Drone With Integrated Moving Baseline System and Time-Domain Autofocus Algorithm for High-Resolution SAR Images

The demand for drone-based synthetic aperture radar (SAR) systems is growing, especially for applications in cases where satellites or airborne systems are not sufficiently flexible. However, the combination of a long operating range and high spatial resolution causes the atmosphere to pose challeng...
Ausführliche Beschreibung

Gespeichert in:

Autor*in:	Peter Brotzer [verfasserIn] Daniel Henke [verfasserIn] David Small [verfasserIn] Emiliano Casalini [verfasserIn] Sebastien Guillaume [verfasserIn] Rolf Vogt [verfasserIn] Elias Mendez Dominguez [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2024

Schlagwörter:	Autofocus drone frequency-modulated continuous wave (FMCW) synthetic aperture radar (SAR) uncrewed aerial vehicle

Übergeordnetes Werk:	In: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing - IEEE, 2020, 17(2024), Seite 2360-2371
Übergeordnetes Werk:	volume:17 ; year:2024 ; pages:2360-2371

Links:	Link aufrufen Link aufrufen Link aufrufen Journal toc

DOI / URN:	10.1109/JSTARS.2023.3345954

Katalog-ID:	DOAJ097855405

Internformat


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520			\|a The demand for drone-based synthetic aperture radar (SAR) systems is growing, especially for applications in cases where satellites or airborne systems are not sufficiently flexible. However, the combination of a long operating range and high spatial resolution causes the atmosphere to pose challenges for these systems. In this article, we present our <inline-formula<<tex-math notation="LaTeX"<$K$</tex-math<</inline-formula<-band drone system that has a long range sensibility through modification to a commercially available radar. In addition, a moving baseline configuration has been integrated to ensure accurate attitude data, especially the heading. The desired spatial resolution is achieved by our proposed autofocus algorithm based on image sharpness. It is designed to also work in challenging cases of nonlinear flight paths and can be integrated into a processing framework based on back-projection. Several experiments were conducted to demonstrate the drone system's capabilities. These included a comparison with an established airborne radar: MIRANDA35. The obtained results demonstrate the ability of the drone SAR system to map wide areas at high spatial resolution.
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650		4	\|a synthetic aperture radar (SAR)
650		4	\|a uncrewed aerial vehicle
653		0	\|a Ocean engineering
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700	0		\|a Elias Mendez Dominguez \|e verfasserin \|4 aut
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spelling	10.1109/JSTARS.2023.3345954 doi (DE-627)DOAJ097855405 (DE-599)DOAJb164d5cc6e2148109babdb7750d59c56 DE-627 ger DE-627 rakwb eng TC1501-1800 QC801-809 Peter Brotzer verfasserin aut Drone With Integrated Moving Baseline System and Time-Domain Autofocus Algorithm for High-Resolution SAR Images 2024 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier The demand for drone-based synthetic aperture radar (SAR) systems is growing, especially for applications in cases where satellites or airborne systems are not sufficiently flexible. However, the combination of a long operating range and high spatial resolution causes the atmosphere to pose challenges for these systems. In this article, we present our <inline-formula<<tex-math notation="LaTeX"<$K$</tex-math<</inline-formula<-band drone system that has a long range sensibility through modification to a commercially available radar. In addition, a moving baseline configuration has been integrated to ensure accurate attitude data, especially the heading. The desired spatial resolution is achieved by our proposed autofocus algorithm based on image sharpness. It is designed to also work in challenging cases of nonlinear flight paths and can be integrated into a processing framework based on back-projection. Several experiments were conducted to demonstrate the drone system's capabilities. These included a comparison with an established airborne radar: MIRANDA35. The obtained results demonstrate the ability of the drone SAR system to map wide areas at high spatial resolution. Autofocus drone frequency-modulated continuous wave (FMCW) <named-content xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:ali="http://www.niso.org/schemas/ali/1.0/" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" content-type="math" xlink:type="simple"< <inline-formula< <tex-math