{"id":"https://openalex.org/W4413277653","doi":"https://doi.org/10.1109/access.2025.3599837","title":"Enhanced Indoor Pedestrian Tracking Using UWB/PDR Fusion and NLOS Error Mitigation","display_name":"Enhanced Indoor Pedestrian Tracking Using UWB/PDR Fusion and NLOS Error Mitigation","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4413277653","doi":"https://doi.org/10.1109/access.2025.3599837"},"language":"en","primary_location":{"id":"doi:10.1109/access.2025.3599837","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2025.3599837","pdf_url":null,"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":null,"license_id":null,"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://doi.org/10.1109/access.2025.3599837","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Shoude Wang","orcid":"https://orcid.org/0009-0004-2485-2299"},"institutions":[{"id":"https://openalex.org/I4210136047","display_name":"Weifang University of Science and Technology","ror":"https://ror.org/04ha2bb10","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210136047"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Shoude Wang","raw_affiliation_strings":["Weifang University of Science and Technology, Shouguang, China","Weifang University of Science and Technology, 1299 Jinguang Street, Shouguang, China"],"raw_orcid":"https://orcid.org/0009-0004-2485-2299","affiliations":[{"raw_affiliation_string":"Weifang University of Science and Technology, Shouguang, China","institution_ids":["https://openalex.org/I4210136047"]},{"raw_affiliation_string":"Weifang University of Science and Technology, 1299 Jinguang Street, Shouguang, China","institution_ids":["https://openalex.org/I4210136047"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5039331012","display_name":"Nur Syazreen Ahmad","orcid":"https://orcid.org/0000-0003-2615-8386"},"institutions":[{"id":"https://openalex.org/I139322472","display_name":"Universiti Sains Malaysia","ror":"https://ror.org/02rgb2k63","country_code":"MY","type":"education","lineage":["https://openalex.org/I139322472"]}],"countries":["MY"],"is_corresponding":false,"raw_author_name":"Nur Syazreen Ahmad","raw_affiliation_strings":["School of Electrical and Electronic Engineering, Universiti Sains Malaysia, Nibong Tebal, Penang, Malaysia"],"raw_orcid":"https://orcid.org/0000-0003-2615-8386","affiliations":[{"raw_affiliation_string":"School of Electrical and Electronic Engineering, Universiti Sains Malaysia, Nibong Tebal, Penang, Malaysia","institution_ids":["https://openalex.org/I139322472"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I4210136047"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":0.6252,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.72496226,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":98},"biblio":{"volume":"13","issue":null,"first_page":"145812","last_page":"145827"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10326","display_name":"Indoor and Outdoor Localization Technologies","score":0.9902999997138977,"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":0.9902999997138977,"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/T10711","display_name":"Target Tracking and Data Fusion in Sensor Networks","score":0.9818999767303467,"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/T11739","display_name":"Microwave Imaging and Scattering Analysis","score":0.9771000146865845,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical 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/non-line-of-sight-propagation","display_name":"Non-line-of-sight propagation","score":0.9097121953964233},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6695116758346558},{"id":"https://openalex.org/keywords/pedestrian","display_name":"Pedestrian","score":0.6613028049468994},{"id":"https://openalex.org/keywords/fusion","display_name":"Fusion","score":0.5564588904380798},{"id":"https://openalex.org/keywords/sensor-fusion","display_name":"Sensor fusion","score":0.5474716424942017},{"id":"https://openalex.org/keywords/tracking","display_name":"Tracking (education)","score":0.5432563424110413},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.37018585205078125},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.32446175813674927},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.15117332339286804},{"id":"https://openalex.org/keywords/wireless","display_name":"Wireless","score":0.14614138007164001},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.11555635929107666},{"id":"https://openalex.org/keywords/transport-engineering","display_name":"Transport engineering","score":0.07328510284423828}],"concepts":[{"id":"https://openalex.org/C154910267","wikidata":"https://www.wikidata.org/wiki/Q1740982","display_name":"Non-line-of-sight propagation","level":3,"score":0.9097121953964233},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6695116758346558},{"id":"https://openalex.org/C2777113093","wikidata":"https://www.wikidata.org/wiki/Q221488","display_name":"Pedestrian","level":2,"score":0.6613028049468994},{"id":"https://openalex.org/C158525013","wikidata":"https://www.wikidata.org/wiki/Q2593739","display_name":"Fusion","level":2,"score":0.5564588904380798},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.5474716424942017},{"id":"https://openalex.org/C2775936607","wikidata":"https://www.wikidata.org/wiki/Q466845","display_name":"Tracking (education)","level":2,"score":0.5432563424110413},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.37018585205078125},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.32446175813674927},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.15117332339286804},{"id":"https://openalex.org/C555944384","wikidata":"https://www.wikidata.org/wiki/Q249","display_name":"Wireless","level":2,"score":0.14614138007164001},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.11555635929107666},{"id":"https://openalex.org/C22212356","wikidata":"https://www.wikidata.org/wiki/Q775325","display_name":"Transport engineering","level":1,"score":0.07328510284423828},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.0},{"id":"https://openalex.org/C19417346","wikidata":"https://www.wikidata.org/wiki/Q7922","display_name":"Pedagogy","level":1,"score":0.0},{"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}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2025.3599837","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2025.3599837","pdf_url":null,"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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:73bfdd0a6de34d2095bca2f4ec9b4f37","is_oa":true,"landing_page_url":"https://doaj.org/article/73bfdd0a6de34d2095bca2f4ec9b4f37","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 13, Pp 145812-145827 (2025)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2025.3599837","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2025.3599837","pdf_url":null,"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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2964138830","display_name":null,"funder_award_id":"FRGS/1/2024/TK07/USM/02/3","funder_id":"https://openalex.org/F4320321709","funder_display_name":"Ministry of Higher Education, Malaysia"}],"funders":[{"id":"https://openalex.org/F4320321709","display_name":"Ministry of Higher Education, Malaysia","ror":"https://ror.org/05mcs2t73"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":52,"referenced_works":["https://openalex.org/W28412257","https://openalex.org/W132318879","https://openalex.org/W2025241138","https://openalex.org/W2056797234","https://openalex.org/W2084077058","https://openalex.org/W2111072639","https://openalex.org/W2125943568","https://openalex.org/W2139386984","https://openalex.org/W2158581396","https://openalex.org/W2804231978","https://openalex.org/W2907574584","https://openalex.org/W2945710797","https://openalex.org/W2946465327","https://openalex.org/W2965087352","https://openalex.org/W2981861079","https://openalex.org/W3008563426","https://openalex.org/W3011291128","https://openalex.org/W3033586993","https://openalex.org/W3101720559","https://openalex.org/W3106678532","https://openalex.org/W3118145897","https://openalex.org/W3120364461","https://openalex.org/W3132834417","https://openalex.org/W3142222582","https://openalex.org/W3154148285","https://openalex.org/W3155991567","https://openalex.org/W3157587584","https://openalex.org/W3158380703","https://openalex.org/W3165066846","https://openalex.org/W3174758