{"id":"https://openalex.org/W4385444729","doi":"https://doi.org/10.1109/taes.2023.3300260","title":"Deep Unfolding Network for ISAR Imaging Based on Hypernetwork","display_name":"Deep Unfolding Network for ISAR Imaging Based on Hypernetwork","publication_year":2023,"publication_date":"2023-08-01","ids":{"openalex":"https://openalex.org/W4385444729","doi":"https://doi.org/10.1109/taes.2023.3300260"},"language":"en","primary_location":{"id":"doi:10.1109/taes.2023.3300260","is_oa":false,"landing_page_url":"https://doi.org/10.1109/taes.2023.3300260","pdf_url":null,"source":{"id":"https://openalex.org/S193624734","display_name":"IEEE Transactions on Aerospace and Electronic Systems","issn_l":"0018-9251","issn":["0018-9251","1557-9603","2371-9877"],"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 Aerospace and Electronic Systems","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/A5043605891","display_name":"Jianwen Guo","orcid":"https://orcid.org/0000-0002-1390-4098"},"institutions":[{"id":"https://openalex.org/I39333907","display_name":"Yanshan University","ror":"https://ror.org/02txfnf15","country_code":"CN","type":"education","lineage":["https://openalex.org/I39333907"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jianwen Guo","raw_affiliation_strings":["Yanshan University, Qinhuangdao, China"],"raw_orcid":"https://orcid.org/0000-0002-1390-4098","affiliations":[{"raw_affiliation_string":"Yanshan University, Qinhuangdao, China","institution_ids":["https://openalex.org/I39333907"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5025155285","display_name":"Hongyin Shi","orcid":"https://orcid.org/0000-0002-2919-9004"},"institutions":[{"id":"https://openalex.org/I62853816","display_name":"Beijing University of Civil Engineering and Architecture","ror":"https://ror.org/02yj0p855","country_code":"CN","type":"education","lineage":["https://openalex.org/I62853816"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hongyin Shi","raw_affiliation_strings":["Beijing University of Civil Engineering and Architecture, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-2919-9004","affiliations":[{"raw_affiliation_string":"Beijing University of Civil Engineering and Architecture, Beijing, China","institution_ids":["https://openalex.org/I62853816"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5019731119","display_name":"Ting Yang","orcid":"https://orcid.org/0000-0002-4511-2546"},"institutions":[{"id":"https://openalex.org/I39333907","display_name":"Yanshan University","ror":"https://ror.org/02txfnf15","country_code":"CN","type":"education","lineage":["https://openalex.org/I39333907"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ting Yang","raw_affiliation_strings":["Yanshan University, Qinhuangdao, China"],"raw_orcid":"https://orcid.org/0000-0002-4511-2546","affiliations":[{"raw_affiliation_string":"Yanshan University, Qinhuangdao, China","institution_ids":["https://openalex.org/I39333907"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101511140","display_name":"Liu Da","orcid":"https://orcid.org/0000-0002-9866-5419"},"institutions":[{"id":"https://openalex.org/I39333907","display_name":"Yanshan University","ror":"https://ror.org/02txfnf15","country_code":"CN","type":"education","lineage":["https://openalex.org/I39333907"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Da Liu","raw_affiliation_strings":["Yanshan University, Qinhuangdao, China"],"raw_orcid":"https://orcid.org/0000-0002-9866-5419","affiliations":[{"raw_affiliation_string":"Yanshan University, Qinhuangdao, China","institution_ids":["https://openalex.org/I39333907"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100357525","display_name":"Zhijun Qiao","orcid":"https://orcid.org/0000-0002-5578-6181"},"institutions":[{"id":"https://openalex.org/I2802326326","display_name":"The University of Texas Rio Grande Valley","ror":"https://ror.org/02p5xjf12","country_code":"US","type":"education","lineage":["https://openalex.org/I2802326326"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Zhijun Qiao","raw_affiliation_strings":["University of Texas Rio Grande Valley, Edinburg, TX, USA"],"raw_orcid":"https://orcid.org/0000-0002-5578-6181","affiliations":[{"raw_affiliation_string":"University of Texas Rio Grande