{"id":"https://openalex.org/W3127701791","doi":"https://doi.org/10.1109/access.2021.3058305","title":"LPI Radar Waveform Recognition Based on Multi-Resolution Deep Feature Fusion","display_name":"LPI Radar Waveform Recognition Based on Multi-Resolution Deep Feature Fusion","publication_year":2021,"publication_date":"2021-01-01","ids":{"openalex":"https://openalex.org/W3127701791","doi":"https://doi.org/10.1109/access.2021.3058305","mag":"3127701791"},"language":"en","primary_location":{"id":"doi:10.1109/access.2021.3058305","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2021.3058305","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/9312710/09350641.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://ieeexplore.ieee.org/ielx7/6287639/9312710/09350641.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101659937","display_name":"Xue Ni","orcid":"https://orcid.org/0000-0002-7524-3360"},"institutions":[{"id":"https://openalex.org/I4210163363","display_name":"PLA Army Engineering University","ror":"https://ror.org/05mgp8x93","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210163363"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xue Ni","raw_affiliation_strings":["College of Communications Engineering, Army Engineering University of PLA, Nanjing, China"],"raw_orcid":"https://orcid.org/0000-0002-7524-3360","affiliations":[{"raw_affiliation_string":"College of Communications Engineering, Army Engineering University of PLA, Nanjing, China","institution_ids":["https://openalex.org/I4210163363"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101869845","display_name":"Huali Wang","orcid":"https://orcid.org/0000-0003-2084-6110"},"institutions":[{"id":"https://openalex.org/I4210163363","display_name":"PLA Army Engineering University","ror":"https://ror.org/05mgp8x93","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210163363"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Huali Wang","raw_affiliation_strings":["College of Communications Engineering, Army Engineering University of PLA, Nanjing, China"],"raw_orcid":"https://orcid.org/0000-0003-2084-6110","affiliations":[{"raw_affiliation_string":"College of Communications Engineering, Army Engineering University of PLA, Nanjing, China","institution_ids":["https://openalex.org/I4210163363"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103151002","display_name":"Fan Meng","orcid":"https://orcid.org/0000-0002-4818-7009"},"institutions":[{"id":"https://openalex.org/I4210153872","display_name":"Jiangsu Maritime Institute","ror":"https://ror.org/04pekda06","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210153872"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Fan Meng","raw_affiliation_strings":["Nanjing Marine Radar Institute, Nanjing, China"],"raw_orcid":"https://orcid.org/0000-0002-4818-7009","affiliations":[{"raw_affiliation_string":"Nanjing Marine Radar Institute, Nanjing, China","institution_ids":["https://openalex.org/I4210153872"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5003645187","display_name":"Jing Hu","orcid":"https://orcid.org/0000-0001-5567-6911"},"institutions":[{"id":"https://openalex.org/I4210163363","display_name":"PLA Army Engineering University","ror":"https://ror.org/05mgp8x93","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210163363"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jing Hu","raw_affiliation_strings":["College of Communications Engineering, Army Engineering University of PLA, Nanjing, China"],"raw_orcid":"https://orcid.org/0000-0001-5567-6911","affiliations":[{"raw_affiliation_string":"College of Communications Engineering, Army Engineering University of PLA, Nanjing, China","institution_ids":["https://openalex.org/I4210163363"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5072031726","display_name":"Changkai Tong","orcid":"https://orcid.org/0000-0001-8705-093X"},"institutions":[{"id":"https://openalex.org/I4210163363","display_name":"PLA Army Engineering University","ror":"https://ror.org/05mgp8x93","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210163363"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Changkai Tong","raw_affiliation_strings":["College of Communications Engineering, Army Engineering University of PLA, Nanjing, China"],"raw_orcid":"https://orcid.org/0000-0001-8705-093X","affiliations":[{"raw_affiliation_string":"College of Communications