Maneuvering Target Tracking Using Passive TDOA Measurements

摘要：

　　This paper proposes a novel interacting multiple model (IMM) algorithm to track a maneuvering target,with the aim of improving the tracking performance of a time difference of arrival (TDOA) passive tracking system.Under the architecture of the proposed algorithm,the multiple model deals with the model switching,while the iterated extended Kalman filter (EKF) accounts for non-linearity in the dynamic system models.The tracking performances of the proposed algorithm,EKF,IMM are compared via Monte Carlo simulations.Simulation results indicate that the proposed algorithm is an effective nonlinear filtering algorithm for TDOA passive tracking system,and has higher tracking precision than the IMM and EKF.The proposed algorithm can reduce nearly 6.75% and 61.23% of the positioning error than IMM and EKF algorithms.

关键词： Extended Kalman filter (EKF) Interacting multiple model (IMM) Time difference of arrival (TDOA) target tracking

作者: WU Panlong GUO Qiang ZHANG Xinyu BO Yuming

作者单位: Department of Automation,Nanjing University of Science and Technology,Nanjing 210094 Network Management Center,Sias International University,Xinzheng,451150

会议类型: 国际会议

会议名称: The 33th Chinese Control Conference第33届中国控制会议

会议地点: 南京

会议语种:英文

页码: 758-762

在线出版日期: 2014-07-28（万方平台首次上网日期，不代表论文的发表时间）