{"title":"A novel parametric SAR autofocus method","authors":"Jia Xu, Yingning Peng, Liping Zhang, Yin-shen Lin, Xianggen Xia","doi":"10.1109/NRC.2004.1316394","DOIUrl":null,"url":null,"abstract":"In synthetic aperture radar (SAR), low scene-contrast may invalidate most of the existing autofocus methods, and the limited autofocus performance is also difficult to verify. Based on a parametric statistical signal model in the coherent processing interval (CPI) of SAR, a novel SAR autofocus method is developed and it is especially applicable to extremely low-contrast scenes. Furthermore, the limitation of CPI length and the Cramer-Rao low bound of the autofocus parameter estimation are all analytically obtained. Finally, real measurement data is also exploited to validate the proposed model and the new method.","PeriodicalId":268965,"journal":{"name":"Proceedings of the 2004 IEEE Radar Conference (IEEE Cat. No.04CH37509)","volume":"97 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2004-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 2004 IEEE Radar Conference (IEEE Cat. No.04CH37509)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/NRC.2004.1316394","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
In synthetic aperture radar (SAR), low scene-contrast may invalidate most of the existing autofocus methods, and the limited autofocus performance is also difficult to verify. Based on a parametric statistical signal model in the coherent processing interval (CPI) of SAR, a novel SAR autofocus method is developed and it is especially applicable to extremely low-contrast scenes. Furthermore, the limitation of CPI length and the Cramer-Rao low bound of the autofocus parameter estimation are all analytically obtained. Finally, real measurement data is also exploited to validate the proposed model and the new method.
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