{"title":"通过傅立叶系数的距离-多普勒处理:到达亚奈奎斯特SAR的路径","authors":"Kfir Aberman, Yonina C. Eldar","doi":"10.1109/RADAR.2016.7485295","DOIUrl":null,"url":null,"abstract":"The increasing demand for wide swath, high-resolution, Synthetic Aperture Radar (SAR) images, requires high sampling rates which are difficult to attain in practice. Consequently, sampling rate reduction is of high practical value in radar imaging. In this paper, we introduce a new algorithm, equivalent to the well-known Range-Doppler method, to process SAR data using the Fourier coefficients of the raw signals. We then demonstrate how to exploit the new algorithm features, particularly, the relationship between the processed signals before and after Range Cells Migration Correction (RCMC), to reduce sampling rate at the acquisition stage and process the signals effectively at sub-Nyquist rates. Beyond sampling rate reduction, the proposed fast recovery algorithm forms a new CS-SAR imaging method that can be applied to high-quality and high-resolution real SAR imaging data acquired at sub-Nyquist rates. The performance of the algorithms is assessed using simulated data sets.","PeriodicalId":185932,"journal":{"name":"2016 IEEE Radar Conference (RadarConf)","volume":" 4","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-05-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Range-Doppler processing via fourier coefficients: The path to a sub-Nyquist SAR\",\"authors\":\"Kfir Aberman, Yonina C. Eldar\",\"doi\":\"10.1109/RADAR.2016.7485295\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The increasing demand for wide swath, high-resolution, Synthetic Aperture Radar (SAR) images, requires high sampling rates which are difficult to attain in practice. Consequently, sampling rate reduction is of high practical value in radar imaging. In this paper, we introduce a new algorithm, equivalent to the well-known Range-Doppler method, to process SAR data using the Fourier coefficients of the raw signals. We then demonstrate how to exploit the new algorithm features, particularly, the relationship between the processed signals before and after Range Cells Migration Correction (RCMC), to reduce sampling rate at the acquisition stage and process the signals effectively at sub-Nyquist rates. Beyond sampling rate reduction, the proposed fast recovery algorithm forms a new CS-SAR imaging method that can be applied to high-quality and high-resolution real SAR imaging data acquired at sub-Nyquist rates. The performance of the algorithms is assessed using simulated data sets.\",\"PeriodicalId\":185932,\"journal\":{\"name\":\"2016 IEEE Radar Conference (RadarConf)\",\"volume\":\" 4\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-05-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 IEEE Radar Conference (RadarConf)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/RADAR.2016.7485295\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 IEEE Radar Conference (RadarConf)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/RADAR.2016.7485295","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Range-Doppler processing via fourier coefficients: The path to a sub-Nyquist SAR
The increasing demand for wide swath, high-resolution, Synthetic Aperture Radar (SAR) images, requires high sampling rates which are difficult to attain in practice. Consequently, sampling rate reduction is of high practical value in radar imaging. In this paper, we introduce a new algorithm, equivalent to the well-known Range-Doppler method, to process SAR data using the Fourier coefficients of the raw signals. We then demonstrate how to exploit the new algorithm features, particularly, the relationship between the processed signals before and after Range Cells Migration Correction (RCMC), to reduce sampling rate at the acquisition stage and process the signals effectively at sub-Nyquist rates. Beyond sampling rate reduction, the proposed fast recovery algorithm forms a new CS-SAR imaging method that can be applied to high-quality and high-resolution real SAR imaging data acquired at sub-Nyquist rates. The performance of the algorithms is assessed using simulated data sets.