Inverse synthetic aperture ladar imaging algorithm for space spinning targets
Due to the limitation of laser modulation technology, the azimuth Doppler ambiguity problem exists in the process of inverse synthetic aperture ladar (ISAL) imaging for spinning targets. The traditional azimuth imaging method will not be used to obtain a good two-dimensional image. Therefore, we con...
Ausführliche Beschreibung
Autor*in: |
Yakun Lv [verfasserIn] Yanhong Wu [verfasserIn] Hongyan Wang [verfasserIn] Lei Qiu [verfasserIn] |
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Format: |
E-Artikel |
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Sprache: |
Englisch |
Erschienen: |
2019 |
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Schlagwörter: |
inverse synthetic aperture ladar imaging azimuth doppler ambiguity problem traditional azimuth imaging method generalised autocorrelation method |
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Übergeordnetes Werk: |
In: The Journal of Engineering - Wiley, 2013, (2019) |
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Übergeordnetes Werk: |
year:2019 |
Links: |
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DOI / URN: |
10.1049/joe.2019.0574 |
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Katalog-ID: |
DOAJ053594312 |
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520 | |a Due to the limitation of laser modulation technology, the azimuth Doppler ambiguity problem exists in the process of inverse synthetic aperture ladar (ISAL) imaging for spinning targets. The traditional azimuth imaging method will not be used to obtain a good two-dimensional image. Therefore, we consider using the target's spinning information for imaging. The spatial geometric model of the spinning target ISAL imaging is established, and the characteristics of the echo signal are analysed. An ISAL imaging algorithm based on the backward projection transform is proposed. First, the spinning angular velocity of the target is obtained by the generalised autocorrelation method, and then the envelope and phase of the distance and the slow time domain are transformed into a backward projection to achieve coherent accumulation, and the two-dimensional high-resolution image of the spinning target is finally obtained. Due to the use of echo phase information, the sidelobe effect is low and the resolution is high. The simulation results show that the algorithm can still get well-focused images under low SNR and Doppler ambiguity. | ||
650 | 4 | |a synthetic aperture radar | |
650 | 4 | |a radar imaging | |
650 | 4 | |a optical radar | |
650 | 4 | |a echo | |
650 | 4 | |a image resolution | |
650 | 4 | |a doppler radar | |
650 | 4 | |a inverse synthetic aperture ladar imaging | |
650 | 4 | |a space spinning targets | |
650 | 4 | |a laser modulation technology | |
650 | 4 | |a azimuth doppler ambiguity problem | |
650 | 4 | |a traditional azimuth imaging method | |
650 | 4 | |a two-dimensional image | |
650 | 4 | |a spinning information | |
650 | 4 | |a spatial geometric model | |
650 | 4 | |a spinning target isal imaging | |
650 | 4 | |a isal imaging algorithm | |
650 | 4 | |a backward projection | |
650 | 4 | |a spinning angular velocity | |
650 | 4 | |a generalised autocorrelation method | |
650 | 4 | |a two-dimensional high-resolution image | |
650 | 4 | |a echo phase information | |
653 | 0 | |a Engineering (General). Civil engineering (General) | |
700 | 0 | |a Yanhong Wu |e verfasserin |4 aut | |
700 | 0 | |a Yanhong Wu |e verfasserin |4 aut | |
700 | 0 | |a Hongyan Wang |e verfasserin |4 aut | |
700 | 0 | |a Lei Qiu |e verfasserin |4 aut | |
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10.1049/joe.2019.0574 doi (DE-627)DOAJ053594312 (DE-599)DOAJ01e9740e00e846b38ba012098a07a20e DE-627 ger DE-627 rakwb eng TA1-2040 Yakun Lv verfasserin aut Inverse synthetic aperture ladar imaging algorithm for space spinning targets 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Due to the limitation of laser modulation technology, the azimuth Doppler ambiguity problem exists in the process of inverse synthetic aperture ladar (ISAL) imaging for spinning targets. The traditional azimuth imaging method will not be used to obtain a good two-dimensional image. Therefore, we consider using the target's spinning information for imaging. The spatial geometric model of the spinning target ISAL imaging is established, and the characteristics of the echo signal are analysed. An ISAL imaging algorithm based on the backward projection transform is proposed. First, the spinning angular velocity of the target is obtained by the generalised autocorrelation method, and then the envelope and phase of the distance and the slow time domain are transformed into a backward projection to achieve coherent accumulation, and the two-dimensional high-resolution image of the spinning target is finally obtained. Due to the use of echo phase information, the sidelobe effect is low and the resolution is high. The simulation results show that the algorithm can still get well-focused images under low SNR and Doppler ambiguity. synthetic aperture radar radar imaging optical radar echo image resolution doppler radar inverse synthetic aperture ladar imaging space spinning targets laser modulation technology azimuth doppler ambiguity problem traditional azimuth imaging method two-dimensional image spinning information spatial