{"id":"https://openalex.org/W7204833939","doi":"https://doi.org/10.1145/3817124.3817202","title":"Lightweight Multi-Scale Attention Network for HRRP Target Recognition","display_name":"Lightweight Multi-Scale Attention Network for HRRP Target Recognition","publication_year":2026,"publication_date":"2026-03-27","ids":{"openalex":"https://openalex.org/W7204833939","doi":"https://doi.org/10.1145/3817124.3817202"},"language":"en","primary_location":{"id":"doi:10.1145/3817124.3817202","doi":"https://doi.org/10.1145/3817124.3817202","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3817124.3817202","pdf_url":null,"source":{"id":"https://openalex.org/S4363607990","display_name":"International Conference on Applied Mathematics, Modelling and Intelligent Computing (CAMMIC)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2026 6th International Conference on Applied Mathematics, Modelling and Intelligent Computing","raw_type":"proceedings-article"},"volume":null,"type":"conference-paper","is_traditional":true,"indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://doi.org/10.1145/3817124.3817202","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5114189866","display_name":"Chixing Lu","orcid":"https://orcid.org/0009-0001-3015-062X","observed_orcids":["https://orcid.org/0009-0001-3015-062X"]},"institutions":[{"id":"https://openalex.org/I4210148107","display_name":"Space Engineering University","ror":"https://ror.org/04rj1td02","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210148107"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chixing Lu","raw_affiliation_strings":["Graduate School, Space Engineering University, Beijing, China"],"raw_orcid":"https://orcid.org/0009-0001-3015-062X","affiliations":[{"raw_affiliation_string":"Graduate School, Space Engineering University, Beijing, China","institution_ids":["https://openalex.org/I4210148107"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5148772925","display_name":"Dan Liu","orcid":"https://orcid.org/0009-0008-3771-6084","observed_orcids":["https://orcid.org/0009-0008-3771-6084"]},"institutions":[{"id":"https://openalex.org/I4210148107","display_name":"Space Engineering University","ror":"https://ror.org/04rj1td02","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210148107"]},{"id":"https://openalex.org/I4387153688","display_name":"Beijing Institute of Radio Metrology and Measurement","ror":"https://ror.org/02c8ctc21","country_code":"CN","type":"company","lineage":["https://openalex.org/I15089104","https://openalex.org/I4387153688"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dan Liu","raw_affiliation_strings":["Institute of Radio Measurement, Beijing, China","National Key Laboratory of Space Target Awareness, Beijing, China","School of Space Information, Space Engineering University, Beijing, China"],"raw_orcid":"https://orcid.org/0009-0008-3771-6084","affiliations":[{"raw_affiliation_string":"Institute of Radio Measurement, Beijing, China","institution_ids":["https://openalex.org/I4387153688"]},{"raw_affiliation_string":"National Key Laboratory of Space Target Awareness, Beijing, China","institution_ids":[]},{"raw_affiliation_string":"School of Space Information, Space Engineering University, Beijing, China","institution_ids":["https://openalex.org/I4210148107"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5061298105","display_name":"Feihuang Chu","orcid":"https://orcid.org/0000-0002-1161-2542","observed_orcids":["https://orcid.org/0000-0002-1161-2542","https://orcid.org/0000-0001-5304-1285"]},"institutions":[{"id":"https://openalex.org/I4210148107","display_name":"Space Engineering University","ror":"https://ror.org/04rj1td02","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210148107"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Feihuang Chu","raw_affiliation_strings":["National Key Laboratory of Space Target Awareness, Beijing, China","School of Space Information, Space Engineering University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-1161-2542","affiliations":[{"raw_affiliation_string":"National Key Laboratory of Space Target Awareness, Beijing, China","institution_ids":[]},{"raw_affiliation_string":"School of Space Information, Space Engineering University, Beijing, China","institution_ids":["https://openalex.org/I4210148107"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5148831435","display_name":"Jinyan Zhang","orcid":"https://orcid.org/0009-0007-5044-8099","observed_orcids":["https://orcid.org/0009-0007-5044-8099"]},"institutions":[{"id":"https://openalex.org/I4210148107","display_name":"Space Engineering University","ror":"https://ror.org/04rj1td02","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210148107"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jinyan Zhang","raw_affiliation_strings":["Graduate School, Space Engineering University, Beijing, China"],"raw_orcid":"https://orcid.org/0009-0007-5044-8099","affiliations":[{"raw_affiliation_string":"Graduate School, Space Engineering University, Beijing, China","institution_ids":["https://openalex.org/I4210148107"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5148775045","display_name":"Desheng