Sparse Target Batch-processing Framework for Scanning Radar Superresolution Imaging
Sparse superresolution algorithms have been applied in scanning radar imaging to improve its azimuth resolution. However, the inverse matrix in each iteration is usually diagonal loading by the updating result, which leads to huge computational complexity for two-dimensional echo data. In this lette...
Saved in:
| Published in: | IEEE geoscience and remote sensing letters Vol. 20; p. 1 |
|---|---|
| Main Authors: | , , , , , |
| Format: | Journal Article |
| Language: | English |
| Published: |
Piscataway
IEEE
01.01.2023
The Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subjects: | |
| ISSN: | 1545-598X, 1558-0571 |
| Online Access: | Get full text |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Abstract | Sparse superresolution algorithms have been applied in scanning radar imaging to improve its azimuth resolution. However, the inverse matrix in each iteration is usually diagonal loading by the updating result, which leads to huge computational complexity for two-dimensional echo data. In this letter, a batch-processing superresolution framework is proposed to process the echo data in parallel. On the one hand, the optimization problem for sparse target recovery is modified as matrix form, which presents batch-processing potential for two-dimensional echo data. On the other hand, the optimization problem is solved by the proposed alternating direction method of multipliers (ADMM)-based batch-processing framework, which can avoid high-dimensional matrix inversion along different range bins. Compared with traditional sparse superresolution methods, the proposed batch-processing framework is much suitable for two-dimensional echo data superresolution. |
|---|---|
| AbstractList | Sparse superresolution algorithms have been applied in scanning radar imaging to improve its azimuth resolution. However, the inverse matrix in each iteration is usually diagonal loading by the updating result, which leads to huge computational complexity for 2-D echo data. In this letter, a batch-processing superresolution framework is proposed to process the echo data in parallel. On the one hand, the optimization problem for sparse target recovery is modified as matrix form, which presents the batch-processing potential for 2-D echo data. On the other hand, the optimization problem is solved by the proposed alternating direction method of multipliers (ADMM)-based batch-processing framework, which can avoid high-dimensional matrix inversion along different range bins. Compared with traditional sparse superresolution methods, the proposed batch-processing framework is more suitable for 2-D echo data superresolution. Sparse superresolution algorithms have been applied in scanning radar imaging to improve its azimuth resolution. However, the inverse matrix in each iteration is usually diagonal loading by the updating result, which leads to huge computational complexity for two-dimensional echo data. In this letter, a batch-processing superresolution framework is proposed to process the echo data in parallel. On the one hand, the optimization problem for sparse target recovery is modified as matrix form, which presents batch-processing potential for two-dimensional echo data. On the other hand, the optimization problem is solved by the proposed alternating direction method of multipliers (ADMM)-based batch-processing framework, which can avoid high-dimensional matrix inversion along different range bins. Compared with traditional sparse superresolution methods, the proposed batch-processing framework is much suitable for two-dimensional echo data superresolution. |