geometric model spinning target isal imaging isal imaging algorithm backward projection spinning angular velocity generalised autocorrelation method two-dimensional high-resolution image echo phase information Engineering (General). Civil engineering (General) Yanhong Wu verfasserin aut Yanhong Wu verfasserin aut Hongyan Wang verfasserin aut Lei Qiu verfasserin aut In The Journal of Engineering Wiley, 2013 (2019) (DE-627)75682270X (DE-600)2727074-9 20513305 nnns year:2019 https://doi.org/10.1049/joe.2019.0574 kostenfrei https://doaj.org/article/01e9740e00e846b38ba012098a07a20e kostenfrei https://digital-library.theiet.org/content/journals/10.1049/joe.2019.0574 kostenfrei https://doaj.org/toc/2051-3305 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ SSG-OLC-PHA GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 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_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 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_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 2019 |
spelling |
10.1049/joe.2019.0574 doi (DE-627)DOAJ053594312 (DE-599)DOAJ01e9740e00e846b38ba012098a07a20e DE-627 ger DE-627 rakwb eng TA1-2040 Yakun Lv verfasserin aut Inverse synthetic aperture ladar imaging algorithm for space spinning targets 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Due to the limitation of laser modulation technology, the azimuth Doppler ambiguity problem exists in the process of inverse synthetic aperture ladar (ISAL) imaging for spinning targets. The traditional azimuth imaging method will not be used to obtain a good two-dimensional image. Therefore, we consider using the target's spinning information for imaging. The spatial geometric model of the spinning target ISAL imaging is established, and the characteristics of the echo signal are analysed. An ISAL imaging algorithm based on the backward projection transform is proposed. First, the spinning angular velocity of the target is obtained by the generalised autocorrelation method, and then the envelope and phase of the distance and the slow time domain are transformed into a backward projection to achieve coherent accumulation, and the two-dimensional high-resolution image of the spinning target is finally obtained. Due to the use of echo phase information, the sidelobe effect is low and the resolution is high. The simulation results show that the algorithm can still get well-focused images under low SNR and Doppler ambiguity. synthetic aperture radar radar imaging optical radar echo image resolution doppler radar inverse synthetic aperture ladar imaging space spinning targets laser modulation technology azimuth doppler ambiguity problem traditional azimuth imaging method two-dimensional image spinning information spatial geometric model spinning target isal imaging isal imaging algorithm backward projection spinning angular velocity generalised autocorrelation method two-dimensional high-resolution image echo phase information Engineering (General). Civil engineering (General) Yanhong Wu verfasserin aut Yanhong Wu verfasserin aut Hongyan Wang verfasserin aut Lei Qiu verfasserin aut In The Journal of Engineering Wiley, 2013 (2019) (DE-627)75682270X (DE-600)2727074-9 20513305 nnns year:2019 https://doi.org/10.1049/joe.2019.0574 kostenfrei https://doaj.org/article/01e9740e00e846b38ba012098a07a20e kostenfrei https://digital-library.theiet.org/content/journals/10.1049/joe.2019.0574 kostenfrei https://doaj.org/toc/2051-3305 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ SSG-OLC-PHA GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 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_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 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_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 2019 |
allfields_unstemmed |
10.1049/joe.2019.0574 doi (DE-627)DOAJ053594312 (DE-599)DOAJ01e9740e00e846b38ba012098a07a20e DE-627 ger DE-627 rakwb eng TA1-2040 Yakun Lv verfasserin aut Inverse synthetic aperture ladar imaging algorithm for space spinning targets 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Due to the limitation of laser modulation technology, the azimuth Doppler ambiguity problem exists in the process of inverse synthetic aperture ladar (ISAL) imaging for spinning targets. The traditional azimuth imaging method will not be used to obtain a good two-dimensional image. Therefore, we consider using the target's spinning information for imaging. The spatial geometric model of the spinning target ISAL imaging is established, and the characteristics of the echo signal are analysed. An ISAL imaging algorithm based on the backward projection transform is proposed. First, the spinning angular velocity of the target is obtained by the generalised autocorrelation method, and then the envelope and phase of the distance and the slow time domain are transformed into a backward projection to achieve coherent accumulation, and the two-dimensional high-resolution image of the spinning target is finally obtained. Due to the use of echo phase information, the sidelobe effect is low and the resolution is high. The simulation results show that the algorithm can still get well-focused images under low SNR and Doppler ambiguity. synthetic aperture radar radar imaging optical radar echo image resolution doppler radar inverse synthetic aperture ladar imaging space