为提高复杂数据融合系统中的航迹关联正确率,在ZHOU B 的DC 和AC 算法基础上提出了一种新的近似多传感器多目标联合概率数据关联算法。它以一个目标为中心的近似聚为构造关联事件的起点,并在计算中将DC 和AC 结合得到的一种全邻的点迹2航迹关联算法,在杂波下目标密集、航迹复杂的数据融合系统中进行实验,对关联正确率、关联时耗等与最近邻法进行了比较,效果较好。它能有效提高目标点迹2航迹的关联正确率,在计算时上较完全联合概率法少得多,能满足工程中实时性的要求。关键词:近似联合概率数据关联;最近邻法;数据融合Abstract : To improve the correct association rate of track in complex data fusion system , a new association algorithm2 approximate multi2sensor multi2target joint probabilistic data association (AMSJ PDA) is presented in the paper based on DC and AC brought by ZHOU B. AMSJ PDA is a neighbor plot2track association algorithm in which the approximate setof a target is made as the start2point to construct associations and DC is united with AC. It is tested in the data fusion system of compacted targets under scatter wave and complex track. Compared to nearest neighbor , it shows better effects of the correct association rate and association time. It can improve the correct association rate and target plot2track and demand less time needed than joint probabilistic data association. The AMSJ PDA can meet the requirements of real2time in engineering.Keywords :Approximate multi2sensor multi2target joint probabilistic data association ;Nearest neighbor ;Data fusion.
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