{"title":"基于小波包算法的压缩感知SAR成像方法","authors":"Shi Yan, Di-rong Chen","doi":"10.3724/SP.J.1300.2013.20068","DOIUrl":null,"url":null,"abstract":"Compressive sensing SAR imaging can significantly reduce the sampling rate and the amount of data required, but it is essential only in the case where the reflection coefficients of a SAR scene are sparse. This paper proposes a compressive sensing SAR imaging method based on wavelet packet sparse representation. The wavelet packet algorithm is used to choose the most sparse representation of the SAR scene by training the same type of SAR images. By solving for the minimum 1 l norm optimization, the SAR scene reflection coefficients can be reconstructed. Unambiguous SAR images can be produced with the proposed method, even with fewer samples. SAR data simulation experiments demonstrate the efficiency of the proposed method.","PeriodicalId":37701,"journal":{"name":"雷达学报","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2013-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A Compressive Sensing SAR Imaging Approach Based on Wavelet Package Algorithm\",\"authors\":\"Shi Yan, Di-rong Chen\",\"doi\":\"10.3724/SP.J.1300.2013.20068\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Compressive sensing SAR imaging can significantly reduce the sampling rate and the amount of data required, but it is essential only in the case where the reflection coefficients of a SAR scene are sparse. This paper proposes a compressive sensing SAR imaging method based on wavelet packet sparse representation. The wavelet packet algorithm is used to choose the most sparse representation of the SAR scene by training the same type of SAR images. By solving for the minimum 1 l norm optimization, the SAR scene reflection coefficients can be reconstructed. Unambiguous SAR images can be produced with the proposed method, even with fewer samples. SAR data simulation experiments demonstrate the efficiency of the proposed method.\",\"PeriodicalId\":37701,\"journal\":{\"name\":\"雷达学报\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-04-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"雷达学报\",\"FirstCategoryId\":\"1093\",\"ListUrlMain\":\"https://doi.org/10.3724/SP.J.1300.2013.20068\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"Physics and Astronomy\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"雷达学报","FirstCategoryId":"1093","ListUrlMain":"https://doi.org/10.3724/SP.J.1300.2013.20068","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"Physics and Astronomy","Score":null,"Total":0}
A Compressive Sensing SAR Imaging Approach Based on Wavelet Package Algorithm
Compressive sensing SAR imaging can significantly reduce the sampling rate and the amount of data required, but it is essential only in the case where the reflection coefficients of a SAR scene are sparse. This paper proposes a compressive sensing SAR imaging method based on wavelet packet sparse representation. The wavelet packet algorithm is used to choose the most sparse representation of the SAR scene by training the same type of SAR images. By solving for the minimum 1 l norm optimization, the SAR scene reflection coefficients can be reconstructed. Unambiguous SAR images can be produced with the proposed method, even with fewer samples. SAR data simulation experiments demonstrate the efficiency of the proposed method.