A Phase-Derived Velocity Measurement Method Based on the Generalized Radon-Fourier Transform With a Low SNR
The phase-derived velocity measurement (PDVM) technique can achieve a high measurement accuracy at the phase level and thus has great application prospects in the field of micromotion feature extraction and target recognition. To achieve a PDVM with a low signal-to-noise ratio (SNR), a PDVM method b...
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| Veröffentlicht in: | IEEE transactions on geoscience and remote sensing 2022, Vol.60, p.1-16 |
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| creator | Li, Wenji Fan, Huayu Ren, Lixiang Sha, Minghui Mao, Erke Liu, Quanhua |
| description | The phase-derived velocity measurement (PDVM) technique can achieve a high measurement accuracy at the phase level and thus has great application prospects in the field of micromotion feature extraction and target recognition. To achieve a PDVM with a low signal-to-noise ratio (SNR), a PDVM method based on the generalized Radon-Fourier transform (GRFT) is proposed in this article. The main challenges that we overcome are phase extraction and phase ambiguity resolving under the condition of a low SNR. By utilizing the GRFT to estimate the target motion parameters, the echo peak position can be reconstructed, and then the peak phase value can be extracted. In the meantime, the phase ambiguity integer can be resolved based on the rough velocity estimation results obtained by the GRFT, and the phase ambiguity resolving can be realized at a low SNR. In addition, to suppress the influence of noise on the extracted phase, a filter design method based on the target motion characteristics is proposed to further improve the accuracy of the PDVM. In the simulation, the performance of the proposed method under different motion models and different SNR conditions is analyzed, and the effectiveness of the proposed method under low-SNR conditions is verified. Compared with directly using the GRFT, the proposed method has the advantages of strong applicability to different motion models and low computational load. |
| doi_str_mv | 10.1109/TGRS.2022.3155741 |
| format | Article |
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To achieve a PDVM with a low signal-to-noise ratio (SNR), a PDVM method based on the generalized Radon-Fourier transform (GRFT) is proposed in this article. The main challenges that we overcome are phase extraction and phase ambiguity resolving under the condition of a low SNR. By utilizing the GRFT to estimate the target motion parameters, the echo peak position can be reconstructed, and then the peak phase value can be extracted. In the meantime, the phase ambiguity integer can be resolved based on the rough velocity estimation results obtained by the GRFT, and the phase ambiguity resolving can be realized at a low SNR. In addition, to suppress the influence of noise on the extracted phase, a filter design method based on the target motion characteristics is proposed to further improve the accuracy of the PDVM. In the simulation, the performance of the proposed method under different motion models and different SNR conditions is analyzed, and the effectiveness of the proposed method under low-SNR conditions is verified. Compared with directly using the GRFT, the proposed method has the advantages of strong applicability to different motion models and low computational load.</description><identifier>ISSN: 0196-2892</identifier><identifier>EISSN: 1558-0644</identifier><identifier>DOI: 10.1109/TGRS.2022.3155741</identifier><identifier>CODEN: IGRSD2</identifier><language>eng</language><publisher>New York: IEEE</publisher><subject>Accuracy ; Ambiguity ; Computer applications ; Echoes ; Feature extraction ; Filter design (mathematics) ; Fourier transforms ; Generalized Radon–Fourier transform (GRFT) ; low signal-to-noise ratio (SNR) ; Measurement ; Measurement methods ; Movement ; phase ambiguity resolving ; phase filter ; Phase measurement ; phase-derived velocity measurement (PDVM) ; Radar ; Radon ; Signal resolution ; Signal to noise ratio ; Target recognition ; Velocity ; Velocity measurement ; Wideband</subject><ispartof>IEEE transactions on geoscience and remote sensing, 2022, Vol.60, p.1-16</ispartof><rights>Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2022</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c293t-df23fe2ad20f1965ee74e47c44e8bf64855b1d186515e23a59b0f408abdf423c3</citedby><cites>FETCH-LOGICAL-c293t-df23fe2ad20f1965ee74e47c44e8bf64855b1d186515e23a59b0f408abdf423c3</cites><orcidid>0000-0001-9369-8580 ; 0000-0001-9422-1311 ; 0000-0003-4253-2614</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/9724171$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>314,776,780,792,4009,27902,27903,27904,54737</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/9724171$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Li, Wenji</creatorcontrib><creatorcontrib>Fan, Huayu</creatorcontrib><creatorcontrib>Ren, Lixiang</creatorcontrib><creatorcontrib>Sha, Minghui</creatorcontrib><creatorcontrib>Mao, Erke</creatorcontrib><creatorcontrib>Liu, Quanhua</creatorcontrib><title>A Phase-Derived Velocity Measurement Method Based on the Generalized Radon-Fourier Transform With a Low SNR</title><title>IEEE transactions on geoscience and remote sensing</title><addtitle>TGRS</addtitle><description>The