结合最小熵的SAS图像自聚焦研究  

SAS Autofocus Combined with Minimum Entropy

作　　者：朱三文[1] 唐劲松[1] 胡金华[1] 

机构地区：[1]海军工程大学电子工程系,湖北武汉430033

出　　处：《测控技术》2009年第3期81-84,共4页Measurement & Control Technology

基　　金：国家"863"计划资助项目(2007AA091101)

摘　　要：合成孔径声呐成像中,主要通过自聚焦校正剩余相位误差。最小熵自聚焦算法是典型的参数化自聚焦方法,一般用于估计二次相位误差。拖鱼前向速度偏差是引起回波数据中存在二阶相位误差的重要来源,为此提出将最小熵算法和R-D算法结合用于校正SAS图像中由于速度偏差引入的二次相位误差。仿真和实测数据处理结果表明所提出的方法可以有效补偿图像中由于速度偏差引起的相位误差。In synthetic aperture sonar imaging, the residual phase error is mainly corrected via autofocus. Mini- mum entropy autofocus is a typical parametric autofocus method which is used to estimate and correct quadratic phase error. Quadratic phase error is mainly caused by forward velocity and acceleration of line of sight. Quad- ratic phase error is corrected by using R-D algorithm combined with minimum entropy. Simulation and experi- ment from lake test show the validity of the method presented.

关 键 词：合成孔径声呐 R-D算法 最小熵 二次相位误差 

分 类 号：TN911.73[电子电信—通信与信息系统]