| Author | Tuo, Xingyu Mao, Deqing Zhang, Yin Yang, Jianyu Zhang, Yongchao Huang, Yulin |
| Author_xml | – sequence: 1 givenname: Xingyu orcidid: 0000-0003-0118-2240 surname: Tuo fullname: Tuo, Xingyu – sequence: 2 givenname: Deqing orcidid: 0000-0002-7408-1654 surname: Mao fullname: Mao, Deqing – sequence: 3 givenname: Yin orcidid: 0000-0002-6761-2269 surname: Zhang fullname: Zhang, Yin – sequence: 4 givenname: Yongchao orcidid: 0000-0001-5634-6156 surname: Zhang fullname: Zhang, Yongchao – sequence: 5 givenname: Yulin orcidid: 0000-0003-3930-9323 surname: Huang fullname: Huang, Yulin – sequence: 6 givenname: Jianyu orcidid: 0000-0002-4726-8384 surname: Yang fullname: Yang, Jianyu |
| BookMark | eNp9kE1LAzEQhoNUsK3-AMHDguetSTZpkqMWWwsFoVvBW0jTSd3abtZkl-K_d5f2IB48zdf7zAzvAPVKXwJCtwSPCMHqYTFb5iOKaTbKqGCK4AvUJ5zLFHNBel3OeMqVfL9Cgxh3GFMmpeijPK9MiJCsTNhCnTyZ2n6kVfAWYizKbTIN5gBHHz4T50OSW1OWXXtpNqYtmwpCgOj3TV34MpkfzLadXqNLZ_YRbs5xiN6mz6vJS7p4nc0nj4vUUsXqlAEYucbOCcrHhisQLmMglAVulcRKGotBCOU4cY4SC2JD1No5xqWkjGfZEN2f9rb_fjUQa73zTSjbk5pKIhnmmOBWJU4qG3yMAZy2RW26f-tgir0mWHcO6s5B3Tmozw62JPlDVqE4mPD9L3N3YgoA-KUnlI5Vlv0AsmV_Ew |
| CODEN | IGRSBY |
| CitedBy_id | crossref_primary_10_1088_1361_6501_adc14c crossref_primary_10_1109_ACCESS_2024_3494792 crossref_primary_10_1109_JSEN_2024_3409886 crossref_primary_10_1109_TGRS_2025_3561856 crossref_primary_10_1088_1361_6501_ad704f |
| Cites_doi | 10.1109/TGRS.2022.3203131 10.1109/LGRS.2012.2185679 10.1137/080724265 10.1109/ACCESS.2020.2965973 10.1109/TIP.2017.2779265 10.1109/IAEAC50856.2021.9390998 10.1109/TAES.2010.5417172 10.1109/IGARSS39084.2020.9324322 10.1109/LGRS.2008.2006285 10.1007/s11042-020-10035-z 10.1109/TAES.2010.5545210 |
| ContentType | Journal Article |
| Copyright | Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2023 |
| Copyright_xml | – notice: Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2023 |
| DBID | 97E RIA RIE AAYXX CITATION 7SC 7SP 7TG 7UA 8FD C1K F1W FR3 H8D H96 JQ2 KL. KR7 L.G L7M L~C L~D |
| DOI | 10.1109/LGRS.2023.3274910 |
| DatabaseName | IEEE All-Society Periodicals Package (ASPP) 2005–Present IEEE All-Society Periodicals Package (ASPP) 1998–Present IEEE/IET Electronic Library CrossRef Computer and Information Systems Abstracts Electronics & Communications Abstracts Meteorological & Geoastrophysical Abstracts Water Resources Abstracts Technology Research Database Environmental Sciences and Pollution Management ASFA: Aquatic Sciences and Fisheries Abstracts Engineering Research Database Aerospace Database Aquatic Science & Fisheries Abstracts (ASFA) 2: Ocean Technology, Policy & Non-Living Resources ProQuest Computer Science Collection Meteorological & Geoastrophysical Abstracts - Academic Civil Engineering Abstracts Aquatic Science & Fisheries Abstracts (ASFA) Professional Advanced Technologies Database with Aerospace Computer and Information Systems Abstracts Academic Computer and Information Systems Abstracts Professional |
| DatabaseTitle | CrossRef Civil Engineering Abstracts Aquatic Science & Fisheries Abstracts (ASFA) Professional Technology Research Database Computer and Information Systems Abstracts – Academic Electronics & Communications Abstracts ProQuest Computer Science Collection Computer and Information Systems Abstracts Water Resources Abstracts Environmental Sciences and Pollution Management Computer and Information Systems Abstracts Professional Aerospace Database Meteorological & Geoastrophysical Abstracts Aquatic Science & Fisheries Abstracts (ASFA) 2: Ocean Technology, Policy & Non-Living Resources ASFA: Aquatic Sciences and Fisheries Abstracts Engineering Research Database Advanced Technologies Database with Aerospace Meteorological & Geoastrophysical Abstracts - Academic |
