{"id":"https://openalex.org/W4417131224","doi":"https://doi.org/10.1109/lcomm.2025.3641829","title":"A Robust WIFI Localization Method for Indoor Dynamic Scenes","display_name":"A Robust WIFI Localization Method for Indoor Dynamic Scenes","publication_year":2025,"publication_date":"2025-12-08","ids":{"openalex":"https://openalex.org/W4417131224","doi":"https://doi.org/10.1109/lcomm.2025.3641829"},"language":null,"primary_location":{"id":"doi:10.1109/lcomm.2025.3641829","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lcomm.2025.3641829","pdf_url":null,"source":{"id":"https://openalex.org/S147316732","display_name":"IEEE Communications Letters","issn_l":"1089-7798","issn":["1089-7798","1558-2558","2373-7891"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310316002","host_organization_name":"IEEE Communications Society","host_organization_lineage":["https://openalex.org/P4310316002","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Communications Society","Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Communications Letters","raw_type":"journal-article"},"type":"article","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/A5100716194","display_name":"Jian Sun","orcid":"https://orcid.org/0000-0003-4696-3104"},"institutions":[{"id":"https://openalex.org/I198357462","display_name":"Changsha University","ror":"https://ror.org/011d8sm39","country_code":"CN","type":"education","lineage":["https://openalex.org/I198357462"]},{"id":"https://openalex.org/I56934997","display_name":"Changsha University of Science and Technology","ror":"https://ror.org/03yph8055","country_code":"CN","type":"education","lineage":["https://openalex.org/I56934997"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Jian Sun","raw_affiliation_strings":["School of Artificial Intelligence, Changsha University of Science and Technology, Changsha, China"],"raw_orcid":"https://orcid.org/0000-0003-4696-3104","affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, Changsha University of Science and Technology, Changsha, China","institution_ids":["https://openalex.org/I56934997","https://openalex.org/I198357462"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100637917","display_name":"Wei Sun","orcid":"https://orcid.org/0000-0002-8644-2998"},"institutions":[{"id":"https://openalex.org/I4210121405","display_name":"Centre for Artificial Intelligence and Robotics","ror":"https://ror.org/01xnbq218","country_code":"IN","type":"facility","lineage":["https://openalex.org/I1340206300","https://openalex.org/I4210121405","https://openalex.org/I4210150591"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Wei Sun","raw_affiliation_strings":["School of Artificial Intelligence and Robotics, Hunan University, Changsha, China"],"raw_orcid":"https://orcid.org/0000-0002-8644-2998","affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence and Robotics, Hunan University, Changsha, China","institution_ids":["https://openalex.org/I4210121405"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5037559337","display_name":"Genwei Zhang","orcid":"https://orcid.org/0000-0002-4432-220X"},"institutions":[{"id":"https://openalex.org/I4210157236","display_name":"National Institute for Radiological Protection","ror":"https://ror.org/05whjqq05","country_code":"CN","type":"government","lineage":["https://openalex.org/I184490438","https://openalex.org/I4210127390","https://openalex.org/I4210151987","https://openalex.org/I4210157236"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Genwei Zhang","raw_affiliation_strings":["State Key Laboratory of Chemistry for NBC Hazards Protection, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Chemistry for NBC Hazards Protection, Beijing, China","institution_ids":["https://openalex.org/I4210157236"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5029706116","display_name":"Chenjun Tang","orcid":"https://orcid.org/0000-0001-5719-1459"},"institutions":[{"id":"https://openalex.org/I4210122501","display_name":"Hunan Xiangdian Test Research Institute (China)","ror":"https://ror.org/0391pty66","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210122501"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chenjun Tang","raw_affiliation_strings":["Hunan Xiangke Technology Research Institute Company Ltd., Changsha, China","Hunan Xiangke Technology Research Institute Co., Ltd, Changsha, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Hunan Xiangke Technology Research Institute Company Ltd., Changsha, China","institution_ids":["https://openalex.org/I4210122501"]},{"raw_affiliation_string":"Hunan Xiangke Technology Research Institute Co., Ltd, Changsha, China","institution_ids":["https://openalex.org/I4210122501"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5056640073","display_name":"Song Li","orcid":"https://orcid.org/0000-0002-8467-9262"},"institutions":[{"id":"https://openalex.org/I16609230","display_name":"Hunan University","ror":"https://ror.org/05htk5m33","country_code":"CN","type":"education","lineage":["https://openalex.org/I16609230"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Song Li","raw_affiliation_strings":["National Engineering Research Center of Robot Visual Perception and Control Technology, Hunan