{"id":"https://openalex.org/W4316661105","doi":"https://doi.org/10.1109/tgrs.2023.3237332","title":"Enhancing Forward-Looking Image Resolution: Combining Low-Rank and Sparsity Priors","display_name":"Enhancing Forward-Looking Image Resolution: Combining Low-Rank and Sparsity Priors","publication_year":2023,"publication_date":"2023-01-01","ids":{"openalex":"https://openalex.org/W4316661105","doi":"https://doi.org/10.1109/tgrs.2023.3237332"},"language":"en","primary_location":{"id":"doi:10.1109/tgrs.2023.3237332","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2023.3237332","pdf_url":null,"source":{"id":"https://openalex.org/S111326731","display_name":"IEEE Transactions on Geoscience and Remote Sensing","issn_l":"0196-2892","issn":["0196-2892","1558-0644"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Geoscience and Remote Sensing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5057436876","display_name":"Junkui Tang","orcid":"https://orcid.org/0000-0002-4563-2154"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Junkui Tang","raw_affiliation_strings":["National Laboratory of Radar Signal Processing, Xidian University, Xi’an, China"],"affiliations":[{"raw_affiliation_string":"National Laboratory of Radar Signal Processing, Xidian University, Xi’an, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100744285","display_name":"Zheng Liu","orcid":"https://orcid.org/0000-0001-6526-059X"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zheng Liu","raw_affiliation_strings":["National Laboratory of Radar Signal Processing, Xidian University, Xi’an, China"],"affiliations":[{"raw_affiliation_string":"National Laboratory of Radar Signal Processing, Xidian University, Xi’an, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5007677145","display_name":"Lei Ran","orcid":"https://orcid.org/0000-0003-0687-7738"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lei Ran","raw_affiliation_strings":["National Laboratory of Radar Signal Processing, Xidian University, Xi’an, China"],"affiliations":[{"raw_affiliation_string":"National Laboratory of Radar Signal Processing, Xidian University, Xi’an, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5026237422","display_name":"Rong Xie","orcid":"https://orcid.org/0009-0006-6092-328X"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Rong Xie","raw_affiliation_strings":["National Laboratory of Radar Signal Processing, Xidian University, Xi’an, China"],"affiliations":[{"raw_affiliation_string":"National Laboratory of Radar Signal Processing, Xidian University, Xi’an, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5068386390","display_name":"Jikai Qin","orcid":"https://orcid.org/0000-0003-3688-6651"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jikai Qin","raw_affiliation_strings":["National Laboratory of Radar Signal Processing, Xidian University, Xi’an, China"],"affiliations":[{"raw_affiliation_string":"National Laboratory of Radar Signal Processing, Xidian University, Xi’an, China","institution_ids":["https://openalex.org/I149594827"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5057436876"],"corresponding_institution_ids":["https://openalex.org/I149594827"],"apc_list":null,"apc_paid":null,"fwci":4.4553,"has_fulltext":false,"cited_by_count":21,"citation_normalized_percentile":{"value":0.95599168,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":"61","issue":null,"first_page":"1","last_page":"12"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11038","display_name":"Advanced SAR Imaging Techniques","score":0.9988999962806702,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12015","display_name":"Photoacoustic and Ultrasonic Imaging","score":0.9987999796867371,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7540469169616699},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.6611932516098022},{"id":"https://openalex.org/keywords/radar-imaging","display_name":"Radar imaging","score":0.6393686532974243},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5664731860160828},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5594198107719421},{"id":"https://openalex.org/keywords/compressed-sensing","display_name":"Compressed sensing","score":0.5401095747947693},{"id":"https://openalex.org/keywords/radar","display_name":"Radar","score":0.4906226694583893},{"id":"https://openalex.org/keywords/iterative-reconstruction","display_name":"Iterative reconstruction","score":0.4526427388191223},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.41810908913612366},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.39142751693725586},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.2407556176185608},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.08621934056282043}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7540469169616699},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.6611932516098022},{"id":"https://openalex.org/C10929652","wikidata":"https://www.wikidata.org/wiki/Q7279985","display_name":"Radar imaging","level":3,"score":0.6393686532974243},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5664731860160828},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5594198107719421},{"id":"https://openalex.org/C124851039","wikidata":"https://www.wikidata.org/wiki/Q2665459","display_name":"Compressed sensing","level":2,"score":0.5401095747947693},{"id":"https://openalex.org/C554190296","wikidata":"https://www.wikidata.org/wiki/Q47528","display_name":"Radar","level":2,"score":0.4906226694583893},{"id":"https://openalex.org/C141379421","wikidata":"https://www.wikidata.org/wiki/Q6094427","display_name":"Iterative