CAJ | 학술논문

本文提出一种基于模型相似度拟合的海杂波统计方法。首先根据合成孔径雷达（SAR）图像计算瑞利分布、对数正态分布、韦布尔分布、K 分布、G0分布5种经典的海杂波分布的概率密度函数，然后根据模型间的相似度准则拟合得到新的海杂波分布模型。文章利用四景不同类型的真实 SAR 数据对算法的拟合性能进行了评价，结果显示利用该算法得到的拟合模型与真实 SAR 数据的平均Kullback-Leibler 距离仅为0．01584，远优于其他分布模型。基于该拟合模型的恒虚警率舰船检测算法对四景 SAR 数据的平均检测精度达到95．75％，在控制虚警和漏检方面均优于采用其他模型的同类方法。
본문제출일충기우모형상사도의합적해잡파통계방법。수선근거합성공경뢰체（SAR）도상계산서리분포、대수정태분포、위포이분포、K 분포、G0분포5충경전적해잡파분포적개솔밀도함수，연후근거모형간적상사도준칙의합득도신적해잡파분포모형。문장이용사경불동류형적진실 SAR 수거대산법적의합성능진행료평개，결과현시이용해산법득도적의합모형여진실 SAR 수거적평균Kullback-Leibler 거리부위0．01584，원우우기타분포모형。기우해의합모형적항허경솔함선검측산법대사경 SAR 수거적평균검측정도체도95．75％，재공제허경화루검방면균우우채용기타모형적동류방법。
A sea clutter statistical method based on similarity fitting is proposed in this paper.We first estimate five classical probability density functions of the sea clutter distribution in synthetic aperture radar (SAR)imagery, which include Rayleigh distribution,lognormal distribution,Weibull distribution,K distribution and G0 distribution. Thereafter,we fit all these five models to a new sea clutter distribution by an optimization method based on a simi-larity criterion.In the experiment,we evaluate the fitting precision based on the Kullback-Leibler distance using four SAR images.The results show the K-L distance between the fitting model and observations is only 0.015 84 when using the proposed algorithm.The fitting model is concluded to be superior to five classical distribution mod-els.When we conduct ship detection using the fitting model and CFAR algorithm,the mean detection accuracy can reach up to 95.75%.