notation="LaTeX"<$K$</tex-math< </inline-formula< </named-content<-band synthetic aperture radar (SAR) uncrewed aerial vehicle Ocean engineering Geophysics. Cosmic physics Daniel Henke verfasserin aut David Small verfasserin aut Emiliano Casalini verfasserin aut Sebastien Guillaume verfasserin aut Rolf Vogt verfasserin aut Elias Mendez Dominguez verfasserin aut In IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing IEEE, 2020 17(2024), Seite 2360-2371 (DE-627)581732634 (DE-600)2457423-5 21511535 nnns volume:17 year:2024 pages:2360-2371 https://doi.org/10.1109/JSTARS.2023.3345954 kostenfrei https://doaj.org/article/b164d5cc6e2148109babdb7750d59c56 kostenfrei https://ieeexplore.ieee.org/document/10373018/ kostenfrei https://doaj.org/toc/2151-1535 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_187 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2048 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2068 GBV_ILN_2106 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2129 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2472 GBV_ILN_2522 GBV_ILN_2965 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 17 2024 2360-2371
allfields_unstemmed	10.1109/JSTARS.2023.3345954 doi (DE-627)DOAJ097855405 (DE-599)DOAJb164d5cc6e2148109babdb7750d59c56 DE-627 ger DE-627 rakwb eng TC1501-1800 QC801-809 Peter Brotzer verfasserin aut Drone With Integrated Moving Baseline System and Time-Domain Autofocus Algorithm for High-Resolution SAR Images 2024 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier The demand for drone-based synthetic aperture radar (SAR) systems is growing, especially for applications in cases where satellites or airborne systems are not sufficiently flexible. However, the combination of a long operating range and high spatial resolution causes the atmosphere to pose challenges for these systems. In this article, we present our <inline-formula<<tex-math notation="LaTeX"<$K$</tex-math<</inline-formula<-band drone system that has a long range sensibility through modification to a commercially available radar. In addition, a moving baseline configuration has been integrated to ensure accurate attitude data, especially the heading. The desired spatial resolution is achieved by our proposed autofocus algorithm based on image sharpness. It is designed to also work in challenging cases of nonlinear flight paths and can be integrated into a processing framework based on back-projection. Several experiments were conducted to demonstrate the drone system's capabilities. These included a comparison with an established airborne radar: MIRANDA35. The obtained results demonstrate the ability of the drone SAR system to map wide areas at high spatial resolution. Autofocus drone frequency-modulated continuous wave (FMCW) <named-content xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:ali="http://www.niso.org/schemas/ali/1.0/" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" content-type="math" xlink:type="simple"< <inline-formula< <tex-math notation="LaTeX"<$K$</tex-math< </inline-formula< </named-content<-band synthetic aperture radar (SAR) uncrewed aerial vehicle Ocean engineering Geophysics. Cosmic physics Daniel Henke verfasserin aut David Small verfasserin aut Emiliano Casalini verfasserin aut Sebastien Guillaume verfasserin aut Rolf Vogt verfasserin aut Elias Mendez Dominguez verfasserin aut In IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing IEEE, 2020 17(2024), Seite 2360-2371 (DE-627)581732634 (DE-600)2457423-5 21511535 nnns volume:17 year:2024 pages:2360-2371 https://doi.org/10.1109/JSTARS.2023.3345954 kostenfrei https://doaj.org/article/b164d5cc6e2148109babdb7750d59c56 kostenfrei https://ieeexplore.ieee.org/document/10373018/ kostenfrei https://doaj.org/toc/2151-1535 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_187 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2048 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2068 GBV_ILN_2106 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2129 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2472 GBV_ILN_2522 GBV_ILN_2965 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 17 2024 2360-2371
