satisfy the observerability condition.Computer simulations are conducted to compare the SRSPKF based IMM (SRSPKF-IMM) tracker with the traditional EKF based IMM(EKF- IMM) tracker.Simulation results demonstrate that the SRSPKF-IMM tracker is more stable and effective.

关键词： maneuvering target tracking passive location interacting multiple model sigma points Kalman filter square root filter

作者: Zhengbin Yang Danxing Zhong Fucheng Guo Yiyu Zhou

作者单位: School of Electronic Science and Engineering National University of Defense Technology Changsha, Hunan 410073, China

会议类型: 国际会议

会议名称: The International Colloquium on Onformation Fusion 2007(2007年国际信息融合研讨会)

会议地点: 西安

会议语种:英文

页码: 118-123

在线出版日期: 2007-08-22（万方平台首次上网日期，不代表论文的发表时间）