测向交叉定位中消除虚假点的二次聚类算法

Quadratic Clustering Algorithm for Eliminating False Intersection Points in DOA Location

测向交叉定位中消除虚假点的二次聚类算法,先对每条测向线上的交点进行聚类分析,得到几个聚类程度较高的交点集合,再对该交点集合通过取交集的方法进行二次聚类,得到更少数几个交点集合,最后再对这几个少数的交点集合进行选优,从而消除虚假交点集合,得到真实交点集合。仿真结果表明,该算法关联正确率很高,计算量较小,实时程度较高,适用于多传感器存在漏测的情形。

To realize quadratic clustering algorithm for eliminating false intersection points in DOA location. First, all points of intersection in each direction line are clustered to get a few intersection sets that have high clustering degree. Then, the intersection sets are clustered again by calculating the intersection of all sets and get a few intersection sets. At last, the best intersection sets are selected to eliminate fault intersection sets and get the real sets. The computer simulation results show that the method has high association correctness, low computational complexity and good real time capability. The algorithm adapts to the miss detection situation of multi-sensor.