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An Azimuth Ambiguity Suppression Method for SAR Based on Time-Frequency Joint Analysis.

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Title: An Azimuth Ambiguity Suppression Method for SAR Based on Time-Frequency Joint Analysis.
Authors: Zhou, Gangbing1 (AUTHOR), Yu, Ze1,2 (AUTHOR), Yao, Xianxun1 (AUTHOR) xianxun.yao@buaa.edu.cn, Yu, Jindong2 (AUTHOR)
Source: Remote Sensing. Jul2025, Vol. 17 Issue 13, p2327. 20p.
Subjects: Azimuth, Synthetic aperture radar, Time-frequency analysis, Signal processing, Image quality in imaging systems
Abstract: Azimuth ambiguity caused by spectral aliasing severely degrades the quality of Synthetic Aperture Radar (SAR) images. To suppress azimuth ambiguity while preserving image details as much as possible, this paper proposes an azimuth ambiguity suppression method for SAR based on time-frequency joint analysis. By exploiting the distribution differences of ambiguous signals across different sub-spectra, the method locates azimuth ambiguity in the time domain through multi-sub-spectrum change detection and fusion, followed by ambiguity suppression in the azimuth time-frequency domain. Experimental results demonstrate that the proposed method effectively suppresses azimuth ambiguity while maintaining superior performance in preserving genuine targets. [ABSTRACT FROM AUTHOR]
Copyright of Remote Sensing is the property of MDPI and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: An Azimuth Ambiguity Suppression Method for SAR Based on Time-Frequency Joint Analysis.
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  Data: <searchLink fieldCode="AR" term="%22Zhou%2C+Gangbing%22">Zhou, Gangbing</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Yu%2C+Ze%22">Yu, Ze</searchLink><relatesTo>1,2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Yao%2C+Xianxun%22">Yao, Xianxun</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> xianxun.yao@buaa.edu.cn</i><br /><searchLink fieldCode="AR" term="%22Yu%2C+Jindong%22">Yu, Jindong</searchLink><relatesTo>2</relatesTo> (AUTHOR)
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  Data: <searchLink fieldCode="JN" term="%22Remote+Sensing%22">Remote Sensing</searchLink>. Jul2025, Vol. 17 Issue 13, p2327. 20p.
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  Data: <searchLink fieldCode="DE" term="%22Azimuth%22">Azimuth</searchLink><br /><searchLink fieldCode="DE" term="%22Synthetic+aperture+radar%22">Synthetic aperture radar</searchLink><br /><searchLink fieldCode="DE" term="%22Time-frequency+analysis%22">Time-frequency analysis</searchLink><br /><searchLink fieldCode="DE" term="%22Signal+processing%22">Signal processing</searchLink><br /><searchLink fieldCode="DE" term="%22Image+quality+in+imaging+systems%22">Image quality in imaging systems</searchLink>
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  Label: Abstract
  Group: Ab
  Data: Azimuth ambiguity caused by spectral aliasing severely degrades the quality of Synthetic Aperture Radar (SAR) images. To suppress azimuth ambiguity while preserving image details as much as possible, this paper proposes an azimuth ambiguity suppression method for SAR based on time-frequency joint analysis. By exploiting the distribution differences of ambiguous signals across different sub-spectra, the method locates azimuth ambiguity in the time domain through multi-sub-spectrum change detection and fusion, followed by ambiguity suppression in the azimuth time-frequency domain. Experimental results demonstrate that the proposed method effectively suppresses azimuth ambiguity while maintaining superior performance in preserving genuine targets. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Remote Sensing is the property of MDPI and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Text: English
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      – SubjectFull: Time-frequency analysis
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              Text: Jul2025
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