{"id":"https://openalex.org/W2935707394","doi":"https://doi.org/10.3390/sym11040540","title":"LPI Radar Waveform Recognition Based on Deep Convolutional Neural Network Transfer Learning","display_name":"LPI Radar Waveform Recognition Based on Deep Convolutional Neural Network Transfer Learning","publication_year":2019,"publication_date":"2019-04-15","ids":{"openalex":"https://openalex.org/W2935707394","doi":"https://doi.org/10.3390/sym11040540","mag":"2935707394"},"language":"en","primary_location":{"id":"doi:10.3390/sym11040540","is_oa":true,"landing_page_url":"https://doi.org/10.3390/sym11040540","pdf_url":"https://www.mdpi.com/2073-8994/11/4/540/pdf?version=1555320232","source":{"id":"https://openalex.org/S190787756","display_name":"Symmetry","issn_l":"2073-8994","issn":["2073-8994"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Symmetry","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/2073-8994/11/4/540/pdf?version=1555320232","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5082950831","display_name":"Qiang Guo","orcid":"https://orcid.org/0000-0002-8366-7163"},"institutions":[{"id":"https://openalex.org/I151727225","display_name":"Harbin Engineering University","ror":"https://ror.org/03x80pn82","country_code":"CN","type":"education","lineage":["https://openalex.org/I151727225"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qiang Guo","raw_affiliation_strings":["College of Information and Telecommunication, Harbin Engineering University, Harbin 150001, China"],"affiliations":[{"raw_affiliation_string":"College of Information and Telecommunication, Harbin Engineering University, Harbin 150001, China","institution_ids":["https://openalex.org/I151727225"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100655674","display_name":"Xin Yu","orcid":"https://orcid.org/0000-0002-1474-9851"},"institutions":[{"id":"https://openalex.org/I151727225","display_name":"Harbin Engineering University","ror":"https://ror.org/03x80pn82","country_code":"CN","type":"education","lineage":["https://openalex.org/I151727225"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xin Yu","raw_affiliation_strings":["College of Information and Telecommunication, Harbin Engineering University, Harbin 150001, China"],"affiliations":[{"raw_affiliation_string":"College of Information and Telecommunication, Harbin Engineering University, Harbin 150001, China","institution_ids":["https://openalex.org/I151727225"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5018040958","display_name":"Guoqing Ruan","orcid":"https://orcid.org/0000-0001-6746-7471"},"institutions":[{"id":"https://openalex.org/I2800372957","display_name":"China Electronics Technology Group Corporation","ror":"https://ror.org/0098hst83","country_code":"CN","type":"company","lineage":["https://openalex.org/I2800372957"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guoqing Ruan","raw_affiliation_strings":["Key Laboratory of Information System Engineering, The 28th Research Institute of China Electronics Technology Group Corporation, Nanjing 210014, China"],"affiliations":[{"raw_affiliation_string":"Key Laboratory of Information System Engineering, The 28th Research Institute of China Electronics Technology Group Corporation, Nanjing 210014, China","institution_ids":["https://openalex.org/I2800372957"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5100655674"],"corresponding_institution_ids":["https://openalex.org/I151727225"],"apc_list":{"value":2000,"currency":"CHF","value_usd":2165},"apc_paid":{"value":2000,"currency":"CHF","value_usd":2165},"fwci":4.6201,"has_fulltext":true,"cited_by_count":63,"citation_normalized_percentile":{"value":0.95760967,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":100},"biblio":{"volume":"11","issue":"4","first_page":"540","last_page":"540"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12131","display_name":"Wireless Signal Modulation Classification","score":0.9994000196456909,"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":0.9994000196456909,"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":0.994700014591217,"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/T11609","display_name":"Geophysical Methods and Applications","score":0.9830999970436096,"subfield":{"id":"https://openalex.org/subfields/2212","display_name":"Ocean 