allfieldsGer	10.1109/JSTARS.2023.3345954 doi (DE-627)DOAJ097855405 (DE-599)DOAJb164d5cc6e2148109babdb7750d59c56 DE-627 ger DE-627 rakwb eng TC1501-1800 QC801-809 Peter Brotzer verfasserin aut Drone With Integrated Moving Baseline System and Time-Domain Autofocus Algorithm for High-Resolution SAR Images 2024 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier The demand for drone-based synthetic aperture radar (SAR) systems is growing, especially for applications in cases where satellites or airborne systems are not sufficiently flexible. However, the combination of a long operating range and high spatial resolution causes the atmosphere to pose challenges for these systems. In this article, we present our <inline-formula<<tex-math notation="LaTeX"<$K$</tex-math<</inline-formula<-band drone system that has a long range sensibility through modification to a commercially available radar. In addition, a moving baseline configuration has been integrated to ensure accurate attitude data, especially the heading. The desired spatial resolution is achieved by our proposed autofocus algorithm based on image sharpness. It is designed to also work in challenging cases of nonlinear flight paths and can be integrated into a processing framework based on back-projection. Several experiments were conducted to demonstrate the drone system's capabilities. These included a comparison with an established airborne radar: MIRANDA35. The obtained results demonstrate the ability of the drone SAR system to map wide areas at high spatial resolution. Autofocus drone frequency-modulated continuous wave (FMCW) <named-content xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:ali="http://www.niso.org/schemas/ali/1.0/" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" content-type="math" xlink:type="simple"< <inline-formula< <tex-math notation="LaTeX"<$K$</tex-math< </inline-formula< </named-content<-band synthetic aperture radar (SAR) uncrewed aerial vehicle Ocean engineering Geophysics. Cosmic physics Daniel Henke verfasserin aut David Small verfasserin aut Emiliano Casalini verfasserin aut Sebastien Guillaume verfasserin aut Rolf Vogt verfasserin aut Elias Mendez Dominguez verfasserin aut In IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing IEEE, 2020 17(2024), Seite 2360-2371 (DE-627)581732634 (DE-600)2457423-5 21511535 nnns volume:17 year:2024 pages:2360-2371 https://doi.org/10.1109/JSTARS.2023.3345954 kostenfrei https://doaj.org/article/b164d5cc6e2148109babdb7750d59c56 kostenfrei https://ieeexplore.ieee.org/document/10373018/ kostenfrei https://doaj.org/toc/2151-1535 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_187 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2048 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2068 GBV_ILN_2106 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2129 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2472 GBV_ILN_2522 GBV_ILN_2965 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 17 2024 2360-2371
allfieldsSound	10.1109/JSTARS.2023.3345954 doi (DE-627)DOAJ097855405 (DE-599)DOAJb164d5cc6e2148109babdb7750d59c56 DE-627 ger DE-627 rakwb eng TC1501-1800 QC801-809 Peter Brotzer verfasserin aut Drone With Integrated Moving Baseline System and Time-Domain Autofocus Algorithm for High-Resolution SAR Images 2024 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier The demand for drone-based synthetic aperture radar (SAR) systems is growing, especially for applications in cases where satellites or airborne systems are not sufficiently flexible. However, the combination of a long operating range and high spatial resolution causes the atmosphere to pose challenges for these systems. In this article, we present our <inline-formula<<tex-math notation="LaTeX"<$K$</tex-math<</inline-formula<-band drone system that has a long range sensibility through modification to a commercially available radar. In addition, a moving baseline configuration has been integrated to ensure accurate attitude data, especially the heading. The desired spatial resolution is achieved by our proposed autofocus algorithm based on image sharpness. It is designed to also work in challenging cases of nonlinear flight paths and can be integrated into a processing framework based on back-projection. Several experiments were conducted to demonstrate the drone system's capabilities. These included a comparison with an established airborne radar: MIRANDA35. The obtained results demonstrate the ability of the drone SAR system to map wide areas at high spatial resolution. Autofocus drone frequency-modulated continuous wave (FMCW) <named-content xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:ali="http://www.niso.org/schemas/ali/1.0/" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" content-type="math" xlink:type="simple"< <inline-formula< <tex-math