Engineering, Army Engineering University of PLA, Nanjing, China","institution_ids":["https://openalex.org/I4210163363"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":3.4983,"has_fulltext":true,"cited_by_count":30,"citation_normalized_percentile":{"value":0.93620945,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":"9","issue":null,"first_page":"26138","last_page":"26146"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12131","display_name":"Wireless Signal Modulation Classification","score":0.9994999766349792,"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"}},"topics":[{"id":"https://openalex.org/T12131","display_name":"Wireless Signal Modulation Classification","score":0.9994999766349792,"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/T11038","display_name":"Advanced SAR Imaging Techniques","score":0.991100013256073,"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/T14117","display_name":"Integrated Circuits and Semiconductor Failure Analysis","score":0.9871000051498413,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic 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":0.7544018626213074},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7180318832397461},{"id":"https://openalex.org/keywords/radar","display_name":"Radar","score":0.605912446975708},{"id":"https://openalex.org/keywords/waveform","display_name":"Waveform","score":0.6045956611633301},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5995103120803833},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5770934224128723},{"id":"https://openalex.org/keywords/low-probability-of-intercept-radar","display_name":"Low probability of intercept radar","score":0.5202442407608032},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4878847599029541},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.4737566113471985},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.4479960799217224},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.43061283230781555},{"id":"https://openalex.org/keywords/fusion","display_name":"Fusion","score":0.4227350354194641},{"id":"https://openalex.org/keywords/jamming","display_name":"Jamming","score":0.4220961034297943},{"id":"https://openalex.org/keywords/radar-imaging","display_name":"Radar imaging","score":0.3541029691696167},{"id":"https://openalex.org/keywords/continuous-wave-radar","display_name":"Continuous-wave radar","score":0.26963821053504944},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.09938856959342957}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7544018626213074},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7180318832397461},{"id":"https://openalex.org/C554190296","wikidata":"https://www.wikidata.org/wiki/Q47528","display_name":"Radar","level":2,"score":0.605912446975708},{"id":"https://openalex.org/C197424946","wikidata":"https://www.wikidata.org/wiki/Q1165717","display_name":"Waveform","level":3,"score":0.6045956611633301},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5995103120803833},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5770934224128723},{"id":"https://openalex.org/C147345108","wikidata":"https://www.wikidata.org/wiki/Q6693040","display_name":"Low probability of intercept radar","level":5,"score":0.5202442407608032},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4878847599029541},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.4737566113471985},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.4479960799217224},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.43061283230781555},{"id":"https://openalex.org/C158525013","wikidata":"https://www.wikidata.org/wiki/Q2593739","display_name":"Fusion","level":2,"score":0.4227350354194641},{"id":"https://openalex.org/C2779079576","wikidata":"https://www.wikidata.org/wiki/Q17092823","display_name":"Jamming","level":2,"score":0.4220961034297943},{"id":"https://openalex.org/C10929652","wikidata":"https://www.wikidata.org/wiki/Q7279985","display_name":"Radar imaging","level":3,"score":0.3541029691696167},{"id":"https://openalex.org/C59584813","wikidata":"https://www.wikidata.org/wiki/Q1029234","display_name":"Continuous-wave radar","level":4,"score":0.26963821053504944},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.09938856959342957},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C97355855","wikidata":"https://www.wikidata.org/wiki/Q11473","display_name":"Thermodynamics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2021.3058305","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2021.3058305","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/9312710/09350641.