针对密集杂波环境下多目标数据关联问题,提出了一种基于弱化算子自适应模糊C均值聚类的数据关联算法。该算法首先采用弱化算子对有效回波进行弱化处理,在此基础上应用自适应模糊C均值算法对目标有效回波进行聚类,并将聚类中心作为相应目标最终观测值,最后采用最近邻法将聚类中心与目标航迹配对。实验结果表明,该算法与FCM方法相比,具备更高的关联和跟踪精度;与JPDA算法相比,提高了关联时实性。

In oder to solve the problem of multi-target date association in dense clutter, a novel algorithm of data association was proposed based on weakening operator self-adepted fuzzy C-means. First, in the new algorithm, the weakening operator was used to reduce the randomness of effective echoes, then the self-adepted FCM algorithm was used to cluster effective echoes, and the resulting cluster centers were considered the final measurement of the targets. Finally, the nearest neighboring algorithmwas used to associate the culster centers with the tracks. Simulation results show the algorithm has a better tracking and associating accuracy than FCM data association algorithm and the CPU occupies a relatively short time than JPDA algorithm.