基于红外和雷达的目标跟踪数据关联快速算法

Fast Data Association Algorithm for Target Tracking with Infrared Sensor and Radar

在顺序串行多传感器联合概率数据关联算法的基础上,提出了一种杂波环境下多传感器多机动目标快速跟踪算法,即顺序的MSFAFDA.首先顺序地用来自红外和雷达的量测更新状态估计,然后应用多传感器快速数据关联算法进行数据关联,易于推广到具有多个传感器的跟踪系统.仿真结果表明,MSFAFDA算法的计算量要比一般的多传感器IMM-JPDA算法小,具有更快的收敛速度;跟踪的目标数越多,MSFAFDA算法在实时性方面的优势就越明显.

Based on sequential serial Multi-sensor Joint Probabilistic Data Association algorithm, a multi-sensor fast algorithm for data association of multi-target tracking under clutter is proposed, i.e. , sequential MSFAFDA. It first sequentially utilizes measurements from infrared sensor and radar update state estimation, then realizes data association with MSFAFDA which can be easily generalized to tracking system with more than two sensors. Simulation results show MSFAFDA has smaller computation complexity than Interacting Multiple Model Joint Probabilistic Data Association （IMM-JPDA） algorithm, and faster convergent speed. And the more targets, the more advantage is obvious in real-time performance of MSFAFDA.