Fisher分布下基于白化滤波的极化SAR图像CFAR检测方法

doi:10.3969/j.issn.0372-2112.2018.12.006

电子学报 ›› 2018, Vol. 46 ›› Issue (12): 2854-2861.DOI: 10.3969/j.issn.0372-2112.2018.12.006

Fisher分布下基于白化滤波的极化SAR图像CFAR检测方法

张嘉峰^1,2, 张鹏¹, 王明春¹, 刘涛¹

1. 海军工程大学电子工程学院, 湖北武汉 430030;
2. 中国人民解放军92118部队, 浙江舟山 316000

收稿日期:2017-08-21 修回日期:2018-05-23 出版日期:2018-12-25
- 作者简介:
- 张嘉峰 男,1993年生于河北邯郸.现为92118部队助理工程师.主要研究方向为雷达极化信息处理、新体制雷达技术及电子战建模与仿真.E-mail:751971863@qq.com;张鹏男,1996年生于安徽蒙城.现为海军工程大学硕士研究生.主要研究方向为雷达极化信息处理、新体制雷达技术及电子战建模与仿真.E-mail:zhangpeng212121@163.com;刘涛男,1978年生于山东新泰.现为海军工程大学教授、博士生导师.主要研究方向为雷达极化信息处理、新体制雷达技术及电子战建模与仿真.目前以第一作者在IEEE Transactions、Science in China、Chinese Physics B、《中国科学》、《自然科学进展》、《物理学报》、《电子学报》等期刊发表论文20余篇,其中SCI检索12篇.E-mail:liutao1018@sina.com
- 基金资助:
- 国家自然科学基金 (No.61372165，No.61771483）

A New CFAR Detection Method of Polarimetric SAR Imagery Based on Whitening Filter Under Fisher Distribution

ZHANG Jia-feng^1,2, ZHANG Peng¹, WANG Ming-chun¹, LIU Tao¹

1.School of Electronic Engineering, Naval University of Engineering, Wuhan, Hubei 430030, China;
2.No. 92118 Unit of PLA, Zhoushan, Zhejiang 316000, China

Received:2017-08-21 Revised:2018-05-23 Online:2018-12-25 Published:2018-12-25
- Supported by:
- National Natural Science Foundation of China (No.61372165, No.61771483)

摘要/Abstract

摘要： 在已有的极化合成孔径雷达（SAR）图像恒虚警（CFAR）检测方法中，存在着高分辨下杂波模型适用性差的难题.为此提出了一种Fisher分布下具有虚警概率解析表达形式的CFAR检测方法.首先，在乘积模型框架下，引入Fisher纹理变量，推导出了极化白化滤波（PWF）检测量的概率密度函数（PDF）.然后，对PDF积分得到了虚警概率关于检测门限的解析表达形式，并设计了相应的CFAR检测算法流程.最后，通过机载合成孔径雷达（AIRSAR）实测数据比较了新方法和双参数恒虚警（2P-CFAR）算法及已有的基于K分布、G₀分布、Wishart分布的CFAR检测方法的检测性能.结果表明新方法能有效检测出目标，且鲁棒性较强，相比于其他检测方法，品质因数平均高出32.66%.

关键词: 合成孔径雷达(SAR), 恒虚警(CFAR), 乘积模型, Fisher分布, 极化白化滤波, 虚警概率, 品质因数

Abstract: There is a problem of the poor applicability of clutter models under high resolution with the existing constant false alarm rate (CFAR) detection methods in polarimetric synthetic aperture radar (SAR) imageries. To solve the problem, a CFAR detection method with an analytical expression for the false alarm rate is proposed. Firstly, the probability density function (PDF) of the polarization whitening filter (PWF) metric is derived based on product model combining the hypothesis of the Fisher distribution texture. Secondly, the PDF of the PWF metric is integrated, and the analytical expression of the false alarm rate with respect to the detection threshold is obtained. The process of the proposed CFAR detection method is also designed. Finally, the CFAR detection performances of the proposed method are compared via airborne SAR (AIRSAR) real data with the existing detection methods, such as the two-parameter CFAR (2P-CFAR) detector and the detection methods based on K distribution, G₀ distribution and Wishart distribution. The results show that the proposed method can detect the targets effectively, and the robustness of the method is strong. Compared with other detection methods, the figure of merit (FoM) of the proposed method is on average higher than 32.66%.

Key words: synthetic aperture radar (SAR), constant false alarm rate (CFAR), product model, Fisher distribution, polarization whitening filter (PWF), false alarm rate, figure of merit

中图分类号:

TN95

张嘉峰, 张鹏, 王明春, 等. Fisher分布下基于白化滤波的极化SAR图像CFAR检测方法[J]. 电子学报, 2018, 46(12): 2854-2861.

ZHANG Jia-feng, ZHANG Peng, WANG Ming-chun, et al. A New CFAR Detection Method of Polarimetric SAR Imagery Based on Whitening Filter Under Fisher Distribution[J]. Acta Electronica Sinica, 2018, 46(12): 2854-2861.

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Fisher分布下基于白化滤波的极化SAR图像CFAR检测方法

A New CFAR Detection Method of Polarimetric SAR Imagery Based on Whitening Filter Under Fisher Distribution

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