Liu","orcid":"https://orcid.org/0009-0005-5119-4866","observed_orcids":["https://orcid.org/0009-0005-5119-4866"]},"institutions":[{"id":"https://openalex.org/I4210148107","display_name":"Space Engineering University","ror":"https://ror.org/04rj1td02","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210148107"]},{"id":"https://openalex.org/I4387153688","display_name":"Beijing Institute of Radio Metrology and Measurement","ror":"https://ror.org/02c8ctc21","country_code":"CN","type":"company","lineage":["https://openalex.org/I15089104","https://openalex.org/I4387153688"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Desheng Liu","raw_affiliation_strings":["Institute of Radio Measurement, Beijing, China","National Key Laboratory of Space Target Awareness, Beijing, China","School of Space Information, Space Engineering University, Beijing, China"],"raw_orcid":"https://orcid.org/0009-0005-5119-4866","affiliations":[{"raw_affiliation_string":"Institute of Radio Measurement, Beijing, China","institution_ids":["https://openalex.org/I4387153688"]},{"raw_affiliation_string":"National Key Laboratory of Space Target Awareness, Beijing, China","institution_ids":[]},{"raw_affiliation_string":"School of Space Information, Space Engineering University, Beijing, China","institution_ids":["https://openalex.org/I4210148107"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.0,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"506","last_page":"513"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11038","display_name":"Advanced SAR Imaging Techniques","score":0.9926999807357788,"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":0.9926999807357788,"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/T10891","display_name":"Radar Systems and Signal Processing","score":0.004600000102072954,"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/T12131","display_name":"Wireless Signal Modulation Classification","score":0.0006000000284984708,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/high-resolution-range-profile","display_name":"high-resolution range profile","score":0.984000027179718},{"id":"https://openalex.org/keywords/radar-automatic-target-recognition","display_name":"radar automatic target recognition","score":0.9039999842643738},{"id":"https://openalex.org/keywords/multiscale-attention","display_name":"multi-scale attention","score":0.7699999809265137},{"id":"https://openalex.org/keywords/squeeze-and-excitation","display_name":"squeeze-and-excitation","score":0.9599999785423279},{"id":"https://openalex.org/keywords/multi-branch-convolution","display_name":"multi-branch convolution","score":0.9929999709129333},{"id":"https://openalex.org/keywords/lightweight-neural-networks","display_name":"lightweight neural networks","score":0.7289999723434448},{"id":"https://openalex.org/keywords/noise-robustness","display_name":"noise robustness","score":0.9869999885559082}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7064999938011169},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6879000067710876},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.5857999920845032},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5683000087738037},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5558000206947327},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.5435000061988831},{"id":"https://openalex.org/C554190296","wikidata":"https://www.wikidata.org/wiki/Q47528","display_name":"Radar","level":2,"score":0.534600019454956},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5019999742507935},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.4934999942779541},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4253000020980835},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.3991999924182892},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.3905999958515167},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.374099999666214},{"id":"https://openalex.org/C57493831","wikidata":"https://www.wikidata.org/wiki/Q3134666","display_name":"Projection (relational algebra)","level":2,"score":0.3456000089645386},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.3305000066757202},{"id":"https://openalex.org/C117623542","wikidata":"https://www.wikidata.org/wiki/Q621974","display_name":"Automatic target recognition","level":3,"score":0.323199987411499},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.319599986076355},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.3158000111579895},{"id":"https://openalex.org/C100675267","wikidata":"https://www.wikidata.org/wiki/Q1371624","display_name":"Background noise","level":2,"score":0.31029999256134033},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.29280000925064087},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2863999903202057},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.272599995136261},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.26429998874664307},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.2639000117778778}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3817124.3817202","doi":"https://doi.org/10.1145/3817124.3817202","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3817124.3817202","pdf_url":null,"source":{"id":"https://openalex.org/S4363607990","display_name":"International