notation="LaTeX"<$K$</tex-math< </inline-formula< </named-content<-band synthetic aperture radar (SAR) uncrewed aerial vehicle Ocean engineering Geophysics. Cosmic physics Daniel Henke verfasserin aut David Small verfasserin aut Emiliano Casalini verfasserin aut Sebastien Guillaume verfasserin aut Rolf Vogt verfasserin aut Elias Mendez Dominguez verfasserin aut In IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing IEEE, 2020 17(2024), Seite 2360-2371 (DE-627)581732634 (DE-600)2457423-5 21511535 nnns volume:17 year:2024 pages:2360-2371 https://doi.org/10.1109/JSTARS.2023.3345954 kostenfrei https://doaj.org/article/b164d5cc6e2148109babdb7750d59c56 kostenfrei https://ieeexplore.ieee.org/document/10373018/ kostenfrei https://doaj.org/toc/2151-1535 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_187 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2048 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2068 GBV_ILN_2106 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2129 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2472 GBV_ILN_2522 GBV_ILN_2965 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 17 2024 2360-2371
language	English
source	In IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 17(2024), Seite 2360-2371 volume:17 year:2024 pages:2360-2371
sourceStr	In IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 17(2024), Seite 2360-2371 volume:17 year:2024 pages:2360-2371
format_phy_str_mv	Article
institution	findex.gbv.de
topic_facet	Autofocus drone frequency-modulated continuous wave (FMCW) <named-content xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:ali="http://www.niso.org/schemas/ali/1.0/" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" content-type="math" xlink:type="simple"< <inline-formula< <tex-math notation="LaTeX"<$K$</tex-math< </inline-formula< </named-content<-band synthetic aperture radar (SAR) uncrewed aerial vehicle Ocean engineering Geophysics. Cosmic physics
isfreeaccess_bool	true
container_title	IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
authorswithroles_txt_mv	Peter Brotzer @@aut@@ Daniel Henke @@aut@@ David Small @@aut@@ Emiliano Casalini @@aut@@ Sebastien Guillaume @@aut@@ Rolf Vogt @@aut@@ Elias Mendez Dominguez @@aut@@
publishDateDaySort_date	2024-01-01T00:00:00Z
hierarchy_top_id	581732634
id	DOAJ097855405
language_de	englisch
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callnumber-first	T - Technology
author	Peter Brotzer
spellingShingle	Peter Brotzer misc TC1501-1800 misc QC801-809 misc Autofocus misc drone misc frequency-modulated continuous wave (FMCW) misc <named-content xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:ali="http://www.niso.org/schemas/ali/1.0/" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" content-type="math" xlink:type="simple"< <inline-formula< <tex-math notation="LaTeX"<$K$</tex-math< </inline-formula< </named-content<-band misc synthetic aperture radar (SAR) misc uncrewed aerial vehicle misc Ocean engineering misc Geophysics. Cosmic physics Drone With Integrated Moving Baseline System and Time-Domain Autofocus Algorithm for High-Resolution SAR Images
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topic_title	TC1501-1800 QC801-809 Drone With Integrated Moving Baseline System and Time-Domain Autofocus Algorithm for High-Resolution SAR Images Autofocus drone frequency-modulated continuous wave (FMCW) <named-content xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:ali="http://www.niso.org/schemas/ali/1.0/" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" content-type="math" xlink:type="simple"< <inline-formula< <tex-math notation="LaTeX"<$K$</tex-math< </inline-formula< </named-content<-band synthetic aperture radar (SAR) uncrewed aerial vehicle
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title	Drone With Integrated Moving Baseline System and Time-Domain Autofocus Algorithm for High-Resolution SAR Images
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title_full	Drone With Integrated Moving Baseline System and Time-Domain Autofocus Algorithm for High-Resolution SAR Images
author_sort	Peter Brotzer
journal	IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
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author_browse	Peter Brotzer Daniel Henke David Small Emiliano Casalini Sebastien Guillaume Rolf Vogt Elias Mendez Dominguez
