{"id":"https://openalex.org/W7084097177","doi":"https://doi.org/10.1109/bmsb65076.2025.11165560","title":"Radio-Frequency-Based Unmanned-Aerial-Vehicle Identification Using Cyclic-Paw-Print","display_name":"Radio-Frequency-Based Unmanned-Aerial-Vehicle Identification Using Cyclic-Paw-Print","publication_year":2025,"publication_date":"2025-06-11","ids":{"openalex":"https://openalex.org/W7084097177","doi":"https://doi.org/10.1109/bmsb65076.2025.11165560"},"language":"en","primary_location":{"id":"doi:10.1109/bmsb65076.2025.11165560","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bmsb65076.2025.11165560","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Symposium on Broadband Multimedia Systems and Broadcasting (BMSB)","raw_type":"proceedings-article"},"type":"conference-paper","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":"Xiao Yan","orcid":null},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]},{"id":"https://openalex.org/I9842412","display_name":"Nanjing University of Aeronautics and Astronautics","ror":"https://ror.org/01scyh794","country_code":"CN","type":"education","lineage":["https://openalex.org/I9842412"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiao Yan","raw_affiliation_strings":["University of Electronic Science and Technology of China,School of Aeronautics and Astronautics,Chengdu,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Electronic Science and Technology of China,School of Aeronautics and Astronautics,Chengdu,China","institution_ids":["https://openalex.org/I150229711","https://openalex.org/I9842412"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Minghui Zhao","orcid":null},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]},{"id":"https://openalex.org/I9842412","display_name":"Nanjing University of Aeronautics and Astronautics","ror":"https://ror.org/01scyh794","country_code":"CN","type":"education","lineage":["https://openalex.org/I9842412"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Minghui Zhao","raw_affiliation_strings":["University of Electronic Science and Technology of China,School of Aeronautics and Astronautics,Chengdu,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Electronic Science and Technology of China,School of Aeronautics and Astronautics,Chengdu,China","institution_ids":["https://openalex.org/I150229711","https://openalex.org/I9842412"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Qian Wang","orcid":null},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]},{"id":"https://openalex.org/I9842412","display_name":"Nanjing University of Aeronautics and Astronautics","ror":"https://ror.org/01scyh794","country_code":"CN","type":"education","lineage":["https://openalex.org/I9842412"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qian Wang","raw_affiliation_strings":["University of Electronic Science and Technology of China,School of Aeronautics and Astronautics,Chengdu,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Electronic Science and Technology of China,School of Aeronautics and Astronautics,Chengdu,China","institution_ids":["https://openalex.org/I150229711","https://openalex.org/I9842412"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Hsiao-Chun Wu","orcid":null},"institutions":[{"id":"https://openalex.org/I121820613","display_name":"Louisiana State University","ror":"https://ror.org/05ect4e57","country_code":"US","type":"education","lineage":["https://openalex.org/I121820613"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Hsiao-Chun Wu","raw_affiliation_strings":["Louisiana State University,School of Electrical Engineering and Computer Science,Baton Rouge,USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Louisiana State University,School of Electrical Engineering and Computer Science,Baton Rouge,USA","institution_ids":["https://openalex.org/I121820613"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Guannan Liu","orcid":null},"institutions":[{"id":"https://openalex.org/I51504820","display_name":"San Jose State University","ror":"https://ror.org/04qyvz380","country_code":"US","type":"education","lineage":["https://openalex.org/I51504820"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Guannan Liu","raw_affiliation_strings":["San Jose State University,Department of Applied Data Science,San Jose,USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"San Jose State University,Department of Applied Data Science,San Jose,USA","institution_ids":["https://openalex.org/I51504820"]}]},{"author_position":"last","author":{"id":null,"display_name":"Yiyan Wu","orcid":null},"institutions":[{"id":"https://openalex.org/I4210151552","display_name":"Communications Research Centre Canada","ror":"https://ror.org/05dybt340","country_code":"CA","type":"facility","lineage":["https://openalex.org/I4210151552"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Yiyan Wu","raw_affiliation_strings":["Communications Research Centre,Ottawa,Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Communications Research Centre,Ottawa,Canada","institution_ids":["https://openalex.org/I4210151552"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.6768,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.88588284,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":true,"primary_topic":{"id":"https://openalex.org/T12157","display_name":"Geochemistry and Geologic Mapping","score":0.6445000171661377,"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/T12157","display_name":"Geochemistry and Geologic Mapping","score":0.6445000171661377,"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/T13067","display_name":"Geological