spinning targets laser modulation technology azimuth doppler ambiguity problem traditional azimuth imaging method two-dimensional image spinning information spatial geometric model spinning target isal imaging isal imaging algorithm backward projection spinning angular velocity generalised autocorrelation method two-dimensional high-resolution image echo phase information Engineering (General). Civil engineering (General) Yanhong Wu verfasserin aut Yanhong Wu verfasserin aut Hongyan Wang verfasserin aut Lei Qiu verfasserin aut In The Journal of Engineering Wiley, 2013 (2019) (DE-627)75682270X (DE-600)2727074-9 20513305 nnns year:2019 https://doi.org/10.1049/joe.2019.0574 kostenfrei https://doaj.org/article/01e9740e00e846b38ba012098a07a20e kostenfrei https://digital-library.theiet.org/content/journals/10.1049/joe.2019.0574 kostenfrei https://doaj.org/toc/2051-3305 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ SSG-OLC-PHA GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 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_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 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_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 2019 |
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10.1049/joe.2019.0574 doi (DE-627)DOAJ053594312 (DE-599)DOAJ01e9740e00e846b38ba012098a07a20e DE-627 ger DE-627 rakwb eng TA1-2040 Yakun Lv verfasserin aut Inverse synthetic aperture ladar imaging algorithm for space spinning targets 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Due to the limitation of laser modulation technology, the azimuth Doppler ambiguity problem exists in the process of inverse synthetic aperture ladar (ISAL) imaging for spinning targets. The traditional azimuth imaging method will not be used to obtain a good two-dimensional image. Therefore, we consider using the target's spinning information for imaging. The spatial geometric model of the spinning target ISAL imaging is established, and the characteristics of the echo signal are analysed. An ISAL imaging algorithm based on the backward projection transform is proposed. First, the spinning angular velocity of the target is obtained by the generalised autocorrelation method, and then the envelope and phase of the distance and the slow time domain are transformed into a backward projection to achieve coherent accumulation, and the two-dimensional high-resolution image of the spinning target is finally obtained. Due to the use of echo phase information, the sidelobe effect is low and the resolution is high. The simulation results show that the algorithm can still get well-focused images under low SNR and Doppler ambiguity. synthetic aperture radar radar imaging optical radar echo image resolution doppler radar inverse synthetic aperture ladar imaging space spinning targets laser modulation technology azimuth doppler ambiguity problem traditional azimuth imaging method two-dimensional image spinning information spatial geometric model spinning target isal imaging isal imaging algorithm backward projection spinning angular velocity generalised autocorrelation method two-dimensional high-resolution image echo phase information Engineering (General). Civil engineering (General) Yanhong Wu verfasserin aut Yanhong Wu verfasserin aut Hongyan Wang verfasserin aut Lei Qiu verfasserin aut In The Journal of Engineering Wiley, 2013 (2019) (DE-627)75682270X (DE-600)2727074-9 20513305 nnns year:2019 https://doi.org/10.1049/joe.2019.0574 kostenfrei https://doaj.org/article/01e9740e00e846b38ba012098a07a20e kostenfrei https://digital-library.theiet.org/content/journals/10.1049/joe.2019.0574 kostenfrei https://doaj.org/toc/2051-3305 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ SSG-OLC-PHA GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 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_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 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_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 2019 |
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10.1049/joe.2019.0574 doi (DE-627)DOAJ053594312 (DE-599)DOAJ01e9740e00e846b38ba012098a07a20e DE-627 ger DE-627 rakwb eng TA1-2040 Yakun Lv verfasserin aut Inverse synthetic aperture ladar imaging algorithm for space spinning targets 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Due to the limitation of laser modulation technology, the azimuth Doppler ambiguity problem exists in the process of inverse synthetic aperture ladar (ISAL) imaging for spinning targets. The traditional azimuth imaging method will not be used to obtain a good two-dimensional image. Therefore, we consider using the target's spinning information for imaging. The spatial geometric model of the spinning target ISAL imaging is established, and the characteristics of the echo signal are analysed. An ISAL imaging algorithm based on the backward projection transform is proposed. First, the spinning angular velocity of the target is obtained by the generalised autocorrelation method, and then the envelope and phase of the distance and the slow time domain are transformed into a backward projection to achieve coherent accumulation, and the two-dimensional high-resolution image of the spinning target is finally obtained. Due to the use of echo phase information, the sidelobe effect is low and the resolution is high. The simulation results