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:0acff32a6b1e49c29435afaac4e6f4ef","is_oa":true,"landing_page_url":"https://doaj.org/article/0acff32a6b1e49c29435afaac4e6f4ef","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 9, Pp 26138-26146 (2021)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2021.3058305","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2021.3058305","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/9312710/09350641.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3127701791.pdf","grobid_xml":"https://content.openalex.org/works/W3127701791.grobid-xml"},"referenced_works_count":22,"referenced_works":["https://openalex.org/W1598868193","https://openalex.org/W2015861736","https://openalex.org/W2097117768","https://openalex.org/W2117539524","https://openalex.org/W2123506034","https://openalex.org/W2163630665","https://openalex.org/W2565639579","https://openalex.org/W2591459666","https://openalex.org/W2591880439","https://openalex.org/W2614570116","https://openalex.org/W2624887404","https://openalex.org/W2766793945","https://openalex.org/W2781731889","https://openalex.org/W2901054254","https://openalex.org/W2902978430","https://openalex.org/W2910123878","https://openalex.org/W2935707394","https://openalex.org/W2947560542","https://openalex.org/W2965265594","https://openalex.org/W2988343071","https://openalex.org/W3011402415","https://openalex.org/W3034682287"],"related_works":["https://openalex.org/W4200319726","https://openalex.org/W1984793747","https://openalex.org/W4312547492","https://openalex.org/W3197729047","https://openalex.org/W1974895211","https://openalex.org/W293646134","https://openalex.org/W2464278922","https://openalex.org/W2903871247","https://openalex.org/W2292882608","https://openalex.org/W2085211552"],"abstract_inverted_index":{"Deep":[0],"neural":[1],"networks":[2,36],"are":[3,37,119],"used":[4],"as":[5],"effective":[6,31],"methods":[7],"for":[8,53,106,140],"the":[9,30,35,61,132,154,165,179],"Low":[10],"Probability":[11],"of":[12,148,158,167],"Intercept":[13],"(LPI)":[14],"radar":[15,55,76,150],"waveform":[16,56],"recognition.":[17,57],"However,":[18],"existing":[19],"models\u2019":[20],"performance":[21,70],"degrades":[22],"seriously":[23],"at":[24,71,164,183],"low":[25,72,184],"Signal-to-Noise":[26],"Ratios":[27],"(SNRs)":[28],"because":[29],"features":[32,93,118],"extracted":[33],"by":[34],"insufficient":[38],"under":[39],"noise":[40],"jamming.":[41],"In":[42],"this":[43],"paper,":[44],"we":[45,59,82,99,126],"propose":[46],"a":[47,84,128],"multi-resolution":[48,85],"deep":[49,86,92,107],"feature":[50,103,108],"fusion":[51,104,129,139],"method":[52,160],"LPI":[54,149],"First,":[58],"apply":[60,127],"enhanced":[62],"Fourier-based":[63],"Synchrosqueezing":[64],"Transform":[65],"(FSST),":[66],"which":[67],"shows":[68],"good":[69],"SNRs,":[73],"to":[74,89,121,131,136],"convert":[75],"signals":[77],"into":[78],"time-frequency":[79],"images.":[80],"Then,":[81],"construct":[83],"convolutional":[87],"network":[88],"extract":[90],"more":[91],"from":[94],"each":[95],"resolution":[96,117],"channel.":[97],"Next,":[98],"explore":[100],"an":[101],"interactive":[102],"strategy":[105],"fusion.":[109],"By":[110],"some":[111],"down-sampling":[112],"or":[113],"up-sampling":[114],"blocks,":[115],"different":[116],"fused":[120],"generate":[122],"new":[123],"features.":[124],"Finally,":[125],"algorithm":[130],"fully":[133],"connected":[134],"layer":[135],"achieve":[137],"classification":[138],"better":[141],"performance.":[142],"Simulation":[143],"experiments":[144],"on":[145],"twelve":[146],"kinds":[147],"waveforms":[151],"show":[152],"that":[153,173],"overall":[155],"recognition":[156,180],"accuracy":[157,181],"our":[159,174],"can":[161],"reach":[162],"95.2%":[163],"SNR":[166],"\u22128":[168],"dB.":[169],"It":[170],"is":[171],"proved":[172],"approach":[175],"does":[176],"indeed":[177],"improve":[178],"effectively":[182],"SNRs.":[185]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":9},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":10},{"year":2021,"cited_by_count":2}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}