基于UMVE算法的恒虚警检测器

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SwerlingⅡ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只的解析表达式，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。

CFAR Detector Based on Unbiased Minimum-variance Estimation Algorithm

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.