低空蜂群目标点航迹精细化融合算法研究  

Study on Fusion Combination Algorithm of Low- altitude Bee Colony Target Point Track

作　　者：王家隆[1] 何文涛 王琦 孙辰欣 WANG Jia-long;HE Wen-tao;WANG Qi;SUN Chen-xin(China Electronics Technology Group Corporation 15,Beijing 100000,China)

机构地区：[1]中国电子科技集团公司第十五研究所,北京100000

出　　处：《航空计算技术》2022年第2期44-48,共5页Aeronautical Computing Technique

摘　　要：为了实现目标点航迹数据的关联,形成连续稳定的精细化蜂群目标融合航迹。针对低空蜂群目标点航迹融合时易出现关联错误的问题,提出了基于群目标精细化管理的低空蜂群目标点航迹融合算法。选取低空固定队型为分析对象,构建低空组网雷达数据融合模型,对各低空预警探测雷达上报的蜂群目标点航迹信息分簇,形成稳定的簇目标航迹,建立簇内目标航迹精细化管理机制;然后计算簇内目标相对位置坐标向量,实现簇内目标的精细化关联,生成稳定的簇内目标精细化航迹,准确估计蜂群目标的运动状态,并通过实验验证了算法的准确性和有效性。In order to realize the correlation of target point track data, a continuous and stable fine swarm target fusion track is formed.Aiming at the problem that low altitude bee colony target point track fusion is prone to association errors, a low altitude bee colony target point track refinement fusion algorithm is proposed.Firstly, the low altitude fixed formation is selected as the analysis object, the low altitude networking radar data fusion model is constructed, and the bee colony target point track information reported by each low altitude early warning detection radar is clustered.Form a stable cluster target track, establish the fine management mechanism of the target track in the cluster, then calculate the relative position coordinate vector of the target in the cluster, realize the fine association of the target in the cluster, generate a stable fine track of the target in the cluster, and accurately estimate the motion state of the bee colony target.Finally, experiments verify the accuracy and effectiveness of the algorithm.

关 键 词：低空组网雷达 航迹关联 目标航迹融合 蜂群目标跟踪算法 

分 类 号：V243.2[航空宇航科学与技术—飞行器设计]