University, Changsha, China"],"raw_orcid":"https://orcid.org/0000-0002-8467-9262","affiliations":[{"raw_affiliation_string":"National Engineering Research Center of Robot Visual Perception and Control Technology, Hunan University, Changsha, China","institution_ids":["https://openalex.org/I16609230"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100399141","display_name":"Xing Zhang","orcid":"https://orcid.org/0000-0002-7639-2704"},"institutions":[{"id":"https://openalex.org/I16609230","display_name":"Hunan University","ror":"https://ror.org/05htk5m33","country_code":"CN","type":"education","lineage":["https://openalex.org/I16609230"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xing Zhang","raw_affiliation_strings":["National Engineering Research Center of Robot Visual Perception and Control Technology, Hunan University, Changsha, China"],"raw_orcid":"https://orcid.org/0000-0002-7639-2704","affiliations":[{"raw_affiliation_string":"National Engineering Research Center of Robot Visual Perception and Control Technology, Hunan University, Changsha, China","institution_ids":["https://openalex.org/I16609230"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5100716194"],"corresponding_institution_ids":["https://openalex.org/I198357462","https://openalex.org/I56934997"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.37157356,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"30","issue":null,"first_page":"537","last_page":"541"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10326","display_name":"Indoor and Outdoor Localization Technologies","score":0.9751999974250793,"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"}},"topics":[{"id":"https://openalex.org/T10326","display_name":"Indoor and Outdoor Localization Technologies","score":0.9751999974250793,"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"}},{"id":"https://openalex.org/T10860","display_name":"Speech and Audio Processing","score":0.00559999980032444,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T10936","display_name":"Millimeter-Wave Propagation and Modeling","score":0.0020000000949949026,"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/rss","display_name":"RSS","score":0.8256000280380249},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.7989000082015991},{"id":"https://openalex.org/keywords/signal-strength","display_name":"Signal strength","score":0.6133999824523926},{"id":"https://openalex.org/keywords/gaussian-process","display_name":"Gaussian process","score":0.5066999793052673},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.4758000075817108},{"id":"https://openalex.org/keywords/mean-squared-error","display_name":"Mean squared error","score":0.45649999380111694},{"id":"https://openalex.org/keywords/sensor-fusion","display_name":"Sensor fusion","score":0.4334999918937683},{"id":"https://openalex.org/keywords/fingerprint-recognition","display_name":"Fingerprint recognition","score":0.42250001430511475},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4154999852180481},{"id":"https://openalex.org/keywords/path-loss","display_name":"Path loss","score":0.39959999918937683}],"concepts":[{"id":"https://openalex.org/C2385561","wikidata":"https://www.wikidata.org/wiki/Q45432","display_name":"RSS","level":2,"score":0.8256000280380249},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.7989000082015991},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7235000133514404},{"id":"https://openalex.org/C176808163","wikidata":"https://www.wikidata.org/wiki/Q17105794","display_name":"Signal strength","level":3,"score":0.6133999824523926},{"id":"https://openalex.org/C61326573","wikidata":"https://www.wikidata.org/wiki/Q1496376","display_name":"Gaussian process","level":3,"score":0.5066999793052673},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.48539999127388},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.4758000075817108},{"id":"https://openalex.org/C139945424","wikidata":"https://www.wikidata.org/wiki/Q1940696","display_name":"Mean squared error","level":2,"score":0.45649999380111694},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.4334999918937683},{"id":"https://openalex.org/C168406668","wikidata":"https://www.wikidata.org/wiki/Q178022","display_name":"Fingerprint recognition","level":3,"score":0.42250001430511475},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4154999852180481},{"id":"https://openalex.org/C194273485","wikidata":"https://www.wikidata.org/wiki/Q1478845","display_name":"Path loss","level":3,"score":0.39959999918937683},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.399399995803833},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.3928999900817871},{"id":"https://openalex.org/C188198153","wikidata":"https://www.wikidata.org/wiki/Q1613840","display_name":"Limiting","level":2,"score":0.3686000108718872},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.3594000041484833},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3594000041484833},{"id":"https://openalex.org/C177860922","wikidata":"https://www.wikidata.org/wiki/Q788608","display_name":"Decorrelation","level":2,"score":0.3589000105857849},{"id":"https://openalex.org/C104267543","wikidata":"https://www.wikidata.org/wiki/Q208163","display_name":"Signal