On the RFI Detection in Differential Interferometric Synthetic Aperture Radar
Abstract. Synthetic Aperture Radar (SAR) can image the ground with a wide area and high resolution at all times and in all weather and has become an important means of remote sensing. Differential interferometry SAR technology can obtain high-precision surface deformation information by processing more than two SAR images before and after deformation. In recent years, it has attracted widespread attention and research. However, due to the increasing number of ground electronic devices, ground radio frequency interference (RFI) has become one of the main problems in differential interferometry SAR processing, seriously affecting the performance of differential interferometry SAR imaging and differential interferometry surface deformation monitoring applications. In this paper, a clutter cancellation interference enhancement detection algorithm is proposed. By clutter suppression in the primary and secondary images, the interference-to-signal ratio is increased, which effectively improves the interference detection capabilities. The effectiveness of the algorithm in this paper is verified by the on-orbit measured data of the Lutan-1 satellites.
- Standort
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Deutsche Nationalbibliothek Frankfurt am Main
- Umfang
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Online-Ressource
- Sprache
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Englisch
- Erschienen in
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On the RFI Detection in Differential Interferometric Synthetic Aperture Radar ; volume:XLVIII-1-2024 ; year:2024 ; pages:425-430 ; extent:6
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences ; XLVIII-1-2024 (2024), 425-430 (gesamt 6)
- Klassifikation
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Elektrotechnik, Elektronik
- Urheber
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Liu, Yanyang
Tao, Mingliang
Li, Jieshuang
Li, Tao
Chen, Junli
- DOI
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10.5194/isprs-archives-XLVIII-1-2024-425-2024
- URN
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urn:nbn:de:101:1-2405160445585.619963841003
- Rechteinformation
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Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Letzte Aktualisierung
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14.08.2025, 10:57 MESZ
Datenpartner
Deutsche Nationalbibliothek. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Beteiligte
- Liu, Yanyang
- Tao, Mingliang
- Li, Jieshuang
- Li, Tao
- Chen, Junli
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