极不均匀合成孔径雷达杂波建模及恒虚警检测

基于合成孔径雷达(SAR)城区极不均匀杂波实际数据和Cramer-Von Mises距离,本文运用Rayleigh分布、Weibull分布、K分布和G分布对杂波进行了分布拟合检验.结果表明Rayleigh分布和Weibull分布难以拟合极不均匀场景回波,K分布只能部分拟合,而G分布的拟合程度最好.进而,针对G分布下的目标恒虚警检测问题,本文给出了不同参考单元条件下达到给定检测性能时信噪比随形状参数的变化曲线,分析了恒虚警(CFAR)性能损失随分布参数变化的原因,得到了确定恒虚警门限的有效方法.

Model Validation of the Extremely Heterogeneous SAR Clutter and Its CFAR Detection

Based on real extremely heterogeneous synthetic aperture radar(SAR) urban clutter data and Cramer-Von Mises distance,the goodness-of-fit tests were done via Rayleigh distribution,Weibull distribution,K distribution and G distribution,respectively.It is shown that the Rayleigh distribution and Weibull distribution may be mismatched and the K distribution may be only partly matched,but the G distribution may model the real data very well.Furthermore,for the CFAR(Constant False Alarm Rate) detection under the G distributed clutter,the curves of the signal-to-noise ratio versus shape parameter and numbers of reference cells were presented to meet the given detection performance,and the reason was also analyzed that the CFAR losses decrease with the increasing of the distribution parameter.Also,an effective CFAR threshold calculating method was proposed at last.