{"id":"https://openalex.org/W7128611369","doi":"https://doi.org/10.1109/tsipn.2026.3663887","title":"GAF-MLGNN: An Efficient Meta-Learning Framework for Few-Shot HRRP RATR With GNN","display_name":"GAF-MLGNN: An Efficient Meta-Learning Framework for Few-Shot HRRP RATR With GNN","publication_year":2026,"publication_date":"2026-01-01","ids":{"openalex":"https://openalex.org/W7128611369","doi":"https://doi.org/10.1109/tsipn.2026.3663887"},"language":null,"primary_location":{"id":"doi:10.1109/tsipn.2026.3663887","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tsipn.2026.3663887","pdf_url":null,"source":{"id":"https://openalex.org/S4306422866","display_name":"IEEE Transactions on Signal and Information Processing over Networks","issn_l":"2373-776X","issn":["2373-776X","2373-7778"],"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 Signal and Information Processing over Networks","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":null,"display_name":"Lingfeng Chen","orcid":"https://orcid.org/0009-0003-2690-9407"},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Lingfeng Chen","raw_affiliation_strings":["College of Electronic Science and Technology, National University of Defense Technology, Changsha, China"],"raw_orcid":"https://orcid.org/0009-0003-2690-9407","affiliations":[{"raw_affiliation_string":"College of Electronic Science and Technology, National University of Defense Technology, Changsha, China","institution_ids":["https://openalex.org/I170215575"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5020551131","display_name":"Panhe Hu","orcid":"https://orcid.org/0000-0001-5895-3152"},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Panhe Hu","raw_affiliation_strings":["College of Electronic Science and Technology, National University of Defense Technology, Changsha, China"],"raw_orcid":"https://orcid.org/0000-0001-5895-3152","affiliations":[{"raw_affiliation_string":"College of Electronic Science and Technology, National University of Defense Technology, Changsha, China","institution_ids":["https://openalex.org/I170215575"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5125635919","display_name":"Qi Liu","orcid":null},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qi Liu","raw_affiliation_strings":["College of Electronic Science and Technology, National University of Defense Technology, Changsha, China"],"raw_orcid":"https://orcid.org/0000-0002-1196-3510","affiliations":[{"raw_affiliation_string":"College of Electronic Science and Technology, National University of Defense Technology, Changsha, China","institution_ids":["https://openalex.org/I170215575"]}]},{"author_position":"last","author":{"id":null,"display_name":"Zhen Liu","orcid":"https://orcid.org/0000-0002-1233-1494"},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhen Liu","raw_affiliation_strings":["College of Electronic Science and Technology, National University of Defense Technology, Changsha, China"],"raw_orcid":"https://orcid.org/0000-0002-1233-1494","affiliations":[{"raw_affiliation_string":"College of Electronic Science and Technology, National University of Defense Technology, Changsha, China","institution_ids":["https://openalex.org/I170215575"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I170215575"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.28471678,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"12","issue":null,"first_page":"341","last_page":"356"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11038","display_name":"Advanced SAR Imaging Techniques","score":0.9585000276565552,"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":0.9585000276565552,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.005900000222027302,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10891","display_name":"Radar Systems and Signal Processing","score":0.0038999998942017555,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/overfitting","display_name":"Overfitting","score":0.54830002784729},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.5218999981880188},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.44769999384880066},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.4221000075340271},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.38359999656677246},{"id":"https://openalex.org/keywords/automatic-target-recognition","display_name":"Automatic target recognition","score":0.37130001187324524},{"id":"https://openalex.org/keywords/range","display_name":"Range (aeronautics)","score":0.3495999872684479}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6499999761581421},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.646399974822998},{"id":"https://openalex.org/C22019652","wikidata":"https://www.wikidata.org/wiki/Q331309","display_name":"Overfitting","level":3,"score":0.54830002784729},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.5218999981880188},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.44769999384880066},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4339999854564667},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.4221000075340271},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.38359999656677246},{"id":"https://openalex.org/C117623542","wikidata":"https://www.wikidata.org/wiki/Q621974","display_name":"Automatic target