基于UMVE算法的恒虚警检测器  

CFAR Detector Based on Unbiased Minimum-variance Estimation Algorithm

作　　者：郝程鹏[1] 侯朝焕[1] 

机构地区：[1]中国科学院声学研究所,北京100080

出　　处：《现代雷达》2007年第7期38-40,44,共4页Modern Radar

基　　金：国家自然科学基金资助项目(60272087)

摘　　要：基于无偏最小方差估计(UMVE)算法,提出了一种新的恒虚警检测器(UMVEM-CFAR)。它的前沿和后沿滑窗均采用UMVE算法来产生局部估计,再对两者求和得到背景功率水平估计。在Swerling II型目标假设下,推导出UMVEM-CFAR在均匀背景下虚警概率Pfa和检测概率Pd及多目标环境下检测概率Pd的解析表达式,与OS-CFAR相比,UMVEM在均匀背景和多目标环境下均具有最好的检测性能,并且它的处理时间只有OS的一半。A new CFAR detector （ UMVEM-CFAR） based on Unbiased Minimum-variance Estimation （ UMVE） is presented in this paper. It takes the sum of UMVE of leading window and UMVE of lagging window as the global noise power estimation. Under Swerling Ⅱ assumption, the analytic expressions of Pfa and Pd in homogeneous background are derived, and the analytic expression of Pd in multiple target situations is also derived. In contrast to OS-CFAR detector, the UMVEM-CFAR detector has better detection performance in both homogeneous background and multiple target situations. The processing time of the UMVEM- CFAR detector is only half that of the OS-CFAR detector.

关 键 词：检测 恒虚警 无偏最小方差估计 

分 类 号：TP21[自动化与计算机技术—检测技术与自动化装置]