Modeling and Analysis","score":0.026599999517202377,"subfield":{"id":"https://openalex.org/subfields/1906","display_name":"Geochemistry and Petrology"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T14311","display_name":"Electrical and Electromagnetic Research","score":0.022600000724196434,"subfield":{"id":"https://openalex.org/subfields/3107","display_name":"Atomic and Molecular Physics, and Optics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/signal","display_name":"SIGNAL (programming language)","score":0.6714000105857849},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.5781000256538391},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5257999897003174},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4523000121116638},{"id":"https://openalex.org/keywords/monte-carlo-method","display_name":"Monte Carlo method","score":0.3718999922275543},{"id":"https://openalex.org/keywords/digital-signal","display_name":"Digital signal","score":0.3652999997138977}],"concepts":[{"id":"https://openalex.org/C2779843651","wikidata":"https://www.wikidata.org/wiki/Q7390335","display_name":"SIGNAL (programming language)","level":2,"score":0.6714000105857849},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6438999772071838},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.630299985408783},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.5781000256538391},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5257999897003174},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4767000079154968},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4523000121116638},{"id":"https://openalex.org/C19499675","wikidata":"https://www.wikidata.org/wiki/Q232207","display_name":"Monte Carlo method","level":2,"score":0.3718999922275543},{"id":"https://openalex.org/C52773712","wikidata":"https://www.wikidata.org/wiki/Q175022","display_name":"Digital signal","level":3,"score":0.3652999997138977},{"id":"https://openalex.org/C104267543","wikidata":"https://www.wikidata.org/wiki/Q208163","display_name":"Signal processing","level":3,"score":0.3644999861717224},{"id":"https://openalex.org/C13944312","wikidata":"https://www.wikidata.org/wiki/Q7512748","display_name":"Signal-to-noise ratio (imaging)","level":2,"score":0.28450000286102295},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.27160000801086426},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.25519999861717224}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bmsb65076.2025.11165560","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bmsb65076.2025.11165560","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Symposium on Broadband Multimedia Systems and Broadcasting (BMSB)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320329861","display_name":"Natural Science Foundation of Sichuan Province","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":22,"referenced_works":["https://openalex.org/W2797804613","https://openalex.org/W2798636681","https://openalex.org/W2960206217","https://openalex.org/W2962751492","https://openalex.org/W2963125010","https://openalex.org/W2996046992","https://openalex.org/W2999373287","https://openalex.org/W2999472659","https://openalex.org/W3011187591","https://openalex.org/W3040963246","https://openalex.org/W3191940264","https://openalex.org/W4213019189","https://openalex.org/W4280583770","https://openalex.org/W4282970004","https://openalex.org/W4289656326","https://openalex.org/W4292387473","https://openalex.org/W4294982462","https://openalex.org/W4313148215","https://openalex.org/W4324116547","https://openalex.org/W4387934904","https://openalex.org/W4391165323","https://openalex.org/W4394811159"],"related_works":[],"abstract_inverted_index":{"A":[0],"novel":[1],"robust":[2],"unmanned":[3],"aerial":[4],"vehicle":[5],"(UAV)":[6],"identification":[7,142],"approach":[8,143],"using":[9],"our":[10,138],"recently":[11],"proposed":[12,139],"cyclic-paw-print":[13,94],"(CPP)":[14,95],"features":[15],"extracted":[16],"from":[17],"the":[18,84,93,98,107,111,118,123,134],"radio-frequency":[19,36],"(RF)":[20,37],"signals":[21,121],"is":[22,59,74,88,114],"presented":[23],"in":[24,144],"this":[25,33],"paper":[26],"for":[27],"air-traffic":[28],"surveillance":[29],"and":[30,45,49,62],"control.":[31],"In":[32],"work,":[34],"a":[35,41,50,57],"signal":[38,48,54,80],"such":[39],"as":[40,110],"UAV":[42,58,141],"telemetry,":[43],"track,":[44],"command":[46],"(TT&C)":[47],"digital":[51],"data-transmission":[52],"(DDT)":[53],"emitted":[55],"by":[56],"first":[60],"received":[61],"segmented":[63],"according":[64],"to":[65,76,82,91,116],"its":[66],"short-time":[67],"energy-to-spectral-entropy":[68],"ratio":[69],"(ST-ESER).":[70],"Next,":[71],"cyclic-spectrum":[72],"analysis":[73],"applied":[75],"each":[77],"selected":[78],"RF":[79,120],"segment":[81],"form":[83],"corresponding":[85,124],"polyspectrum,":[86],"which":[87,105],"further":[89],"utilized":[90],"establish":[92],"matrices.":[96],"Finally,":[97],"lightweight":[99],"convolutional":[100],"neural":[101],"network,":[102],"namely":[103],"ResNet-18,":[104],"takes":[106],"produced":[108],"CPPs":[109],"input":[112],"features,":[113],"trained":[115],"recognize":[117],"aforementioned":[119],"so":[122],"UAVs":[125],"can":[126],"be":[127],"identified.":[128],"Monte":[129],"Carlo":[130],"simulation":[131],"results":[132],"demonstrate":[133],"superior":[135],"effectiveness":[136],"of":[137],"new":[140],"comparison":[145],"with":[146],"other":[147],"existing":[148],"deep-learning":[149],"methods.":[150]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}