Valley, Edinburg, TX, USA","institution_ids":["https://openalex.org/I2802326326"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":10.1534,"has_fulltext":false,"cited_by_count":13,"citation_normalized_percentile":{"value":0.97472279,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":95,"max":99},"biblio":{"volume":"59","issue":"6","first_page":"8076","last_page":"8089"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"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"}},"topics":[{"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":0.9941999912261963,"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"}},{"id":"https://openalex.org/T10271","display_name":"Seismic Imaging and Inversion Techniques","score":0.9905999898910522,"subfield":{"id":"https://openalex.org/subfields/1908","display_name":"Geophysics"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/inverse-synthetic-aperture-radar","display_name":"Inverse synthetic aperture radar","score":0.8615843057632446},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7412436008453369},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.7126547694206238},{"id":"https://openalex.org/keywords/synthetic-aperture-radar","display_name":"Synthetic aperture radar","score":0.521985650062561},{"id":"https://openalex.org/keywords/radar-imaging","display_name":"Radar imaging","score":0.505481481552124},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4780431389808655},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4485161602497101},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.43665558099746704},{"id":"https://openalex.org/keywords/radar","display_name":"Radar","score":0.41380977630615234},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.34029096364974976}],"concepts":[{"id":"https://openalex.org/C109094680","wikidata":"https://www.wikidata.org/wiki/Q6060432","display_name":"Inverse synthetic aperture radar","level":4,"score":0.8615843057632446},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7412436008453369},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.7126547694206238},{"id":"https://openalex.org/C87360688","wikidata":"https://www.wikidata.org/wiki/Q740686","display_name":"Synthetic aperture radar","level":2,"score":0.521985650062561},{"id":"https://openalex.org/C10929652","wikidata":"https://www.wikidata.org/wiki/Q7279985","display_name":"Radar imaging","level":3,"score":0.505481481552124},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4780431389808655},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4485161602497101},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.43665558099746704},{"id":"https://openalex.org/C554190296","wikidata":"https://www.wikidata.org/wiki/Q47528","display_name":"Radar","level":2,"score":0.41380977630615234},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.34029096364974976},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/taes.2023.3300260","is_oa":false,"landing_page_url":"https://doi.org/10.1109/taes.2023.3300260","pdf_url":null,"source":{"id":"https://openalex.org/S193624734","display_name":"IEEE Transactions on Aerospace and Electronic Systems","issn_l":"0018-9251","issn":["0018-9251","1557-9603","2371-9877"],"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 Aerospace and Electronic Systems","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/9","score":0.4699999988079071,"display_name":"Industry, innovation and infrastructure"}],"awards":[{"id":"https://openalex.org/G5536320282","display_name":null,"funder_award_id":"F2021203085","funder_id":"https://openalex.org/F4320322163","funder_display_name":"Natural Science Foundation of Hebei Province"},{"id":"https://openalex.org/G8064904371","display_name":"\u57fa\u4e8e\u5085\u91cc\u53f6\u53e0\u5c42\u7406\u8bba\u548c\u6df1\u5ea6\u5b66\u4e60\u7684\u7535\u78c1\u6da1\u65cb\u9635\u5217\u96f7\u8fbe\u7a00\u758f\u6210\u50cf\u6280\u672f\u7814\u7a76","funder_award_id":"62071414","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G970927940","display_name":null,"funder_award_id":"61102110","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/F4320322163","display_name":"Natural Science Foundation of Hebei