火力与指挥控制2009，Vol.34Issue(10)：25-28,4.
测向交叉定位中基于最小距离的二次聚类算法
Quadratic Clustering Algorithm based on Least Distance in DOA Location
摘要
Abstract
In this paper, a quadratic clustering algorithm based on least distance is proposed in order to solve the problems of high computational complexity and low association correctness existing in the usual clustering algorithms of DOA location. In this method, all points of intersection in each direction line are clustered with least distance 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. It guarantees high association correctness of real sets through regressing calculation of intersection points. The computer simulation results show that the method has high association correctness, low computational complexity and good realtime capability. It also shows that the method adapts to the miss detection situation of multisensors.关键词
测向交叉定位/聚类算法/数据关联Key words
DOA location/clustering algorithm/data association分类
信息技术与安全科学引用本文复制引用
蒋维特,杨露菁,杨亚桥..测向交叉定位中基于最小距离的二次聚类算法[J].火力与指挥控制,2009,34(10):25-28,4.基金项目
"十一五"国防预研基金资助项目(10103060103) （10103060103）