| DatabaseTitleList | Civil Engineering Abstracts |
| Database_xml | – sequence: 1 dbid: RIE name: IEEE Electronic Library (IEL) url: https://ieeexplore.ieee.org/ sourceTypes: Publisher |
| DeliveryMethod | fulltext_linktorsrc |
| Discipline | Geography Geology |
| EISSN | 1558-0571 |
| EndPage | 1 |
| ExternalDocumentID | 10_1109_LGRS_2023_3274910 10122693 |
| Genre | orig-research |
| GrantInformation_xml | – fundername: China Postdoctoral Science Foundation grantid: 2022M720667; BX20220055 funderid: 10.13039/501100002858 – fundername: National Natural Science Foundation of China grantid: 61901090; 61901092 funderid: 10.13039/501100001809 |
| GroupedDBID | 0R~ 29I 4.4 5GY 6IK 97E AAJGR AARMG AASAJ AAWTH ABAZT ABQJQ ABVLG ACGFO ACIWK AENEX AFRAH AGQYO AHBIQ AKJIK AKQYR ALMA_UNASSIGNED_HOLDINGS ATWAV BEFXN BFFAM BGNUA BKEBE BPEOZ CS3 EBS HZ~ H~9 IFIPE IPLJI JAVBF LAI M43 O9- OCL P2P RIA RIE RNS ~02 5VS AAYXX AETIX AGSQL AIBXA CITATION EJD 7SC 7SP 7TG 7UA 8FD C1K F1W FR3 H8D H96 JQ2 KL. KR7 L.G L7M L~C L~D |
| ID | FETCH-LOGICAL-c294t-4eea8b0ff7256a59e7f34e79ce5c98098ac0e779f51ff21ce7d19bff458824533 |
| IEDL.DBID | RIE |
| ISICitedReferencesCount | 7 |
| ISICitedReferencesURI | http://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=Summon&SrcAuth=ProQuest&DestLinkType=CitingArticles&DestApp=WOS_CPL&KeyUT=000994564800005&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D |
| ISSN | 1545-598X |
| IngestDate | Mon Jun 30 10:24:49 EDT 2025 Sat Nov 29 05:54:16 EST 2025 Tue Nov 18 22:45:35 EST 2025 Wed Aug 27 02:18:21 EDT 2025 |
| IsPeerReviewed | true |
| IsScholarly | true |
| Language | English |
| License | https://ieeexplore.ieee.org/Xplorehelp/downloads/license-information/IEEE.html https://doi.org/10.15223/policy-029 https://doi.org/10.15223/policy-037 |
| LinkModel | DirectLink |
| MergedId | FETCHMERGED-LOGICAL-c294t-4eea8b0ff7256a59e7f34e79ce5c98098ac0e779f51ff21ce7d19bff458824533 |
| Notes | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 |
| ORCID | 0000-0002-7408-1654 0000-0003-3930-9323 0000-0003-0118-2240 0000-0002-4726-8384 0000-0001-5634-6156 0000-0002-6761-2269 |
| PQID | 2818405010 |
| PQPubID | 75725 |
| PageCount | 1 |
| ParticipantIDs | crossref_citationtrail_10_1109_LGRS_2023_3274910 ieee_primary_10122693 proquest_journals_2818405010 crossref_primary_10_1109_LGRS_2023_3274910 |
| PublicationCentury | 2000 |
| PublicationDate | 2023-01-01 |
| PublicationDateYYYYMMDD | 2023-01-01 |
| PublicationDate_xml | – month: 01 year: 2023 text: 2023-01-01 day: 01 |
| PublicationDecade | 2020 |
| PublicationPlace | Piscataway |
| PublicationPlace_xml | – name: Piscataway |
| PublicationTitle | IEEE geoscience and remote sensing letters |
| PublicationTitleAbbrev | LGRS |
| PublicationYear | 2023 |
| Publisher | IEEE The Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher_xml | – name: IEEE – name: The Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| References | ref13 ref12 ref10 ref2 ref1 ref8 ref7 ref9 ref4 ref6 mao (ref3) 2021; 60 ref5 boyd (ref11) 2011 |
| References_xml | – ident: ref2 doi: 10.1109/TGRS.2022.3203131 – ident: ref5 doi: 10.1109/LGRS.2012.2185679 – ident: ref12 doi: 10.1137/080724265 – ident: ref9 doi: 10.1109/ACCESS.2020.2965973 – ident: ref6 doi: 10.1109/TIP.2017.2779265 – ident: ref7 doi: 10.1109/IAEAC50856.2021.9390998 – ident: ref10 doi: 10.1109/TAES.2010.5417172 – ident: ref8 doi: 10.1109/IGARSS39084.2020.9324322 – volume: 60 start-page: 1 year: 2021 ident: ref3 article-title: Angular superresolution of real aperture radar using online detect-before-reconstruct framework publication-title: IEEE Trans Geosci Remote Sens – ident: ref4 doi: 10.1109/LGRS.2008.2006285 – year: 2011 ident: ref11 publication-title: Distributed optimization and statistical learning via the alternating direction method of multipliers – ident: ref13 doi: 10.1007/s11042-020-10035-z – ident: ref1 doi: 10.1109/TAES.2010.5545210 |