reconstruction","level":2,"score":0.4526427388191223},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.41810908913612366},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.39142751693725586},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.2407556176185608},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.08621934056282043},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tgrs.2023.3237332","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2023.3237332","pdf_url":null,"source":{"id":"https://openalex.org/S111326731","display_name":"IEEE Transactions on Geoscience and Remote Sensing","issn_l":"0196-2892","issn":["0196-2892","1558-0644"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Geoscience and Remote Sensing","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G6437026023","display_name":null,"funder_award_id":"2019M663632","funder_id":"https://openalex.org/F4320321543","funder_display_name":"China Postdoctoral Science Foundation"},{"id":"https://openalex.org/G7965330101","display_name":null,"funder_award_id":"62001346","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320321543","display_name":"China Postdoctoral Science Foundation","ror":"https://ror.org/0426zh255"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":49,"referenced_works":["https://openalex.org/W184876746","https://openalex.org/W1566087588","https://openalex.org/W1965736081","https://openalex.org/W1975704715","https://openalex.org/W2035702850","https://openalex.org/W2048428956","https://openalex.org/W2051438985","https://openalex.org/W2146000945","https://openalex.org/W2152279006","https://openalex.org/W2161035945","https://openalex.org/W2161765392","https://openalex.org/W2162409952","https://openalex.org/W2291870248","https://openalex.org/W2314718882","https://openalex.org/W2341556460","https://openalex.org/W2342913866","https://openalex.org/W2467396996","https://openalex.org/W2599580024","https://openalex.org/W2622626024","https://openalex.org/W2730092257","https://openalex.org/W2771141961","https://openalex.org/W2773976392","https://openalex.org/W2786614813","https://openalex.org/W2789274581","https://openalex.org/W2792672598","https://openalex.org/W2800666025","https://openalex.org/W2802894583","https://openalex.org/W2896831678","https://openalex.org/W2926293197","https://openalex.org/W2950020196","https://openalex.org/W2954945393","https://openalex.org/W2960118934","https://openalex.org/W2963664109","https://openalex.org/W2965024619","https://openalex.org/W2977749539","https://openalex.org/W3001455037","https://openalex.org/W3005369213","https://openalex.org/W3030590316","https://openalex.org/W3039531461","https://openalex.org/W3040121955","https://openalex.org/W3120069812","https://openalex.org/W3135759753","https://openalex.org/W3157521196","https://openalex.org/W3178615792","https://openalex.org/W3188702784","https://openalex.org/W3207374033","https://openalex.org/W4205338296","https://openalex.org/W4285296767","https://openalex.org/W4312588616"],"related_works":["https://openalex.org/W2158224665","https://openalex.org/W2379589510","https://openalex.org/W4300044672","https://openalex.org/W2810730439","https://openalex.org/W1881631164","https://openalex.org/W2358292267","https://openalex.org/W2896778670","https://openalex.org/W4313855562","https://openalex.org/W2091422131","https://openalex.org/W2742737769"],"abstract_inverted_index":{"Compressed":[0],"sensing":[1],"(CS)-based":[2],"imaging":[3,15,22,32,53,70,78,111,178],"technology":[4],"has":[5],"attracted":[6],"a":[7,101,113],"lot":[8],"of":[9,18,41,46,85,94,142,154,175],"interest":[10,19],"because":[11],"it":[12],"can":[13,55],"enhance":[14],"resolution.":[16],"Targets":[17],"for":[20,37,109],"forward-looking":[21,48,96,110,176],"radar":[23,69,88,116,177],"are":[24],"typically":[25],"few":[26],"in":[27,68,179],"comparison":[28,180],"to":[29,43,117,181],"the":[30,38,44,60,72,82,86,92,95,123,140,143,152,170],"entire":[31],"region.":[33],"This":[34],"sparsity":[35,93],"allows":[36],"natural":[39],"application":[40],"CS":[42],"reconstruction":[45,137],"high-resolution":[47],"images.":[49],"However,":[50],"conventional":[51],"CS-based":[52,73],"methods":[54,74],"only":[56],"perform":[57],"well":[58],"when":[59],"signal-to-noise":[61],"ratio":[62],"(SNR)":[63],"is":[64,149,165],"high.":[65],"Strong":[66],"noise":[67],"prevents":[71],"from":[75],"producing":[76],"excellent":[77],"results.":[79],"Inspired":[80],"by":[81],"low-rank":[83,103,124],"property":[84],"received":[87],"target":[89],"echo":[90],"and":[91,104,156,173],"image":[97],"targets,":[98],"we":[99],"present":[100],"combined":[102],"sparse":[105,126],"prior":[106,128],"restricted":[107],"model":[108],"with":[112],"multichannel":[114],"array":[115],"overcome":[118],"strong":[119],"noise.":[120],"To":[121],"solve":[122],"joint":[125],"double":[127],"constraint":[129],"optimization":[130],"problem,":[131],"an":[132],"augmented":[133],"Lagrange":[134],"multiplier":[135,146],"(ALM)":[136],"method":[138,147,164],"under":[139],"framework":[141],"alternating":[144],"direction":[145],"(ADMM)":[148],"proposed.":[150],"Finally,":[151],"results":[153],"simulation":[155],"real":[157],"measurement":[158],"data":[159],"indicate":[160],"that":[161],"our":[162],"presented":[163],"fairly":[166],"effective":[167],"at":[168],"enhancing":[169],"azimuth":[171],"resolution":[172],"robustness":[174],"other":[182],"current":[183],"methods.":[184]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":11},{"year":2024,"cited_by_count":9}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}