Distributed Multisensor Multitarget Tracking Algorithm with Time-Offset Registration

时间偏差校准分布式多传感器多目标跟踪算法

¹ School of Automation, Northwestern Polytechnical University, Xi'an 710072, China
² Beijing Aerospace Automatic Control Institute, Beijing 100854, China

Received: 8 October 2019

Abstract

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.

摘要

由于信号处理、量测采集延时等原因，导致多传感器系统中存在量测时间戳不准确，即量测时间偏差。针对量测存在时间偏差的分布式多传感器系统，提出一种时间偏差校准分布式多传感器多目标跟踪算法。在局部处理器，针对传感器量测存在虚警和漏检的情况，基于联合概率数据关联（JPDA）和扩展卡尔曼滤波（EKF）算法进行多目标跟踪，估计出存在时间偏差的局部航迹。在全局处理器，针对局部航迹时间偏差导致全局航迹精度下降的问题，首先，采用逆卡尔曼滤波基于局部航迹构造等效量测，针对匀速直线运动目标，推导出相对时间偏差伪量测方程并给出计算方法；然后，提出一种基于伪量测的相对时间偏差估计算法，采用递推最小二乘估计与卡尔曼滤波在空域及时域实现了相对时间偏差的联合估计；最后，设计一个时间偏差校准分布式多传感器多目标跟踪架构，联合进行时变时间偏差估计与补偿、"等效量测-全局航迹"关联和全局航迹更新。虚警和漏检下的多传感器多目标跟踪仿真结果表明：量测存在时间偏差情况下，所提算法可以有效提高融合后的全局航迹精度。