Data Fusion of Infrared and Radar for Target Tracking

摘要：

A target tracking method based on data fusion of infrared and radar is proposed to improve tracking precision. Unscented Kalman filter (UKF) is applied to process data on distributed fusion architectures. The method combines the advantages of UKF and track-to-track algorithms. The cross covariances of the two sensors are used to estimate overall covariance and states. The overall estimation is obtained by the track-to-track fusion algorithm for the optimal combination of two correlated estimates. The proposed method is applied to simulating target tracking of infrared and radar. The simulation results show the proposed method has advantages in higher precision, and probability of detection is increased.

作者: Anfu ZHU Zhanrong JING Weijun CHEN Liguang WANG Yunfei LI Zhenlin CAO

作者单位: School of Electronic and Information,Northwestern Polytechnical University,Xian,710072,China Department of Computer Science,Weinan Teachers University,Weinan 714000,China YIMA Coal Industry (Group) CO.,LTD,Yima,472300,China

会议类型: 国际会议

会议名称: The 2nd International Symposium on Systems and Control in Aeronautics and Astronautics(第二届航空航天系统与控制国际会议 ISSCAA 2008)

会议地点: 深圳

会议语种:英文

页码: 1005-1008

在线出版日期: 2008-12-10（万方平台首次上网日期，不代表论文的发表时间）