Yunkai Deng;Shuhe Tang;Sheng Chang;Heng Zhang;Dacheng Liu;Wei Wang
{"title":"A Novel Scheme for Range Ambiguity Suppression of Spaceborne SAR Based on Underdetermined Blind Source Separation","authors":"Yunkai Deng;Shuhe Tang;Sheng Chang;Heng Zhang;Dacheng Liu;Wei Wang","doi":"10.1109/TGRS.2025.3556296","DOIUrl":null,"url":null,"abstract":"Range ambiguity is a critical factor degrading the high-resolution and wide-swath (HRWS) imaging performance of spaceborne synthetic aperture radar (SAR), arising primarily from the antenna sidelobe characteristics. Recently, blind source separation (BSS) methods have shown promise in mitigating range ambiguity. However, existing studies have mainly focused on the determined scenario. In contrast, underdetermined cases are often more prevalent in practical settings. To address this gap, this article proposes a novel range ambiguity suppression scheme specifically designed for the underdetermined BSS (UBSS) scenario. Point and distributed targets simulation based on Sentinel-1 system is conducted to verify its effectiveness. The results indicate that for the point target imaging performance of two channels, peak sidelobe ratio (PSLR) and integrated sidelobe ratio (ISLR) are improved by an average of 6.62 and 9.47 dB, respectively. In the distributed target case, the separation and recovery of the echo signals in the target region achieve an average similarity (pixel, structure, and cosine metrics) exceeding 94.27%, and demonstrate robustness at signal-to-noise ratios above 25 dB. These findings provide insight into the feasibility of UBSS-based strategies for range ambiguity suppression and offer valuable reference points for future investigations involving single-channel implementations.","PeriodicalId":13213,"journal":{"name":"IEEE Transactions on Geoscience and Remote Sensing","volume":"63 ","pages":"1-15"},"PeriodicalIF":7.5000,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Transactions on Geoscience and Remote Sensing","FirstCategoryId":"5","ListUrlMain":"https://ieeexplore.ieee.org/document/10945961/","RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
引用次数: 0
Abstract
Range ambiguity is a critical factor degrading the high-resolution and wide-swath (HRWS) imaging performance of spaceborne synthetic aperture radar (SAR), arising primarily from the antenna sidelobe characteristics. Recently, blind source separation (BSS) methods have shown promise in mitigating range ambiguity. However, existing studies have mainly focused on the determined scenario. In contrast, underdetermined cases are often more prevalent in practical settings. To address this gap, this article proposes a novel range ambiguity suppression scheme specifically designed for the underdetermined BSS (UBSS) scenario. Point and distributed targets simulation based on Sentinel-1 system is conducted to verify its effectiveness. The results indicate that for the point target imaging performance of two channels, peak sidelobe ratio (PSLR) and integrated sidelobe ratio (ISLR) are improved by an average of 6.62 and 9.47 dB, respectively. In the distributed target case, the separation and recovery of the echo signals in the target region achieve an average similarity (pixel, structure, and cosine metrics) exceeding 94.27%, and demonstrate robustness at signal-to-noise ratios above 25 dB. These findings provide insight into the feasibility of UBSS-based strategies for range ambiguity suppression and offer valuable reference points for future investigations involving single-channel implementations.
期刊介绍:
IEEE Transactions on Geoscience and Remote Sensing (TGRS) is a monthly publication that focuses on the theory, concepts, and techniques of science and engineering as applied to sensing the land, oceans, atmosphere, and space; and the processing, interpretation, and dissemination of this information.