海量杂波数据目标点关联定位算法仿真研究

Simulation Research on Target Point Correlation Algorithm for Massive Clutter Data

在杂波环境下进行目标点关联定位过程中,由于存在各种噪声干扰,导致目标点定位不准确,提出海量杂波数据目标点关联定位算法。分析不同传感器侧向数据关联以及定位问题,将整体相关和最近邻方法两者相结合,实现海量杂波数据目标点关联;通过纯方位关联算法组建不同类型传感器的关联矩阵,利用目标点相关信息进行测向结果关联,对上述的测向结果进行提纯、滤波以及交叉定位,获取最终的数据目标点关联定位。仿真结果表明,利用所提算法能够快速、准确获取目标点的准确位置,且计算量较小。

In clutter environment, the target point location is inaccurate due to the noise interference. Therefore, an algorithm of target point association location for massive clutter data was proposed. The problem about lateral data association and location of different sensors was analyzed. The whole correlation and nearest neighbor method were combined to achieve the target point association of massive clutter data. The correlation matrices of different types of sensors were constructed by the bearing-only correlation algorithm. The direction-finding results were correlated by the correlation information of target points, and then the direction-finding results are purified, filtered and located. Finally, the correlation location of data target point was obtained. Simulation results show that the proposed algorithm can obtain the accurate position of target point quickly and accurately, and the computation is small.