MAXIMUM A POSTERIORI-BASED AUTOMATIC TARGET DETECTION IN SAR IMAGES  

作　　者：Wang Yimin An Jinwen 

机构地区：[1]College of Automation, Northwestern Polytechnical University, Xi＇an 710072, China

出　　处：《Journal of Electronics(China)》2005年第6期594-598,共5页电子科学学刊（英文版）

摘　　要：The paper presents an algorithm of automatic target detection in Synthetic Aperture Radar(SAR) images based on Maximum A Posteriori(MAP). The algorithm is divided into three steps. First, it employs Gaussian mixture distribution to approximate and estimate multi-modal histogram of SAR image. Then, based on the principle of MAP, when a priori probability is both unknown and learned respectively, the sample pixels are classified into different classes c = {target,shadow, background}. Last, it compares the results of two different target detections. Simulation results preferably indicate that the presented algorithm is fast and robust, with the learned a priori probability, an approach to target detection is reliable and promising.The paper presents an algorithm of automatic target detection in Synthetic Aperture Radar（SAR） images based on Maximum A Posteriori（MAP）. The algorithm is divided into three steps. First, it employs Gaussian mixture distribution to approximate and estimate multi-modal histogram of SAR image. Then, based on the principle of MAP, when a priori probability is both unknown and learned respectively, the sample pixels are classified into different classes c = （target, shadow, background）. Last, it compares the results of two different target detections. Simulation results preferably indicate that the presented algorithm is fast and robust, with the learned a priori probability, an approach to target detection is reliable and promising.

关 键 词：Synthetic Aperture Radar（SAR） image Target detection Maximum A Posteriori（MAP） Gaussian mixture distribution 

分 类 号：TN95[电子电信—信号与信息处理]