计科峰,,
熊博莅,
匡纲要
国防科技大学电子科学学院 电子信息系统复杂电磁环境效应国家重点实验室 长沙 410073
基金项目:国家自然科学基金(61601035, 61971426)
详细信息
作者简介:冷祥光(1991–),男,江西九江人,博士,国防科技大学电子科学学院讲师,研究方向为遥感信息处理、SAR图像智能解译和机器学习
计科峰(1974–),男,陕西长武人,博士,国防科技大学电子科学学院教授,博士生导师,研究方向为SAR图像解译、目标检测与识别、特征提取、SAR和AIS匹配
熊博莅(1981–),男,湖南益阳人,博士,国防科技大学电子科学学院CEMEE国家重点实验室副教授,研究方向为遥感图像智能解译、SAR图像配准及变化检测
匡纲要(1966–),男,湖南衡东人,博士,国防科技大学电子科学学院CEMEE国家重点实验室教授,博士生导师,图形与图像处理方向学科带头人,研究方向为遥感图像智能解译、SAR图像目标检测与识别
通讯作者:冷祥光 luckight@163.com
计科峰 jikefeng@nudt.edu.cn
责任主编:张增辉 Corresponding Editor: ZHANG Zenghui中图分类号:TP753
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出版历程
收稿日期:2020-05-28
修回日期:2020-06-19
网络出版日期:2020-06-30
Statistical Modeling Methods of Single-channel Complex-valued SAR Images for Ship Detection
LENG Xiangguang,,JI Kefeng,,
XIONG Boli,
KUANG Gangyao
State Key Laboratory of Complex Electromagnetic Environment Effects on Electronics and Information System, College of Electronic Science and Technology, National University of Defense Technology, Changsha 410073, China
Funds:The National Natural Science Foundation of China (61601035, 61971426)
More Information
Corresponding author:LENG Xiangguang, luckight@163.com;JI Kefeng, jikefeng@nudt.edu.cn
摘要
摘要: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。
关键词:单通道SAR图像/
舰船目标检测/
复值信息/
统计建模
Abstract: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 complex-valued 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.
Key words:Single-channel SAR image/
Ship detection/
Complex-valued information/
Statistical modeling
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