{"title":"一种基于压缩感知的圆形卷积成像算法","authors":"Shujie Mu","doi":"10.1109/ICOCN53177.2021.9563900","DOIUrl":null,"url":null,"abstract":"To solve the problem of low efficiency in wavenumber domain imaging of circular synthetic aperture radar (CSAR), a novel circular convolution algorithm based on compressed sensing is proposed, which can avoid the complex calculation in by compressed sensing algorithm and the simulation results show that the algorithm can effectively improve the imaging quality.","PeriodicalId":6756,"journal":{"name":"2021 19th International Conference on Optical Communications and Networks (ICOCN)","volume":"42 1","pages":"1-2"},"PeriodicalIF":0.0000,"publicationDate":"2021-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"A Novel Circular Convolution Imaging Algorithm Based on Compressed Sensing for CSAR\",\"authors\":\"Shujie Mu\",\"doi\":\"10.1109/ICOCN53177.2021.9563900\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"To solve the problem of low efficiency in wavenumber domain imaging of circular synthetic aperture radar (CSAR), a novel circular convolution algorithm based on compressed sensing is proposed, which can avoid the complex calculation in by compressed sensing algorithm and the simulation results show that the algorithm can effectively improve the imaging quality.\",\"PeriodicalId\":6756,\"journal\":{\"name\":\"2021 19th International Conference on Optical Communications and Networks (ICOCN)\",\"volume\":\"42 1\",\"pages\":\"1-2\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-08-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 19th International Conference on Optical Communications and Networks (ICOCN)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICOCN53177.2021.9563900\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 19th International Conference on Optical Communications and Networks (ICOCN)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICOCN53177.2021.9563900","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A Novel Circular Convolution Imaging Algorithm Based on Compressed Sensing for CSAR
To solve the problem of low efficiency in wavenumber domain imaging of circular synthetic aperture radar (CSAR), a novel circular convolution algorithm based on compressed sensing is proposed, which can avoid the complex calculation in by compressed sensing algorithm and the simulation results show that the algorithm can effectively improve the imaging quality.