Distributed Multisensor Multitarget Tracking Algorithm with Time-Offset Registration

被引：3
|
作者：
Li S. [1 ]
Cheng Y. [1 ]
Wang H. [1 ]
Gao S. [2 ]
机构：
[1] School of Automation, Northwestern Polytechnical University, Xi'an
[2] Beijing Aerospace Automatic Control Institute, Beijing
来源：
Xibei Gongye Daxue Xuebao/Journal of Northwestern Polytechnical University | 2020年 / 38卷 / 04期
关键词：
Distributed track fusion; Equivalent measurement; Multitarget tracking; Pseudo-measurement equation; Time-offset estimation;
D O I：
10.1051/jnwpu/20203840797
中图分类号：
学科分类号：
摘要：
In multisensor systems, the signal processing delay, measurement acquisition delay, and other factors will lead to imprecisely time-stamped measurements, namely, the problem of time-offset. To deal with the measurement time offsets in distributed multisensor systems, a distributed multisensor multitarget tracking algorithm with time-offset registration is proposed. The local processors track multiple targets in the presence of false alarms and missed detections based on the joint probabilistic data association (JPDA) algorithm and the extended Kalman filter (EKF), providing the time-biased local tracks. In the global processor, in allusion to the global track accuracy degradation introduced by the time offsets of local tracks, the equivalent measurements are firstly constructed based on local tracks by using the inverse Kalman filter. The pseudo-measurement equation of time offset for constant velocity targets is derived and the pseudo-measurement calculation method is presented. Then, the pseudo-measurement based relative time-offset estimation algorithm is presented, by using the recursive least squares estimation (RLSE) and the Kalman filter (KF) to jointly estimate the state in space and time domains, respectively. Finally, a framework of distributed multisensor multitarget tracking with time-offset registration is presented, where the time-varying relative time-offset estimation and compensation, 'equivalent measurement to global track' association, and global track update are included. Simulations for multisensor multitarget tracking in the presence of false alarms and missed detections are conducted, demonstrating that the present algorithm effectively improves the accuracy of fused global tracks. © 2020 Journal of Northwestern Polytechnical University.
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页码：797 / 805
页数：8
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