{"id":"https://openalex.org/W4406356535","doi":"https://doi.org/10.1109/wcsp62071.2024.10826867","title":"A Multi-Feature Time-Series Data Generation Method for LEO Electromagnetic Monitoring Systems","display_name":"A Multi-Feature Time-Series Data Generation Method for LEO Electromagnetic Monitoring Systems","publication_year":2024,"publication_date":"2024-10-24","ids":{"openalex":"https://openalex.org/W4406356535","doi":"https://doi.org/10.1109/wcsp62071.2024.10826867"},"language":"en","primary_location":{"id":"doi:10.1109/wcsp62071.2024.10826867","is_oa":false,"landing_page_url":"https://doi.org/10.1109/wcsp62071.2024.10826867","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 16th International Conference on Wireless Communications and Signal Processing (WCSP)","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":"https://openalex.org/A5032150204","display_name":"Yuxuan Yang","orcid":"https://orcid.org/0009-0004-0906-7292"},"institutions":[{"id":"https://openalex.org/I4210158522","display_name":"PLA Academy of Military Science","ror":"https://ror.org/05ct4s596","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210158522"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuxuan Yang","raw_affiliation_strings":["Academy of Military Sciences, People&#x0027;s Liberation Army,Beijing,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Academy of Military Sciences, People&#x0027;s Liberation Army,Beijing,China","institution_ids":["https://openalex.org/I4210158522"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101418812","display_name":"Boyu Deng","orcid":"https://orcid.org/0000-0001-9491-9795"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Boyu Deng","raw_affiliation_strings":["Tsinghua University,Beijing,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tsinghua University,Beijing,China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5028904438","display_name":"Jingchao Wang","orcid":"https://orcid.org/0000-0003-1848-320X"},"institutions":[{"id":"https://openalex.org/I4210158522","display_name":"PLA Academy of Military Science","ror":"https://ror.org/05ct4s596","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210158522"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jingchao Wang","raw_affiliation_strings":["Academy of Military Sciences, People&#x0027;s Liberation Army,Beijing,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Academy of Military Sciences, People&#x0027;s Liberation Army,Beijing,China","institution_ids":["https://openalex.org/I4210158522"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101729856","display_name":"Ji\u2010Zheng Sun","orcid":"https://orcid.org/0000-0002-4018-1753"},"institutions":[{"id":"https://openalex.org/I4210158522","display_name":"PLA Academy of Military Science","ror":"https://ror.org/05ct4s596","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210158522"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jizheng Sun","raw_affiliation_strings":["Academy of Military Sciences, People&#x0027;s Liberation Army,Beijing,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Academy of Military Sciences, People&#x0027;s Liberation Army,Beijing,China","institution_ids":["https://openalex.org/I4210158522"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100733953","display_name":"Tuo Yang","orcid":"https://orcid.org/0009-0000-3310-1981"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tuo Yang","raw_affiliation_strings":["Xidian University,Xian,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Xidian University,Xian,China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100662557","display_name":"Xiaoyu Zhang","orcid":"https://orcid.org/0000-0003-1436-8116"},"institutions":[{"id":"https://openalex.org/I4210158522","display_name":"PLA Academy of Military Science","ror":"https://ror.org/05ct4s596","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210158522"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaoyu Zhang","raw_affiliation_strings":["Academy of Military Sciences, People&#x0027;s Liberation Army,Beijing,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Academy of Military Sciences, People&#x0027;s Liberation Army,Beijing,China","institution_ids":["https://openalex.org/I4210158522"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"782","last_page":"788"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T14163","display_name":"Astronomical Observations and Instrumentation","score":0.9344000220298767,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"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/T14163","display_name":"Astronomical Observations and Instrumentation","score":0.9344000220298767,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"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/series","display_name":"Series (stratigraphy)","score":0.7237922549247742},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6827154159545898},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.5901440978050232},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5691593885421753},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.10703134536743164},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.0970902144908905}],"concepts":[{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.7237922549247742},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6827154159545898},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.5901440978050232},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5691593885421753},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.10703134536743164},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.0970902144908905},{"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/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/wcsp62071.2024.10826867","is_oa":false,"landing_page_url":"https://doi.org/10.1109/wcsp62071.2024.10826867","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 16th International Conference on Wireless Communications and Signal Processing (WCSP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.5699999928474426,"display_name":"Affordable and clean energy","id":"https://metadata.un.org/sdg/7"}],"awards":[{"id":"https://openalex.org/G2002952674","display_name":null,"funder_award_id":"62101587","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":11,"referenced_works":["https://openalex.org/W1901129140","https://openalex.org/W2125389028","https://openalex.org/W2515503816","https://openalex.org/W2752782242","https://openalex.org/W2963470893","https://openalex.org/W2963767194","https://openalex.org/W3167297489","https://openalex.org/W6685352114","https://openalex.org/W6729482032","https://openalex.org/W6735913928","https://openalex.org/W6741832134"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W4391913857","https://openalex.org/W2358668433","https://openalex.org/W2119012848","https://openalex.org/W2622688551","https://openalex.org/W1550175370","https://openalex.org/W1990205660"],"abstract_inverted_index":{"Low":[0],"Earth":[1],"Orbit":[2],"(LEO)":[3],"electromagnetic":[4,69],"monitoring":[5],"systems":[6],"face":[7],"challenges":[8],"in":[9,15,77,91,113,134],"signal":[10,26,70],"acquisition":[11],"and":[12,41,75,105,116,138],"data":[13,46,78],"scarcity":[14],"typical":[16],"scenarios.":[17],"To":[18],"address":[19],"this":[20],"issue,":[21],"we":[22],"propose":[23],"an":[24],"electromag-netic":[25],"generation":[27,66],"model":[28,36,109,128],"based":[29],"on":[30],"Generative":[31],"Adversarial":[32],"Networks":[33],"(GANs).":[34],"This":[35],"synergistically":[37],"combines":[38],"UNet,":[39],"SENet,":[40],"BiLSTM":[42],"architectures,":[43],"approaching":[44],"multi-feature":[45],"as":[47],"a":[48,54],"multitask":[49],"learning":[50],"challenge.":[51],"By":[52],"leveraging":[53],"mask":[55],"vector":[56],"to":[57],"regulate":[58],"the":[59,64,82,92,107,123],"training":[60],"process,":[61],"it":[62],"enables":[63],"parallel":[65],"of":[67,131,136],"high-fidelity":[68],"data,":[71],"ensuring":[72],"both":[73,103,114],"efficiency":[74],"precision":[76],"synthesis.":[79],"We":[80],"validated":[81],"model's":[83],"effectiveness":[84],"by":[85,126],"simulating":[86],"LEO":[87],"satellite":[88],"signals":[89,124],"reception":[90],"constructed":[93],"virtual":[94],"environment.":[95],"Compared":[96],"with":[97],"other":[98],"conditional":[99],"GAN":[100],"architectures":[101],"for":[102],"generators":[104],"discriminators,":[106],"proposed":[108],"exhibits":[110],"superior":[111],"performance":[112],"qualitative":[115],"quantitative":[117],"analyses.":[118],"Experimental":[119],"results":[120],"demonstrate":[121],"that":[122],"generated":[125],"our":[127],"outperform":[129],"those":[130],"existing":[132],"models":[133],"terms":[135],"similarity":[137],"fidelity.":[139]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
