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

ZHANG Jia-feng; ZHANG Peng; WANG Ming-chun; LIU Tao

doi:10.3969/j.issn.0372-2112.2018.12.006

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

更新时间：2025-07-16

- A New CFAR Detection Method of Polarimetric SAR Imagery Based on Whitening Filter Under Fisher Distribution
- Acta Electronica Sinica Vol. 46, Issue 12, Pages: 2854-2861(2018)
- 作者机构：
  
  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
  3. 海军工程大学电子工程学院,湖北,武汉,430030
  4. 中国人民解放军92118部队,浙江,舟山,316000
- 作者简介：
- 基金信息：
  
  National Natural Science Foundation of China (No.61372165, No.61771483)
- DOI：10.3969/j.issn.0372-2112.2018.12.006
  CLC： TN95
- Published Online：25 December 2018，
  
  Published：2018
- 稿件说明：
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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.
DOI：

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. DOI： 10.3969/j.issn.0372-2112.2018.12.006.

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、

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%.

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

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%.

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