A Novel Scheme for Range Ambiguity Suppression of Spaceborne SAR Based on Underdetermined Blind Source Separation

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.

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Publication Details

Journal
IEEE Transactions on Geoscience and Remote Sensing
Published
2025-01-01
DOI
https://doi.org/10.1109/tgrs.2025.3556296
Citations
16
Primary Topic
Image and Signal Denoising Methods
Type
article
Field-Weighted Citation Impact
20.42
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article

A Novel Scheme for Range Ambiguity Suppression of Spaceborne SAR Based on Underdetermined Blind Source Separation

Tang Shu-he, Sheng Chang, Wei Wang, Heng Zhang et al.
16 citations
IEEE Transactions on Geoscience and Remote Sensing
Image and Signal Denoising Methods
20.42
article

A Novel Scheme for Range Ambiguity Suppression of Spaceborne SAR Based on Underdetermined Blind Source Separation

Tang Shu-he, Sheng Chang, Wei Wang, Heng Zhang, Dacheng Liu, Yunkai Deng
article en
16 citations

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.

IEEE Transactions on Geoscience and Remote SensingVol. 63
Chinese Academy of Sciences (CN), Aerospace Information Research Institute (CN)
Openalex Percentile: Top 1%
Image and Signal Denoising Methods
20.42
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A Novel Scheme for Range Ambiguity Suppression of Spaceborne SAR Based on Underdetermined Blind Source Separation — Tang Shu-he, Sheng Chang, et al. · IEEE Transactions on Geoscience and Remote Sensing (2025) | TGRS Research Map | TGRS