Conference on Applied Mathematics, Modelling and Intelligent Computing (CAMMIC)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2026 6th International Conference on Applied Mathematics, Modelling and Intelligent Computing","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3817124.3817202","doi":"https://doi.org/10.1145/3817124.3817202","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3817124.3817202","pdf_url":null,"source":{"id":"https://openalex.org/S4363607990","display_name":"International Conference on Applied Mathematics, Modelling and Intelligent Computing (CAMMIC)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2026 6th International Conference on Applied Mathematics, Modelling and Intelligent Computing","raw_type":"proceedings-article"},"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":19,"referenced_works":["https://openalex.org/W2124712881","https://openalex.org/W2147771380","https://openalex.org/W2507782627","https://openalex.org/W2752782242","https://openalex.org/W2939570633","https://openalex.org/W3035911592","https://openalex.org/W3162991540","https://openalex.org/W4296917809","https://openalex.org/W4385465023","https://openalex.org/W4385763767","https://openalex.org/W4387845821","https://openalex.org/W4388976284","https://openalex.org/W4392583682","https://openalex.org/W4402265374","https://openalex.org/W4404490408","https://openalex.org/W4405488021","https://openalex.org/W4409709180","https://openalex.org/W7118161194","https://openalex.org/W7125777404"],"related_works":["https://openalex.org/W4412692405","https://openalex.org/W4296441316","https://openalex.org/W4404592658","https://openalex.org/W4361019939","https://openalex.org/W3021012660","https://openalex.org/W4409709180","https://openalex.org/W4402744172","https://openalex.org/W4306965295","https://openalex.org/W2910615677","https://openalex.org/W4319586725"],"abstract_inverted_index":{"High-resolution":[0],"range":[1],"profile":[2],"(HRRP)":[3],"is":[4,27,51,211],"a":[5,15,28,92,103,118,148],"one-dimensional":[6],"radar":[7,21,32],"signature":[8],"that":[9,154],"compactly":[10],"encodes":[11],"the":[12,20,81,96,110,163,183,198,202],"projection":[13],"of":[14,23,86,126,182,201],"target's":[16],"scattering":[17,84],"centres":[18],"along":[19],"line":[22],"sight.":[24],"HRRP":[25,151,226],"recognition":[26,35],"core":[29],"task":[30],"in":[31,39],"automatic":[33],"target":[34,227],"(ATR),":[36],"widely":[37],"used":[38],"air-defence":[40],"surveillance,":[41],"space":[42],"situational":[43],"awareness,":[44],"and":[45,59,77,102,129,135,188,205,221],"maritime":[46],"monitoring.":[47],"However,":[48],"HRRP-based":[49],"classification":[50],"restricted":[52],"by":[53],"three":[54],"typical":[55],"sensitivities:":[56],"aspect,":[57],"translation,":[58],"amplitude,":[60],"as":[61,63],"well":[62],"strong":[64,214],"susceptibility":[65],"to":[66,79,109,141],"noise.":[67],"Meanwhile,":[68],"most":[69],"existing":[70],"deep":[71],"learning":[72],"methods":[73],"adopt":[74],"single-scale":[75],"convolutions":[76],"fail":[78],"capture":[80],"inherent":[82],"multi-scale":[83,132],"structures":[85],"complex":[87],"targets.":[88],"This":[89],"paper":[90],"conducts":[91],"progressive":[93],"study":[94],"from":[95,191],"Support":[97],"Vector":[98],"Machine":[99],"(SVM)":[100],"baseline":[101],"basic":[104],"Convolutional":[105],"Neural":[106],"Network":[107,114],"(BasicCNN)":[108],"proposed":[111,209],"Multi-Scale":[112],"Attention":[113],"(MSA-Net).":[115],"MSA-Net":[116,156,176],"integrates":[117],"Multi-Branch":[119],"Convolution":[120],"(MBC)":[121],"module":[122],"with":[123,213],"parallel":[124],"kernels":[125],"3,":[127],"7,":[128],"15":[130],"for":[131,224],"feature":[133],"extraction,":[134],"combines":[136],"Squeeze-and-Excitation":[137],"(SE)":[138],"attention":[139],"blocks":[140],"achieve":[142],"adaptive":[143],"channel":[144],"recalibration.":[145],"Experiments":[146],"on":[147],"five-class":[149],"simulated":[150],"dataset":[152],"show":[153],"although":[155],"achieves":[157],"slightly":[158],"lower":[159],"clean-data":[160,184],"accuracy":[161,179],"than":[162],"SVM":[164,187],"baseline,":[165],"it":[166,218],"exhibits":[167],"significantly":[168],"stronger":[169],"noise":[170,173,215],"robustness.":[171],"As":[172],"intensity":[174],"increases,":[175],"can":[177],"maintain":[178],"above":[180],"80%":[181],"level,":[185],"while":[186],"BasicCNN":[189],"suffer":[190],"catastrophic":[192],"performance":[193],"degradation.":[194],"Ablation":[195],"studies":[196],"verify":[197],"complementary":[199],"effects":[200],"SE":[203],"mechanism":[204],"multi-branch":[206],"convolution.":[207],"The":[208],"model":[210],"lightweight":[212],"robustness,":[216],"making":[217],"an":[219],"effective":[220],"practical":[222],"solution":[223],"real-world":[225],"recognition.":[228]},"counts_by_year":[],"updated_date":"2026-10-28T10:33:24.094632","created_date":"2026-09-01T00:00:00"}
