Improved Interactive Multiple Model Filter for Maneuvering Target Tracking

摘要：

　　Maneuvering target tracking is very important in visual surveillance systems.However,as a popular algorithm,the standard interactive multiple model(IMM)filter has imprecise estimation and computerized intractability.To solve the problems,an improved IMM filter is proposed in this work.First,the Kalman filter(KF)and the unscented Kalman filter(UKF)are employed to estimate the non-maneuvering and maneuvering motion states respectively.Above all,the transition probability is adaptively calculated by using the posterior probability.Numerical simulations are presented to compare the tracking performance of the proposed filter with that of the standard filter.Finally,the results show that the proposed filter is competent for the maneuvering target tracking with excellent performance.

关键词： interacting multiple model unscented Kalman filter transition probability maneuvering target

作者: Bo LI Fuwen PANG Ce LIANG Xiaohong CHEN Yunfeng LIU

作者单位: College of Information Science and Technology,Dalian Maritime University,Dalian 116026,P.R.China;Ele College of Information Science and Technology,Dalian Maritime University,Dalian 116026,P.R.China

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: 7312-7316

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）