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":0.7174224853515625},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6667462587356567},{"id":"https://openalex.org/keywords/radar","display_name":"Radar","score":0.6140912175178528},{"id":"https://openalex.org/keywords/waveform","display_name":"Waveform","score":0.5849152207374573},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5705444812774658},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5351522564888},{"id":"https://openalex.org/keywords/low-probability-of-intercept-radar","display_name":"Low probability of intercept radar","score":0.5258859992027283},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.487989604473114},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.4696815609931946},{"id":"https://openalex.org/keywords/automatic-target-recognition","display_name":"Automatic target recognition","score":0.4423469007015228},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.4156973361968994},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4028976559638977},{"id":"https://openalex.org/keywords/radar-imaging","display_name":"Radar imaging","score":0.36521369218826294},{"id":"https://openalex.org/keywords/continuous-wave-radar","display_name":"Continuous-wave radar","score":0.2497144341468811},{"id":"https://openalex.org/keywords/synthetic-aperture-radar","display_name":"Synthetic aperture radar","score":0.1530720293521881},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.15258225798606873}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7174224853515625},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6667462587356567},{"id":"https://openalex.org/C554190296","wikidata":"https://www.wikidata.org/wiki/Q47528","display_name":"Radar","level":2,"score":0.6140912175178528},{"id":"https://openalex.org/C197424946","wikidata":"https://www.wikidata.org/wiki/Q1165717","display_name":"Waveform","level":3,"score":0.5849152207374573},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5705444812774658},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5351522564888},{"id":"https://openalex.org/C147345108","wikidata":"https://www.wikidata.org/wiki/Q6693040","display_name":"Low probability of intercept radar","level":5,"score":0.5258859992027283},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.487989604473114},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.4696815609931946},{"id":"https://openalex.org/C117623542","wikidata":"https://www.wikidata.org/wiki/Q621974","display_name":"Automatic target recognition","level":3,"score":0.4423469007015228},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.4156973361968994},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4028976559638977},{"id":"https://openalex.org/C10929652","wikidata":"https://www.wikidata.org/wiki/Q7279985","display_name":"Radar imaging","level":3,"score":0.36521369218826294},{"id":"https://openalex.org/C59584813","wikidata":"https://www.wikidata.org/wiki/Q1029234","display_name":"Continuous-wave radar","level":4,"score":0.2497144341468811},{"id":"https://openalex.org/C87360688","wikidata":"https://www.wikidata.org/wiki/Q740686","display_name":"Synthetic aperture radar","level":2,"score":0.1530720293521881},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.15258225798606873}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.3390/sym11040540","is_oa":true,"landing_page_url":"https://doi.org/10.3390/sym11040540","pdf_url":"https://www.mdpi.com/2073-8994/11/4/540/pdf?version=1555320232","source":{"id":"https://openalex.org/S190787756","display_name":"Symmetry","issn_l":"2073-8994","issn":["2073-8994"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Symmetry","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:1b187c4f965547709c35e766cfe09b42","is_oa":true,"landing_page_url":"https://doaj.org/article/1b187c4f965547709c35e766cfe09b42","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Symmetry, Vol 11, Iss 4, p 540 (2019)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/2073-8994/11/4/540/","is_oa":true,"landing_page_url":"http://dx.doi.org/10.3390/sym11040540","pdf_url":null,"source":{"id":"https://openalex.org/S4306400947","display_name":"MDPI (MDPI AG)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210097602","host_organization_name":"Multidisciplinary Digital Publishing Institute (Switzerland)","host_organization_lineage":["https://openalex.org/I4210097602"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Symmetry","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/sym11040540","is_oa":true,"landing_page_url":"https://doi.org/10.3390/sym11040540","pdf_url":"https://www.mdpi.com/2073-8994/11/4/540/pdf?version=1555320232","source":{"id":"https://openalex.org/S190787756","display_name":"Symmetry","issn_l":"2073-8994","issn":["2073-8994"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Symmetry","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","score":0.46000000834465027,"display_name":"Reduced inequalities"}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2935707394.pdf","grobid_xml":"https://content.openalex.org/works/W2935707394.grobid-xml"},"referenced_works_count":30,"referenced_works":["https://openalex.org/W1986510668","https://openalex.org/W2027036699","https://openalex.org/W2062284305","https://openalex.org/W2097117768","https://openalex.org/W2112796928","https://openalex.org/W2117539524","https://openalex.org/W2130014182","https://openalex.org/W2153816607","https://openalex.org/W2165698076","https://openalex.org/W2172171145","https://openalex.org/W2183341477","https://openalex.org/W2183843206","https://openalex.org/W2341088134","https://openalex.org/W2395579298","https://openalex.org/W2531162019","https://openalex.org/W2586095846","https://openalex.org/W2591880439","https://openalex.org/W2614570116","https://openalex.org/W2624887404","https://openalex.org/W2781731889","https://openalex.org/W2806977582","https://openalex.org/W2885478230","https://openalex.org/W2900530921","https://openalex.org/W2901565938","https://openalex.org/W2902045507","https://openalex.org/W2902686731","https://openalex.org/W2906302663","https://openalex.org/W2963400281","https://openalex.org/W6756010087","https://openalex.org/W6757703106"],"related_works":["https://openalex.org/W1974895211","https://openalex.org/W2129841057","https://openalex.org/W3040712279","https://openalex.org/W2176409448","https://openalex.org/W293646134","https://openalex.org/W2464278922","https://openalex.org/W2519990920","https://openalex.org/W2887270943","https://openalex.org/W2292882608","https://openalex.org/W2085211552"],"abstract_inverted_index":{"Low":[0],"Probability":[1],"of":[2,14,33,45,113,141,153,165,176],"Intercept":[3],"(LPI)":[4],"radar":[5,27,35,81,142,157],"waveform":[6,36,82],"recognition":[7,37,52,140,151,174],"is":[8,66,185],"not":[9],"only":[10],"an":[11,21,48],"important":[12,22],"branch":[13],"the":[15,31,72,79,90,93,100,103,107,114,122,149,154,166,172,177,183],"electronic":[16],"reconnaissance":[17],"field,":[18],"but":[19],"also":[20],"means":[23],"to":[24,83,106,127,134],"obtain":[25,84],"non-cooperative":[26],"information.":[28],"To":[29],"solve":[30],"problems":[32],"LPI":[34,80,156],"rate,":[38],"difficult":[39],"feature":[40,119],"extraction":[41],"and":[42,51,59,138,163,171],"large":[43],"number":[44],"samples":[46],"needed,":[47],"automatic":[49],"classification":[50],"system":[53,73,91,101,168,179],"based":[54],"on":[55,78],"Choi-Williams":[56],"distribution":[57],"(CWD)":[58],"depth":[60],"convolution":[61,116],"neural":[62],"network":[63,117],"migration":[64],"learning":[65],"proposed":[67],"in":[68],"this":[69],"paper.":[70],"First,":[71],"performs":[74],"CWD":[75],"time-frequency":[76,87,95],"transform":[77],"a":[85,128],"2-D":[86],"image.":[88,96],"Then":[89],"preprocesses":[92],"original":[94],"In":[97],"addition,":[98],"then":[99],"sends":[102],"pre-processed":[104],"image":[105],"pre-training":[108],"model":[109],"(Inception-v3":[110],"or":[111],"ResNet-152)":[112],"deep":[115],"for":[118],"extraction.":[120],"Finally,":[121],"extracted":[123],"features":[124],"are":[125],"sent":[126],"Support":[129],"Vector":[130],"Machine":[131],"(SVM)":[132],"classifier":[133],"realize":[135],"offline":[136],"training":[137],"online":[139],"waveforms.":[143],"The":[144],"simulation":[145],"results":[146],"show":[147],"that":[148],"overall":[150,173],"rate":[152,175],"eight":[155],"signals":[158],"(LFM,":[159],"BPSK,":[160],"Costas,":[161],"Frank,":[162],"T1\u2013T4)":[164],"ResNet-152-SVM":[167],"reaches":[169,180],"97.8%,":[170],"Inception-v3-SVM":[178],"96.2%":[181],"when":[182],"SNR":[184],"\u22122":[186],"dB.":[187]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":6},{"year":2024,"cited_by_count":13},{"year":2023,"cited_by_count":10},{"year":2022,"cited_by_count":13},{"year":2021,"cited_by_count":10},{"year":2020,"cited_by_count":9}],"updated_date":"2026-03-09T08:58:05.943551","created_date":"2025-10-10T00:00:00"}
