摘要
针对强杂波条件下弱目标的检测跟踪问题,提出一种基于外辐射源的极大似然概率数据关联检测跟踪算法。该算法建立了多基站外辐射源雷达系统数学模型,并提出基于极大似然概率数据关联的弱目标航迹起始算法。利用遗传算法解决极大似然概率数据关联中的优化求解问题,以提高目标检测跟踪性能。通过滑窗法实现航迹维持。仿真结果表明,所提算法能有效解决强杂波条件下弱目标的检测跟踪问题,并改善检测跟踪性能。
For the problem of detecting and tracking weak targets in heavy clutter with a multistatic passive coherent location radar,a genetic algorithm maximum likelihood probabilistic data association algorithm is proposed.The mathematical model of multistatic radar for targets detection and tracking is established,and a maximum likelihood probabilistic data association algorithm is presented for track initialization.The genetic algorithm is used for optimization and improve the estimation performance.The track maintenance is achieved in a sliding window manner.Simulation results show the effectiveness of the proposed algorithm.
作者
段金英
李盛
陈恒
DUAN Jin-ying;LI Sheng;CHEN Heng(School of Science,Xijing University,Xi’an 710123,China)
出处
《火力与指挥控制》
CSCD
北大核心
2018年第4期66-70,共5页
Fire Control & Command Control
基金
国家自然科学基金(61371163)
西京学院科研基金资助项目(XJ130110)
关键词
弱目标
外辐射源
极大似然概率
数据关联
航迹起始
遗传算法
滑窗法
weak targets
passive coherent location
maximum likelihood probabilistic
data association
track initialization
genetic algorithm
sliding window
