{"title":"Two-dimensional Autofocus for SAR Filtered Backprojection Imagery","authors":"X. Mao, Tianyue Shi, Lan Ding","doi":"10.1109/APSAR46974.2019.9048354","DOIUrl":null,"url":null,"abstract":"Filtered backprojection (FBP) algorithm is a popular choice for nonlinear trajectory SAR image formation processing. However, how to efficiently autofocus the defocused FBP imagery is still a challenging problem. In this paper, a new interpretation of the FBP derivation is presented. Then, by incorporating the a priori knowledge on the 2-D phase error, an accurate and efficient 2-D autofocus approach is proposed. The new approach possesses much higher accuracy and efficiency than conventional blind methods. Experimental results clearly demonstrate the effectiveness and robustness of the proposed method.","PeriodicalId":377019,"journal":{"name":"2019 6th Asia-Pacific Conference on Synthetic Aperture Radar (APSAR)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 6th Asia-Pacific Conference on Synthetic Aperture Radar (APSAR)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/APSAR46974.2019.9048354","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Filtered backprojection (FBP) algorithm is a popular choice for nonlinear trajectory SAR image formation processing. However, how to efficiently autofocus the defocused FBP imagery is still a challenging problem. In this paper, a new interpretation of the FBP derivation is presented. Then, by incorporating the a priori knowledge on the 2-D phase error, an accurate and efficient 2-D autofocus approach is proposed. The new approach possesses much higher accuracy and efficiency than conventional blind methods. Experimental results clearly demonstrate the effectiveness and robustness of the proposed method.