Province","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":52,"referenced_works":["https://openalex.org/W1973503417","https://openalex.org/W1992036418","https://openalex.org/W2002849329","https://openalex.org/W2008540747","https://openalex.org/W2015911499","https://openalex.org/W2057955933","https://openalex.org/W2091155613","https://openalex.org/W2110965352","https://openalex.org/W2127952006","https://openalex.org/W2146554500","https://openalex.org/W2396681965","https://openalex.org/W2502901375","https://openalex.org/W2547878593","https://openalex.org/W2588240548","https://openalex.org/W2757771685","https://openalex.org/W2761315682","https://openalex.org/W2776751579","https://openalex.org/W2810566158","https://openalex.org/W2946622931","https://openalex.org/W2962760202","https://openalex.org/W2963050343","https://openalex.org/W2963521429","https://openalex.org/W2963841451","https://openalex.org/W2963846225","https://openalex.org/W2979357982","https://openalex.org/W2980331766","https://openalex.org/W3007183211","https://openalex.org/W3019840949","https://openalex.org/W3078162961","https://openalex.org/W3087868801","https://openalex.org/W3088137666","https://openalex.org/W3100955934","https://openalex.org/W3104326121","https://openalex.org/W3120690350","https://openalex.org/W3124159345","https://openalex.org/W3133902371","https://openalex.org/W3158906999","https://openalex.org/W3172643713","https://openalex.org/W3182567567","https://openalex.org/W3204069956","https://openalex.org/W3206187317","https://openalex.org/W3214499489","https://openalex.org/W4206336132","https://openalex.org/W4210930491","https://openalex.org/W4220832249","https://openalex.org/W4224950078","https://openalex.org/W4285110357","https://openalex.org/W4285291362","https://openalex.org/W4295916833","https://openalex.org/W6640212811","https://openalex.org/W6739901393","https://openalex.org/W6864424756"],"related_works":["https://openalex.org/W2996630340","https://openalex.org/W2540450177","https://openalex.org/W2170580735","https://openalex.org/W1552305638","https://openalex.org/W1915418828","https://openalex.org/W2547107543","https://openalex.org/W2545123933","https://openalex.org/W2031673444","https://openalex.org/W1994788526","https://openalex.org/W2613451563"],"abstract_inverted_index":{"Inverse":[0],"synthetic":[1],"aperture":[2],"radar":[3],"(ISAR)":[4],"imaging":[5,24,39,76],"can":[6,83,154],"provide":[7],"high-resolution":[8],"images":[9],"of":[10,99,127,132],"targets.":[11],"More":[12],"recently,":[13],"the":[14,31,46,51,61,86,93,97,100,108,118,136,149,157,178],"unfolding":[15,47,87,104,151],"algorithm":[16],"has":[17],"successfully":[18],"realized":[19],"fast":[20],"and":[21,40,56,66,173,185],"efficient":[22],"ISAR":[23,38,75],"by":[25],"providing":[26],"a":[27,80,130,141],"systematic":[28],"connection":[29],"between":[30],"traditional":[32],"iterative":[33],"algorithms":[34],"widely":[35],"used":[36],"in":[37,63,169],"data-based":[41],"deep":[42],"learning.":[43,125],"However,":[44],"once":[45],"framework":[48,77,101],"is":[49,69,102,121,138],"trained,":[50],"layer-dependent":[52],"parameters":[53,90],"are":[54],"fixed":[55],"difficult":[57],"to":[58,60,91,139,161],"adapt":[59],"variations":[62],"test":[64],"scenarios,":[65],"usually,":[67],"retraining":[68],"required.":[70],"This":[71],"article":[72],"proposes":[73],"an":[74,103,145],"based":[78,106],"on":[79,107],"hypernetwork":[81,142],"that":[82,143,153,177],"dynamically":[84,155],"generate":[85,156],"network's":[88],"internal":[89],"accommodate":[92],"various":[94,170],"scenarios.":[95,163,171],"Specifically,":[96],"basis":[98],"network":[105,152],"generalized":[109],"expectation":[110],"consistent":[111],"(GEC)":[112],"approximation":[113],"phase":[114],"recovery":[115],"algorithm,":[116],"where":[117],"damping":[119,134,158],"factor":[120],"employed":[122],"for":[123],"data-driven":[124],"Instead":[126],"directly":[128],"learning":[129],"set":[131],"optimal":[133],"factors,":[135],"key":[137],"develop":[140],"trains":[144],"intelligent":[146],"controller":[147],"as":[148],"main":[150],"factors":[159],"according":[160],"testing":[162],"Thus,":[164],"it":[165],"exhibits":[166,181],"strong":[167],"robustness":[168],"Simulation":[172],"measurement":[174],"experiments":[175],"show":[176],"proposed":[179],"method":[180],"excellent":[182],"performance,":[183],"robustness,":[184],"focusing":[186],"accuracy.":[187]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":9},{"year":2024,"cited_by_count":3}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
