基于多重判别的雷达网距离向多干扰目标鉴别

摘要

Aiming at the high computational complexity and high confusion,during the discrimination of the multi-range-false-targets,a technique based on multiple discriminations for multi-range-false-target jamming of long baseline radars network is proposed.Firstly,aiming at the target measurements association time increases with the increase of the range-false-target numbers,target measurements from radar network are classified into true-true,true-false,false-true and false-false cases for simplification.Then,to improve the correct recognition rate,multiple nearest neighbor and bearings-only associations method is applied.Finally,theoretical analysis and simulation test are used to compare the proposed method with the nearest neighbor method.The results verify that the proposed method is able to improve the correct recognition rate as well as reduce the time of asso-ciation discrimination evidently.%针对距离多假目标迷惑性强，鉴别过程计算复杂度高的问题，在长基线雷达组网背景下提出了一种基于多重判别的距离向多干扰目标鉴别技术。首先，针对目标量测关联判别次数随假目标数量增加而增加问题，将来自雷达网各目标量测分为真真、真假、假真、假假4种情况，以降低计算量；然后，采用最近邻角度信息多重判别的方法提高真假目标的正确识别率；最后通过理论分析和仿真实验的方法，对本文方法与经典的最近邻关联方法进行对比分析，结果表明，本文方法能够在提高正确识别率的同时显著减少判别时间。