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为提高复杂数据融合系统中的航迹关联正确率 ,在ZHOUB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 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 航迹的关联正确率 ,在计算时耗上较完全联合概率法少得多 ,能满足工程中实时性的要求。
In order to improve the accuracy of track association in complex data fusion system, a new approximate multi-sensor multi-target joint probability data association algorithm is proposed based on ZHOUB’s DC and AC algorithms. It takes a goal-centered approximation as the starting point for constructing association events, and in the calculation, an all-neighbor point trajectory association algorithm combining DC with AC has the advantages of dense target and complex track under clutter Data fusion system for experiments, the relevance of the correct rate, associated time-consuming and nearest neighbor method were compared, the effect is better. It can effectively improve the accuracy of the target point trajectory association, in the calculation of the time consumption is much less than the joint probability method can meet the real-time requirements of the project.