show that the algorithm can still get well-focused images under low SNR and Doppler ambiguity. synthetic aperture radar radar imaging optical radar echo image resolution doppler radar inverse synthetic aperture ladar imaging space spinning targets laser modulation technology azimuth doppler ambiguity problem traditional azimuth imaging method two-dimensional image spinning information spatial geometric model spinning target isal imaging isal imaging algorithm backward projection spinning angular velocity generalised autocorrelation method two-dimensional high-resolution image echo phase information Engineering (General). Civil engineering (General) Yanhong Wu verfasserin aut Yanhong Wu verfasserin aut Hongyan Wang verfasserin aut Lei Qiu verfasserin aut In The Journal of Engineering Wiley, 2013 (2019) (DE-627)75682270X (DE-600)2727074-9 20513305 nnns year:2019 https://doi.org/10.1049/joe.2019.0574 kostenfrei https://doaj.org/article/01e9740e00e846b38ba012098a07a20e kostenfrei https://digital-library.theiet.org/content/journals/10.1049/joe.2019.0574 kostenfrei https://doaj.org/toc/2051-3305 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ SSG-OLC-PHA GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 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_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 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_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 2019 |
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synthetic aperture radar radar imaging optical radar echo image resolution doppler radar inverse synthetic aperture ladar imaging space spinning targets laser modulation technology azimuth doppler ambiguity problem traditional azimuth imaging method two-dimensional image spinning information spatial geometric model spinning target isal imaging isal imaging algorithm backward projection spinning angular velocity generalised autocorrelation method two-dimensional high-resolution image echo phase information Engineering (General). Civil engineering (General) |
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Yakun Lv misc TA1-2040 misc synthetic aperture radar misc radar imaging misc optical radar misc echo misc image resolution misc doppler radar misc inverse synthetic aperture ladar imaging misc space spinning targets misc laser modulation technology misc azimuth doppler ambiguity problem misc traditional azimuth imaging method misc two-dimensional image misc spinning information misc spatial geometric model misc spinning target isal imaging misc isal imaging algorithm misc backward projection misc spinning angular velocity misc generalised autocorrelation method misc two-dimensional high-resolution image misc echo phase information misc Engineering (General). Civil engineering (General) Inverse synthetic aperture ladar imaging algorithm for space spinning targets |
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TA1-2040 Inverse synthetic aperture ladar imaging algorithm for space spinning targets synthetic aperture radar radar imaging optical radar echo image resolution doppler radar inverse synthetic aperture ladar imaging space spinning targets laser modulation technology azimuth doppler ambiguity problem traditional azimuth imaging method two-dimensional image spinning information spatial geometric model spinning target isal imaging isal imaging algorithm backward projection spinning angular velocity generalised autocorrelation method two-dimensional high-resolution image echo phase information |
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misc TA1-2040 misc synthetic aperture radar misc radar imaging misc optical radar misc echo misc image resolution misc doppler radar misc inverse synthetic aperture ladar imaging misc space spinning targets misc laser modulation technology misc azimuth doppler ambiguity problem misc traditional azimuth imaging method misc two-dimensional image misc spinning information misc spatial geometric model misc spinning target isal imaging misc isal imaging algorithm misc backward projection misc spinning angular velocity misc generalised autocorrelation method misc two-dimensional high-resolution image misc echo phase information misc Engineering (General). Civil engineering (General) |
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misc TA1-2040 misc synthetic aperture radar misc radar imaging misc optical radar misc echo misc image resolution misc doppler radar misc inverse synthetic aperture ladar imaging misc space spinning targets misc laser modulation technology misc azimuth doppler ambiguity problem misc traditional azimuth imaging method misc two-dimensional image misc spinning information misc spatial geometric model misc spinning target isal imaging misc isal imaging algorithm misc backward projection misc spinning angular velocity misc generalised autocorrelation method misc two-dimensional high-resolution image misc echo phase information misc Engineering (General). Civil engineering (General) |
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Inverse synthetic aperture ladar imaging algorithm for space spinning targets |
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inverse synthetic aperture ladar imaging algorithm for space spinning targets |
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TA1-2040 |
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Inverse synthetic aperture ladar imaging algorithm for space spinning targets |