125","https://openalex.org/W3184959411","https://openalex.org/W4237444302","https://openalex.org/W4293704597","https://openalex.org/W4313479115","https://openalex.org/W4313547892","https://openalex.org/W4322707243","https://openalex.org/W4323020858","https://openalex.org/W4391215952","https://openalex.org/W4392745106","https://openalex.org/W4398185575","https://openalex.org/W4399437409","https://openalex.org/W4399938955","https://openalex.org/W4400844177","https://openalex.org/W4400913393","https://openalex.org/W4402436829","https://openalex.org/W4403017941","https://openalex.org/W4403390281","https://openalex.org/W4404914718","https://openalex.org/W4406028241","https://openalex.org/W4406946955","https://openalex.org/W4408111925","https://openalex.org/W4409336390"],"related_works":["https://openalex.org/W2172272784","https://openalex.org/W2003817535","https://openalex.org/W4307436769","https://openalex.org/W4323793210","https://openalex.org/W2366306259","https://openalex.org/W2132659060","https://openalex.org/W2031992971","https://openalex.org/W3214791684","https://openalex.org/W1982289787","https://openalex.org/W2152662039"],"abstract_inverted_index":{"Pedestrian":[0],"Dead":[1],"Reckoning":[2],"(PDR)":[3],"utilizing":[4],"Inertial":[5],"Navigation":[6],"System":[7],"(INS)":[8],"technology":[9],"often":[10],"encounters":[11],"substantial":[12],"cumulative":[13],"errors":[14],"and":[15,108,159,188,212,219],"random":[16],"sensor-induced":[17],"noise,":[18],"while":[19],"Ultra-Wideband":[20],"(UWB)":[21],"positioning":[22,50,210],"can":[23],"degrade":[24],"severely":[25],"under":[26,120],"Non-Line-of-Sight":[27],"(NLOS)":[28],"conditions":[29],"due":[30],"to":[31,125,147],"environmental":[32],"factors.":[33],"To":[34],"overcome":[35],"the":[36,77,81,85,95,106,112,165,172,195],"above":[37],"challenges,":[38],"this":[39],"research":[40],"proposes":[41],"an":[42,64,181],"enhanced":[43],"PDR/UWB":[44],"fusion":[45,135],"framework":[46],"that":[47,139,194],"significantly":[48],"improves":[49],"accuracy.":[51],"First,":[52],"a":[53,134,141],"novel":[54],"NLOS":[55,122],"ranging":[56],"error":[57],"mitigation":[58],"approach":[59],"is":[60,137],"developed":[61],"by":[62,105,111],"integrating":[63],"Extreme":[65],"Learning":[66],"Machine":[67],"(ELM)":[68],"in":[69,115,209,216],"conjunction":[70],"with":[71,76,177],"Gaussian":[72],"Process":[73],"Regression":[74],"(GPR),":[75],"initial":[78],"parameters":[79],"of":[80],"ELM":[82],"optimized":[83],"via":[84],"Nutcracker":[86],"Optimizer.":[87],"Channel":[88],"Impulse":[89],"Response":[90],"(CIR)":[91],"data":[92],"collected":[93],"from":[94,151],"UWB":[96,129,168,202],"module":[97],"serve":[98],"as":[99],"features,":[100],"which":[101],"are":[102,131,162,170,175],"first":[103],"processed":[104],"ELM,":[107],"subsequently":[109],"refined":[110],"GPR,":[113],"resulting":[114],"more":[116],"accurate":[117],"distance":[118],"estimates":[119],"challenging":[121],"conditions.":[123],"Second,":[124],"accommodate":[126],"scenarios":[127],"where":[128],"signals":[130],"intermittently":[132],"unavailable,":[133],"strategy":[136],"proposed":[138,196],"employs":[140],"Multilayer":[142],"Perceptron":[143],"(MLP)":[144],"neural":[145],"network":[146],"predict":[148],"pseudo-UWB":[149],"observations":[150,174],"PDR":[152,178],"data.":[153],"Specifically,":[154],"PDR-derived":[155],"acceleration,":[156],"angular":[157],"velocity,":[158],"current":[160],"position":[161],"fed":[163],"into":[164],"MLP.":[166],"When":[167],"measurements":[169],"absent,":[171],"MLP-predicted":[173],"integrated":[176,197],"outputs":[179],"using":[180],"Extended":[182],"Kalman":[183],"Filter":[184],"(EKF),":[185],"ensuring":[186],"continuous":[187],"reliable":[189],"localization.":[190,222],"Experimental":[191],"results":[192],"demonstrate":[193],"system":[198],"substantially":[199],"outperforms":[200],"standalone":[201],"or":[203],"EKF-based":[204],"methods,":[205],"achieving":[206],"marked":[207],"improvements":[208],"accuracy":[211],"underscoring":[213],"its":[214],"effectiveness":[215],"delivering":[217],"robust":[218],"precise":[220],"indoor":[221]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-05-06T08:25:59.206177","created_date":"2025-10-10T00:00:00"}