电子学报2013，Vol.41Issue(3)：543-548,6.DOI:10.3969/j.issn.0372-2112.2013.03.021
基于压缩感知的多角度SAR特征提取
Multi-Aspect SAR Feature Extraction Based on Compressive Sensing
摘要
Abstract
In order to improve the precision and robustness of parameter estimation,the multi-aspect SAR data is applied to estimate model parameter of attributed scattering center. We consider the parameter estimation as a sparse signal reconstruction problem, and propose parameter-sequential algorithm to relieve the computational complexity. Two factors are studied. First, the aspect and frequency diversity can improve the performance of dictionary matrix.Second,in order to reduce the algorithm complexity, the parameter estimation procedure is realized sequentially. The initial imagery is reconstructed by dictionary matrix which is built up by the ideal point scattering model.The model order,location and type of scattering center are established primarily by energy segment of initial imagery. Then all parameters are estimated over again based on the dictionary matrix which is built up by the prior estimation. The feasibility and robustness of algorithm is validated by numeric simulation.关键词
多角度SAR/压缩感知/属性散射中心/特征提取Key words
multi-aspect SAR/compressive sensing/ attributed scattering center/feature extraction分类
信息技术与安全科学引用本文复制引用
周汉飞,李禹,粟毅..基于压缩感知的多角度SAR特征提取[J].电子学报,2013,41(3):543-548,6.基金项目
国家自然科学基金(No.60972120,No.61171135) （No.60972120,No.61171135）