| SSID | ssj0024887 |
| Score | 2.3876638 |
| Snippet | Sparse superresolution algorithms have been applied in scanning radar imaging to improve its azimuth resolution. However, the inverse matrix in each iteration... |
| SourceID | proquest crossref ieee |
| SourceType | Aggregation Database Enrichment Source Index Database Publisher |
| StartPage | 1 |
| SubjectTerms | ADMM Algorithms Azimuth batch-processing Convolution Echoes Frameworks Imaging techniques Iterative methods Optimization Radar Radar imaging Scanning scanning radar Sparse matrices Sparse superresolution Superresolution |
| Title | Sparse Target Batch-processing Framework for Scanning Radar Superresolution Imaging |
| URI | https://ieeexplore.ieee.org/document/10122693 https://www.proquest.com/docview/2818405010 |
| Volume | 20 |
| WOSCitedRecordID | wos000994564800005&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D |
| hasFullText | 1 |
| inHoldings | 1 |
| isFullTextHit | |
| isPrint | |
| journalDatabaseRights | – providerCode: PRVIEE databaseName: IEEE Electronic Library (IEL) customDbUrl: eissn: 1558-0571 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0024887 issn: 1545-598X databaseCode: RIE dateStart: 20040101 isFulltext: true titleUrlDefault: https://ieeexplore.ieee.org/ providerName: IEEE |
| link | http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwlV3fS8MwED7cUPTFH3PidEoefBK6tVnbNI8qbgoyZJuwt5KmFyboNvZD2H9vkmY6EAXfWriUki_JfZfk7gO4yhjnOYqWh0JHOmFApZfJSHiR5JKyBDOJvhWbYN1uMhzyZ5esbnNhENFePsOGebRn-flELs1WWdPUoqIxb5WgxFhcJGt9F9ZLrBqeoQRexJOhO8IMfN586vT6DaMT3mjpIIybbNkNJ2RVVX4sxda_tA_--WeHsO-IJLkpkD-CLRxXYNdpmo9WFdjpWNHe1TH0-1MdviIZ2Fvf5FavviNvWmQIaM9F2usLWkQzWNKXhYwR6Ylc6NflFI2Ahxui5PHd6hpV4aV9P7h78JyYgicpDxdeiCiSzFeKaZIjIo5MtUJkXKKGJfF5IqSPjHEVBUrRQCLLA54pZTJZaahJ4QmUx5MxngLRxlEoNDGkcR6i0s1zSrnKZIwyzOKoBv66d1PpKo0bwYu31EYcPk8NIKkBJHWA1OD6q8m0KLPxl3HVILBhWHR-DeprDFM3E-epqXalSakOO89-aXYOe-brxb5KHcqL2RIvYFt-LF7ns0s7yD4BMNHPSA |
| linkProvider | IEEE |
| linkToHtml | http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwlV1bS8MwFD7oVPTFuzivefBJ6GyzdmkeVdwU5xA7YW8lTU-YoFvZRdi_N0kzFUTBtxZOaMmX5HwnyTkfwFnGOM9R1D0UOtIJAyq9TEbCiySXlMWYSfSt2ATrdOJejz-6ZHWbC4OI9vIZ1syjPcvPh3JqtsouTC0q2uD1RVgy0lkuXeurtF5s9fAMKfAiHvfcIWbg84t26ympGaXwWl2HYdzky35zQ1ZX5cdibD1Mc-Of_7YJ645KkssS-y1YwME2rDpV8_5sG1ZaVrZ3tgNJUugAFknX3vsmV3r97XtFmSOgfRdpzq9oEc1hSSJLISPyJHKhX6cFGgkPN0jJ3ZtVNtqF5-ZN9_rWc3IKnqQ8nHghoogzXymmaY6IODJVD5FxiRqY2OexkD4yxlUUKEUDiSwPeKaUyWWloaaFe1AZDAe4D0QbR6HQ1JA28hCVbp5TylUmGyjDrBFVwZ_3bipdrXEjefGa2pjD56kBJDWApA6QKpx_NinKQht_Ge8aBL4Zlp1fhaM5hqmbi-PU1LvStFQHnge_NDuF1dvuQztt33XuD2HNfKncZTmCymQ0xWNYlu-Tl_HoxA64Dyis0pE |
| openUrl | ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=Sparse+Target+Batch-Processing+Framework+for+Scanning+Radar+Superresolution+Imaging&rft.jtitle=IEEE+geoscience+and+remote+sensing+letters&rft.au=Tuo%2C+Xingyu&rft.au=Mao%2C+Deqing&rft.au=Zhang%2C+Yin&rft.au=Zhang%2C+Yongchao&rft.date=2023-01-01&rft.pub=The+Institute+of+Electrical+and+Electronics+Engineers%2C+Inc.+%28IEEE%29&rft.issn=1545-598X&rft.eissn=1558-0571&rft.volume=20&rft.spage=1&rft_id=info:doi/10.1109%2FLGRS.2023.3274910&rft.externalDBID=NO_FULL_TEXT |
| thumbnail_l | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=1545-598X&client=summon |
| thumbnail_m | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=1545-598X&client=summon |
| thumbnail_s | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=1545-598X&client=summon |