phase-derived velocity measurement (PDVM) technique can achieve a high measurement accuracy at the phase level and thus has great application prospects in the field of micromotion feature extraction and target recognition. To achieve a PDVM with a low signal-to-noise ratio (SNR), a PDVM method based on the generalized Radon-Fourier transform (GRFT) is proposed in this article. The main challenges that we overcome are phase extraction and phase ambiguity resolving under the condition of a low SNR. By utilizing the GRFT to estimate the target motion parameters, the echo peak position can be reconstructed, and then the peak phase value can be extracted. In the meantime, the phase ambiguity integer can be resolved based on the rough velocity estimation results obtained by the GRFT, and the phase ambiguity resolving can be realized at a low SNR. In addition, to suppress the influence of noise on the extracted phase, a filter design method based on the target motion characteristics is proposed to further improve the accuracy of the PDVM. In the simulation, the performance of the proposed method under different motion models and different SNR conditions is analyzed, and the effectiveness of the proposed method under low-SNR conditions is verified. Compared with directly using the GRFT, the proposed method has the advantages of strong applicability to different motion models and low computational load.</description><subject>Accuracy</subject><subject>Ambiguity</subject><subject>Computer applications</subject><subject>Echoes</subject><subject>Feature extraction</subject><subject>Filter design (mathematics)</subject><subject>Fourier transforms</subject><subject>Generalized Radon–Fourier transform (GRFT)</subject><subject>low signal-to-noise ratio (SNR)</subject><subject>Measurement</subject><subject>Measurement methods</subject><subject>Movement</subject><subject>phase ambiguity resolving</subject><subject>phase filter</subject><subject>Phase measurement</subject><subject>phase-derived velocity measurement (PDVM)</subject><subject>Radar</subject><subject>Radon</subject><subject>Signal resolution</subject><subject>Signal to noise ratio</subject><subject>Target recognition</subject><subject>Velocity</subject><subject>Velocity measurement</subject><subject>Wideband</subject><issn>0196-2892</issn><issn>1558-0644</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><sourceid>RIE</sourceid><recordid>eNo9kEtPwzAQhC0EEqXwAxAXS5wTbMfO41gKLUjlobbA0XLitZLSxsVOQeXX46oVpx2tZnZHH0KXlMSUkuJmPp7OYkYYixMqRMbpEeoFkUck5fwY9Qgt0ojlBTtFZ94vCKFc0KyHPgf4tVYeojtwzTdo_A5LWzXdFj-B8hsHK2i7oLvaanwbjBrbFnc14DG04NSy-Q2rqdK2jUZ24xpweO5U6411K_zRdDVWeGJ_8Ox5eo5OjFp6uDjMPnob3c-HD9HkZfw4HEyiihVJF2nDEgNMaUZMaC0AMg48qziHvDQpz4UoqaZ5KqgAlihRlMRwkqtSG86SKumj6_3dtbNfG_CdXIRmbXgpWYizgpBcBBfduypnvXdg5No1K-W2khK5Yyp3TOWOqTwwDZmrfaYBgH9_kTFOM5r8Aabeck8</recordid><startdate>2022</startdate><enddate>2022</enddate><creator>Li, Wenji</creator><creator>Fan, Huayu</creator><creator>Ren, Lixiang</creator><creator>Sha, Minghui</creator><creator>Mao, Erke</creator><creator>Liu, Quanhua</creator><general>IEEE</general><general>The Institute of Electrical and Electronics Engineers, Inc. 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To achieve a PDVM with a low signal-to-noise ratio (SNR), a PDVM method based on the generalized Radon-Fourier transform (GRFT) is proposed in this article. The main challenges that we overcome are phase extraction and phase ambiguity resolving under the condition of a low SNR. By utilizing the GRFT to estimate the target motion parameters, the echo peak position can be reconstructed, and then the peak phase value can be extracted. In the meantime, the phase ambiguity integer can be resolved based on the rough velocity estimation results obtained by the GRFT, and the phase ambiguity resolving can be realized at a low SNR. In addition, to suppress the influence of noise on the extracted phase, a filter design method based on the target motion characteristics is proposed to further improve the accuracy of the PDVM. In the simulation, the performance of the proposed method under different motion models and different SNR conditions is analyzed, and the effectiveness of the proposed method under low-SNR conditions is verified. Compared with directly using the GRFT, the proposed method has the advantages of strong applicability to different motion models and low computational load.</abstract><cop>New York</cop><pub>IEEE</pub><doi>10.1109/TGRS.2022.3155741</doi><tpages>16</tpages><orcidid>https://orcid.org/0000-0001-9369-8580</orcidid><orcidid>https://orcid.org/0000-0001-9422-1311</orcidid><orcidid>https://orcid.org/0000-0003-4253-2614</orcidid></addata></record> |
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| subjects | Accuracy Ambiguity Computer applications Echoes Feature extraction Filter design (mathematics) Fourier transforms Generalized Radon–Fourier transform (GRFT) low signal-to-noise ratio (SNR) Measurement Measurement methods Movement phase ambiguity resolving phase filter Phase measurement phase-derived velocity measurement (PDVM) Radar Radon Signal resolution Signal to noise ratio Target recognition Velocity Velocity measurement Wideband |
| title | A Phase-Derived Velocity Measurement Method Based on the Generalized Radon-Fourier Transform With a Low SNR |
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