recognition","level":3,"score":0.37130001187324524},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.35659998655319214},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.3495999872684479},{"id":"https://openalex.org/C554190296","wikidata":"https://www.wikidata.org/wiki/Q47528","display_name":"Radar","level":2,"score":0.33469998836517334},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.30799999833106995},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.2854999899864197},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.2761000096797943},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.27379998564720154},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.2718000113964081},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.2667999863624573},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.2502000033855438}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tsipn.2026.3663887","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tsipn.2026.3663887","pdf_url":null,"source":{"id":"https://openalex.org/S4306422866","display_name":"IEEE Transactions on Signal and Information Processing over Networks","issn_l":"2373-776X","issn":["2373-776X","2373-7778"],"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 Signal and Information Processing over Networks","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G5851501073","display_name":null,"funder_award_id":"62201588","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"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":49,"referenced_works":["https://openalex.org/W1501856433","https://openalex.org/W1989092755","https://openalex.org/W2096261015","https://openalex.org/W2116341502","https://openalex.org/W2140087511","https://openalex.org/W2145680191","https://openalex.org/W2150674271","https://openalex.org/W2194321275","https://openalex.org/W2263236809","https://openalex.org/W2290847742","https://openalex.org/W2558748708","https://openalex.org/W2566079294","https://openalex.org/W2607666785","https://openalex.org/W2904218366","https://openalex.org/W2919115771","https://openalex.org/W2920313172","https://openalex.org/W2922230884","https://openalex.org/W2943605315","https://openalex.org/W2954252026","https://openalex.org/W2963433607","https://openalex.org/W2964105864","https://openalex.org/W2964321699","https://openalex.org/W2968547877","https://openalex.org/W2979689312","https://openalex.org/W2995445161","https://openalex.org/W3015770805","https://openalex.org/W3081328405","https://openalex.org/W3087376917","https://openalex.org/W3117630906","https://openalex.org/W3168674155","https://openalex.org/W3174236562","https://openalex.org/W4200257731","https://openalex.org/W4210260455","https://openalex.org/W4210693529","https://openalex.org/W4285065070","https://openalex.org/W4295855898","https://openalex.org/W4296340043","https://openalex.org/W4296345598","https://openalex.org/W4310348270","https://openalex.org/W4313019727","https://openalex.org/W4313165841","https://openalex.org/W4319781376","https://openalex.org/W4386453433","https://openalex.org/W4387829150","https://openalex.org/W4390871586","https://openalex.org/W4402626679","https://openalex.org/W4405854453","https://openalex.org/W4406856884","https://openalex.org/W4410639995"],"related_works":[],"abstract_inverted_index":{"In":[0],"recent":[1],"years,":[2],"radar":[3],"automatic":[4],"target":[5],"recognition":[6,66,96],"(RATR)":[7],"methods":[8],"employing":[9],"deep-learning":[10],"models":[11],"with":[12],"High":[13],"Resolution":[14],"Range":[15],"Profiles":[16],"(HRRPs)":[17],"have":[18],"demonstrated":[19],"significant":[20],"advancements":[21],"over":[22],"traditional":[23],"approaches.":[24,172],"Nevertheless,":[25],"these":[26],"deep":[27],"architectures":[28],"exhibit":[29],"critical":[30],"performance":[31,158],"degradation":[32],"in":[33],"few-shot":[34,64,99,169],"scenarios":[35],"due":[36],"to":[37,128,164],"severe":[38],"overfitting":[39],"caused":[40],"by":[41],"limited":[42],"training":[43],"samples.":[44],"To":[45,87],"address":[46],"this":[47,101],"challenge,":[48],"we":[49,133],"propose":[50],"<italic":[51],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[52],"xmlns:xlink=\"http://www.w3.org/1999/xlink\"><u>G</u>ramian":[53],"<u>A</u>ngular":[54],"<u>F</u>ield-based":[55],"<u>M</u>eta-<u>L</u>earning":[56],"<u>G</u>raph":[57],"<u>N</u>eural":[58],"<u>N</u>etwork</i>":[59],"(GAF-MLGNN)":[60],"-":[61],"an":[62],"efficient":[63,143],"HRRP":[65,77,84,146,170],"framework":[67,115],"that":[68,122],"makes":[69],"full":[70],"use":[71],"of":[72,76,92,126,137,145,159],"both":[73],"inter-sample":[74,90],"information":[75,82,91],"sequences":[78],"and":[79,108,168],"the":[80,124,135,156,160],"intra-sample":[81,148],"between":[83],"range":[85],"cells.":[86],"fully":[88],"leverage":[89],"HRRPs":[93],"for":[94,118,142],"higher":[95],"accuracy":[97],"under":[98],"circumstances,":[100],"paper":[102],"introduces":[103],"Graph":[104,119],"Neural":[105,120],"Network":[106],"(GNN)":[107],"proposes":[109],"a":[110],"novel":[111],"task":[112],"set-based":[113],"meta-learning":[114,167],"MLGNN":[116],"(Meta-Learning":[117],"Network)":[121],"fits":[123],"characteristic":[125],"GNN":[127],"obtain":[129],"optimal":[130],"parameters.":[131],"Besides,":[132],"incorporate":[134],"technique":[136],"Gramian":[138],"Angular":[139],"Field":[140],"(GAF)":[141],"utilization":[144],"intrinsic":[147],"information.":[149],"Experiments":[150],"conducted":[151],"on":[152],"simulation":[153],"datasets":[154],"demonstrate":[155],"superior":[157],"proposed":[161],"method":[162],"compared":[163],"current":[165],"state-of-the-art":[166],"RATR":[171]},"counts_by_year":[],"updated_date":"2026-03-20T20:47:17.329874","created_date":"2026-02-12T00:00:00"}