processing","level":3,"score":0.34220001101493835},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3407000005245209},{"id":"https://openalex.org/C2779843651","wikidata":"https://www.wikidata.org/wiki/Q7390335","display_name":"SIGNAL (programming language)","level":2,"score":0.33329999446868896},{"id":"https://openalex.org/C2779585090","wikidata":"https://www.wikidata.org/wiki/Q3457762","display_name":"Resilience (materials science)","level":2,"score":0.3328000009059906},{"id":"https://openalex.org/C112972136","wikidata":"https://www.wikidata.org/wiki/Q7595718","display_name":"Stability (learning theory)","level":2,"score":0.33090001344680786},{"id":"https://openalex.org/C2777826928","wikidata":"https://www.wikidata.org/wiki/Q3745713","display_name":"Fingerprint (computing)","level":2,"score":0.33079999685287476},{"id":"https://openalex.org/C2777735758","wikidata":"https://www.wikidata.org/wiki/Q817765","display_name":"Path (computing)","level":2,"score":0.321399986743927},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3176000118255615},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.3111000061035156},{"id":"https://openalex.org/C159620131","wikidata":"https://www.wikidata.org/wiki/Q1938983","display_name":"Spatial analysis","level":2,"score":0.28619998693466187},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.2838999927043915},{"id":"https://openalex.org/C89805583","wikidata":"https://www.wikidata.org/wiki/Q192940","display_name":"Accelerometer","level":2,"score":0.2750000059604645},{"id":"https://openalex.org/C24590314","wikidata":"https://www.wikidata.org/wiki/Q336038","display_name":"Wireless sensor network","level":2,"score":0.27000001072883606},{"id":"https://openalex.org/C47432892","wikidata":"https://www.wikidata.org/wiki/Q831390","display_name":"Wavelet","level":2,"score":0.2597000002861023},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.25369998812675476}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/lcomm.2025.3641829","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lcomm.2025.3641829","pdf_url":null,"source":{"id":"https://openalex.org/S147316732","display_name":"IEEE Communications Letters","issn_l":"1089-7798","issn":["1089-7798","1558-2558","2373-7891"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310316002","host_organization_name":"IEEE Communications Society","host_organization_lineage":["https://openalex.org/P4310316002","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Communications Society","Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Communications Letters","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1548865700","display_name":null,"funder_award_id":"62473139","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G2894388584","display_name":null,"funder_award_id":"62476084","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3408348127","display_name":null,"funder_award_id":"U22A2059","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":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":13,"referenced_works":["https://openalex.org/W2318966136","https://openalex.org/W2763697523","https://openalex.org/W2888183437","https://openalex.org/W2891088180","https://openalex.org/W2891224819","https://openalex.org/W3011286333","https://openalex.org/W3049238838","https://openalex.org/W4225547964","https://openalex.org/W4285392096","https://openalex.org/W4312883020","https://openalex.org/W4390754347","https://openalex.org/W4393145118","https://openalex.org/W4405440339"],"related_works":[],"abstract_inverted_index":{"Indoor":[0],"WIFI":[1],"localization":[2,60,112],"often":[3],"suffers":[4],"from":[5],"severe":[6],"signal":[7],"fluctuations":[8],"and":[9,13,31,44,74,83,105],"interference,":[10],"limiting":[11],"accuracy":[12],"stability":[14],"in":[15,47,88],"dynamic":[16],"environments.":[17],"This":[18],"paper":[19],"introduces":[20],"a":[21,57,89],"dual-model":[22],"fusion":[23],"framework":[24],"that":[25,62,94],"combines":[26],"Gaussian":[27],"Process":[28],"Regression":[29],"(GPR)":[30],"the":[32],"Log-Distance":[33],"Path":[34],"Loss":[35],"(LDPL)":[36],"model":[37],"to":[38,81,102,108,120],"construct":[39],"high-fidelity":[40],"WiFi":[41],"fingerprint":[42],"maps":[43],"predict":[45],"signals":[46],"unobserved":[48],"regions.":[49],"Building":[50],"on":[51],"these":[52],"maps,":[53],"we":[54],"further":[55],"propose":[56],"Bayesian":[58],"multi-fingerprint":[59],"algorithm":[61],"fuses":[63],"three":[64],"complementary":[65],"fingerprints\u2014Received":[66],"Signal":[67,70],"Strength":[68,71],"(RSS),":[69],"Difference":[72],"(SSD),":[73],"Hyperbolic":[75],"Location":[76],"Fingerprint":[77],"(HLF)\u2014to":[78],"enhance":[79],"robustness":[80],"temporal":[82],"spatial":[84],"variations.":[85],"Comprehensive":[86],"experiments":[87],"large":[90],"multi-floor":[91],"environment":[92],"show":[93],"our":[95],"method":[96],"reduces":[97],"mean":[98],"RSS":[99],"prediction":[100],"error":[101],"3.09":[103],"dBm":[104],"achieves":[106],"up":[107],"20":[109],"%":[110],"lower":[111],"RMSE":[113],"than":[114],"state-of-the-art":[115],"methods,":[116],"demonstrating":[117],"superior":[118],"resilience":[119],"environmental":[121],"dynamics.":[122]},"counts_by_year":[],"updated_date":"2025-12-24T23:09:58.560324","created_date":"2025-12-08T00:00:00"}
