红外与毫米波学报2024，Vol.43Issue(4)：572-581,10.DOI:10.11972/j.issn.1001-9014.2024.04.018
基于相干矩阵特征空间的改进PolSAR数据多元散射能量分解方法
Modified multiple-component scattering power decomposition for PolSAR data based on eigenspace of coherency matrix
摘要
Abstract
A modified multiple-component scattering power decomposition for analyzing polarimetric synthetic aperture radar(PolSAR)data is proposed.The modified decomposition involves two distinct steps.Firstly,ei-genvectors of the coherency matrix are used to modify the scattering models.Secondly,the entropy and anisotro-py of targets are used to improve the volume scattering power.With the guarantee of high double-bounce scatter-ing power in the urban areas,the proposed algorithm effectively improves the volume scattering power of vegeta-tion areas.The efficacy of the modified multiple-component scattering power decomposition is validated using ac-tual AIRSAR PolSAR data.The scattering power obtained through decomposing the original coherency matrix and the coherency matrix after orientation angle compensation is compared with three algorithms.Results from the experiment demonstrate that the proposed decomposition yields more effective scattering power for different PolSAR data sets.关键词
极化SAR数据/模型分解/特征值分解/散射能量Key words
PolSAR data/model-based decomposition/eigenvalue decomposition/scattering power分类
信息技术与安全科学引用本文复制引用
张爽,王璐,王文卿..基于相干矩阵特征空间的改进PolSAR数据多元散射能量分解方法[J].红外与毫米波学报,2024,43(4):572-581,10.基金项目
Supported by the National Natural Science Foundation of China(62376214),the Natural Science Basic Research Program of Shaanxi(2023-JC-YB-533),and Foundation of Ministry of Education Key Lab.of Cognitive Radio and Information Processing(Guilin University of Electronic Tech-nology)(CRKL200203) （62376214）
