一种基于估计误差统计的虚假点迹序列辨识算法  

An Algorithm For False Trace Sequence Identification Based on Statistical Characteristic of the Estimation Error

作　　者：邢雷[1] 李品[1] 段蕾[1] XING Lei;LI Pin;DUAN Lei(Nanjing Research Institute of Electronics Technology,Nanjing 210039,China)

机构地区：[1]南京电子技术研究所,江苏南京210039

出　　处：《中国电子科学研究院学报》2020年第12期1186-1192,共7页Journal of China Academy of Electronics and Information Technology

摘　　要：受复杂环境下的干扰和杂波影响,虚假目标识别和剔除是雷达数据处理所面临的重要问题之一。为对抗杂波虚警和欺骗干扰目标,通过多次观测利用运动状态估计来进行虚假目标识别和剔除是一种较为有效的方法。实际情况中,目标真实运动状态未知且存在测量误差,因此有必要对运动状态的估计误差进行研究并选择合适的虚假点迹抑制门限。针对该问题,文中基于线性回归方法,分析了一阶估计模型并统计评估了其状态估计误差,进一步通过对距离、速度、加速度联合建模推导了高阶最小均方误差模型,说明在该准则下状态估计与测量值之差的平方和属于卡方分布,进而指出可以采用相应假设检验来实现虚假目标抑制。最后,文章通过仿真对模型的误差概率特性进行验证,对比了不同虚警和干扰场景下虚假目标的抑制效果。Affected by jamming and clutter in complex environments,identification and elimination of spurious target is one of the most important problems for radar data processing.To achieve the goal,multiple consequent observations can be utilized to identify spurious targets by joint estimation of their motion state.As the true motion state of target cannot be obtained and observation error exists in real situation,statistical characteristic of the estimation error needs to be analyzed to determine the parameter of hypothesis testing method.To solve the problem,a linear regression based approach is proposed to analyze the one dimensional estimation model and evaluate corresponding estimation error.Furthermore,by joint modeling target range,velocity and acceleration under minimum mean-squared error criterion,we prove that the estimation error model of the proposed approach is chi-square distribution.As a result,hypothesis testing can be adopted to suppress spurious target.Simulation experiments show that the statistical characteristic of the estimation error is consistent with chi-square distribution and the proposed approach is able to eliminate most of the spurious target in different jamming scenarios.

关 键 词：卡方分布 干扰目标 线性回归 杂波虚警 点迹序列 

分 类 号：TN953[电子电信—信号与信息处理]