基于Cramer-Rao界的密集目标统计分辨限

发布时间：2018-07-25 13:24

【摘要】：基于Cramer-Rao界,对Smith~([10])给出的密集信号统计分辨限(statistical resolution limit,SRL)进行了进一步研究,给出了一般结果.推导得出了两个点目标空间频率差Cramer-Rao界(CRB)的闭式表达式,并针对目标密集分布情况对此CRB进行了渐进分析,进一步由Smith准则确定了雷达系统密集目标分辨限的一般形式.SRL是目标功率比、目标回波初相差和信噪比(R_(sn))的函数.探讨了不同功率比和初相差条件下SRL与两个目标R_(sn)的关系.极大似然估计(MLE)仿真结果表明,在可分辨区内MLE的实验性能达到了CRB;在本文预测的分辨限处MLE的性能开始偏离CRB曲线.仿真结果验证了本文给出的统计分辨限是准确、合理的.
[Abstract]:Based on the Cramer-Rao bound, a further study of the statistical resolution limit (statistical resolution limited SRL) for dense signals given by Smith ~ (10) is carried out, and the general results are given. In this paper, the closed expression of Cramer-Rao bound of frequency difference between two point objects is derived, and the asymptotic analysis of the CRB for the dense distribution of the target is carried out. Furthermore, the general form of the resolution limit of dense targets in radar system is determined by Smith criterion. SRL is a function of the target power ratio, the initial phase difference of the target echo and the signal-to-noise ratio (R _ (sn). The relationship between SRL and two targets R _ (sn) under different power ratio and initial phase difference is discussed. The maximum likelihood estimation (MLE) simulation results show that the experimental performance of MLE in the discernible region is up to that of CRB, and that the performance of MLE begins to deviate from the CRB curve at the resolution limit predicted in this paper. The simulation results show that the statistical resolution given in this paper is accurate and reasonable.
【作者单位】：北京理工大学信息与电子学院;中国兵器工业第203研究所;
【基金】：高等学校学科创新引智计划资助(B14010)
【分类号】：TN957.2

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