飞控与探测2024，Vol.7Issue(4)：87-95,9.
基于向量线性表示的集群点目标同一性识别方法
Method of Vector Linear Representation-Based Point Cluster Target Registration
摘要
Abstract
Cluster attacks have become an important means in modern warfare. However,the main technical chal-lenges faced by cluster target interception were how to detect and plan to intercept them. In order to detect cluster targets,this paper fused images from ground radars and missiles,and localized targets using multi-view stereo. In view of this,we explored the relationship between vector linear representation and linear transformation of coordi-nate systems among multiple views firstly,and then proposed a target description method based on vector linear representation which can be used to identify point targets in clusters effectively. The experiments showed that the accuracy of identity for sparse cluster targets was as high as 99.6％ under ideal conditions. And in the case,where the existing topological distortion was caused by relative pose errors,the accuracy of identity was over 99％. What is more,with errors from upstream small and weak target recognition tasks,the accuracy of identity recognition can reach up to 95％ under the premise of no change in the available topology of the cluster.关键词
稀疏集群目标/多视角/同一性识别/向量线性表示Key words
sparse cluster targets/multi-view/identity recognition/vector linear representation分类
信息技术与安全科学引用本文复制引用
麻家骅,魏东,吴楚泽,齐文元,李元祥,杨永胜..基于向量线性表示的集群点目标同一性识别方法[J].飞控与探测,2024,7(4):87-95,9.基金项目
上海航天先进技术联合研究基金项目(USCAST2022-35) （USCAST2022-35）