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title_sort	drone with integrated moving baseline system and time-domain autofocus algorithm for high-resolution sar images
callnumber	TC1501-1800
title_auth	Drone With Integrated Moving Baseline System and Time-Domain Autofocus Algorithm for High-Resolution SAR Images
abstract	The demand for drone-based synthetic aperture radar (SAR) systems is growing, especially for applications in cases where satellites or airborne systems are not sufficiently flexible. However, the combination of a long operating range and high spatial resolution causes the atmosphere to pose challenges for these systems. In this article, we present our <inline-formula<<tex-math notation="LaTeX"<$K$</tex-math<</inline-formula<-band drone system that has a long range sensibility through modification to a commercially available radar. In addition, a moving baseline configuration has been integrated to ensure accurate attitude data, especially the heading. The desired spatial resolution is achieved by our proposed autofocus algorithm based on image sharpness. It is designed to also work in challenging cases of nonlinear flight paths and can be integrated into a processing framework based on back-projection. Several experiments were conducted to demonstrate the drone system's capabilities. These included a comparison with an established airborne radar: MIRANDA35. The obtained results demonstrate the ability of the drone SAR system to map wide areas at high spatial resolution.
abstractGer	The demand for drone-based synthetic aperture radar (SAR) systems is growing, especially for applications in cases where satellites or airborne systems are not sufficiently flexible. However, the combination of a long operating range and high spatial resolution causes the atmosphere to pose challenges for these systems. In this article, we present our <inline-formula<<tex-math notation="LaTeX"<$K$</tex-math<</inline-formula<-band drone system that has a long range sensibility through modification to a commercially available radar. In addition, a moving baseline configuration has been integrated to ensure accurate attitude data, especially the heading. The desired spatial resolution is achieved by our proposed autofocus algorithm based on image sharpness. It is designed to also work in challenging cases of nonlinear flight paths and can be integrated into a processing framework based on back-projection. Several experiments were conducted to demonstrate the drone system's capabilities. These included a comparison with an established airborne radar: MIRANDA35. The obtained results demonstrate the ability of the drone SAR system to map wide areas at high spatial resolution.
abstract_unstemmed	The demand for drone-based synthetic aperture radar (SAR) systems is growing, especially for applications in cases where satellites or airborne systems are not sufficiently flexible. However, the combination of a long operating range and high spatial resolution causes the atmosphere to pose challenges for these systems. In this article, we present our <inline-formula<<tex-math notation="LaTeX"<$K$</tex-math<</inline-formula<-band drone system that has a long range sensibility through modification to a commercially available radar. In addition, a moving baseline configuration has been integrated to ensure accurate attitude data, especially the heading. The desired spatial resolution is achieved by our proposed autofocus algorithm based on image sharpness. It is designed to also work in challenging cases of nonlinear flight paths and can be integrated into a processing framework based on back-projection. Several experiments were conducted to demonstrate the drone system's capabilities. These included a comparison with an established airborne radar: MIRANDA35. The obtained results demonstrate the ability of the drone SAR system to map wide areas at high spatial resolution.
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title_short	Drone With Integrated Moving Baseline System and Time-Domain Autofocus Algorithm for High-Resolution SAR Images
url	https://doi.org/10.1109/JSTARS.2023.3345954 https://doaj.org/article/b164d5cc6e2148109babdb7750d59c56 https://ieeexplore.ieee.org/document/10373018/ https://doaj.org/toc/2151-1535
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up_date	2024-07-03T14:09:28.131Z
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Drone With Integrated Moving Baseline System and Time-Domain Autofocus Algorithm for High-Resolution SAR Images

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