abstract |
Due to the limitation of laser modulation technology, the azimuth Doppler ambiguity problem exists in the process of inverse synthetic aperture ladar (ISAL) imaging for spinning targets. The traditional azimuth imaging method will not be used to obtain a good two-dimensional image. Therefore, we consider using the target's spinning information for imaging. The spatial geometric model of the spinning target ISAL imaging is established, and the characteristics of the echo signal are analysed. An ISAL imaging algorithm based on the backward projection transform is proposed. First, the spinning angular velocity of the target is obtained by the generalised autocorrelation method, and then the envelope and phase of the distance and the slow time domain are transformed into a backward projection to achieve coherent accumulation, and the two-dimensional high-resolution image of the spinning target is finally obtained. Due to the use of echo phase information, the sidelobe effect is low and the resolution is high. The simulation results show that the algorithm can still get well-focused images under low SNR and Doppler ambiguity. |
abstractGer |
Due to the limitation of laser modulation technology, the azimuth Doppler ambiguity problem exists in the process of inverse synthetic aperture ladar (ISAL) imaging for spinning targets. The traditional azimuth imaging method will not be used to obtain a good two-dimensional image. Therefore, we consider using the target's spinning information for imaging. The spatial geometric model of the spinning target ISAL imaging is established, and the characteristics of the echo signal are analysed. An ISAL imaging algorithm based on the backward projection transform is proposed. First, the spinning angular velocity of the target is obtained by the generalised autocorrelation method, and then the envelope and phase of the distance and the slow time domain are transformed into a backward projection to achieve coherent accumulation, and the two-dimensional high-resolution image of the spinning target is finally obtained. Due to the use of echo phase information, the sidelobe effect is low and the resolution is high. The simulation results show that the algorithm can still get well-focused images under low SNR and Doppler ambiguity. |
abstract_unstemmed |
Due to the limitation of laser modulation technology, the azimuth Doppler ambiguity problem exists in the process of inverse synthetic aperture ladar (ISAL) imaging for spinning targets. The traditional azimuth imaging method will not be used to obtain a good two-dimensional image. Therefore, we consider using the target's spinning information for imaging. The spatial geometric model of the spinning target ISAL imaging is established, and the characteristics of the echo signal are analysed. An ISAL imaging algorithm based on the backward projection transform is proposed. First, the spinning angular velocity of the target is obtained by the generalised autocorrelation method, and then the envelope and phase of the distance and the slow time domain are transformed into a backward projection to achieve coherent accumulation, and the two-dimensional high-resolution image of the spinning target is finally obtained. Due to the use of echo phase information, the sidelobe effect is low and the resolution is high. The simulation results show that the algorithm can still get well-focused images under low SNR and Doppler ambiguity. |
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title_short |
Inverse synthetic aperture ladar imaging algorithm for space spinning targets |
url |
https://doi.org/10.1049/joe.2019.0574 https://doaj.org/article/01e9740e00e846b38ba012098a07a20e https://digital-library.theiet.org/content/journals/10.1049/joe.2019.0574 https://doaj.org/toc/2051-3305 |
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The traditional azimuth imaging method will not be used to obtain a good two-dimensional image. Therefore, we consider using the target's spinning information for imaging. The spatial geometric model of the spinning target ISAL imaging is established, and the characteristics of the echo signal are analysed. An ISAL imaging algorithm based on the backward projection transform is proposed. First, the spinning angular velocity of the target is obtained by the generalised autocorrelation method, and then the envelope and phase of the distance and the slow time domain are transformed into a backward projection to achieve coherent accumulation, and the two-dimensional high-resolution image of the spinning target is finally obtained. Due to the use of echo phase information, the sidelobe effect is low and the resolution is high. 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Civil engineering (General)</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Yanhong Wu</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Yanhong Wu</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Hongyan Wang</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Lei Qiu</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">In</subfield><subfield code="t">The Journal of Engineering</subfield><subfield code="d">Wiley, 2013</subfield><subfield code="g">(2019)</subfield><subfield code="w">(DE-627)75682270X</subfield><subfield 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