面向舰船目标检测的单通道复值SAR图像统计建模方法研究

Statistical Modeling Methods of Single-channel Complex-valued SAR Images for Ship Detection

合成孔径雷达(SAR)成像模式丰富、覆盖范围广、分辨率高,可以长期、动态、宏观地对海洋进行监测。在完全发展的相干斑假设条件下,传统单通道SAR图像舰船目标检测方法主要研究幅度信息。然而,其部分假设条件在高分辨率情形下并非严格成立,因此无法有效利用单通道SAR图像的相位或复值信息。该文面向舰船目标检测应用,将单通道复值SAR图像统计建模方法划分为幅度、相位和复值统计建模3个部分,首先简要综述了单通道SAR图像幅度统计建模方法,然后详细阐述了单通道SAR图像相位和复值统计建模方法,并重点介绍了其建模过程和参数估计方法。在此基础上,该文给出了作者研究小组在基于复值统计信息的单通道SAR图像舰船目标检测方面的部分最新研究结果,并分析展望了下一步研究方向。

Synthetic Aperture Radar(SAR),which features rich imaging modes,wide coverage,and high resolution,is an effective technique for long-term,dynamic,and large-scale monitoring of the ocean.Under the assumption of fully developed speckle,traditional ship detection methods in single-channel SAR images focus mainly on amplitude information.Since conventional assumptions are not strictly true in high-resolution situations,this prevents the full investigation of phase or complex-valued information in single-channel SAR images.In this paper,with a focus on ship detection applications,we categories the methods used in the statistical modeling of single-channel complexvalued SAR images as amplitude-,phase-,or complex-valued-based.After providing a brief overview of amplitude statistical modeling methods,we focus on phase and complex-valued statistical modeling methods of single-channel SAR images,describing their modeling processes and parameter estimation methods.We then present the results of our recent ship detection research based on complex-valued statistical information in single-channel SAR images and make suggestions regarding future research.