{"id":"https://openalex.org/W2778547285","doi":"https://doi.org/10.1109/gcce.2017.8229229","title":"An accurate indoor positioning algorithm using particle filter based on the proximity of bluetooth beacons","display_name":"An accurate indoor positioning algorithm using particle filter based on the proximity of bluetooth beacons","publication_year":2017,"publication_date":"2017-10-01","ids":{"openalex":"https://openalex.org/W2778547285","doi":"https://doi.org/10.1109/gcce.2017.8229229","mag":"2778547285"},"language":"en","primary_location":{"id":"doi:10.1109/gcce.2017.8229229","is_oa":false,"landing_page_url":"https://doi.org/10.1109/gcce.2017.8229229","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE 6th Global Conference on Consumer Electronics (GCCE)","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/A5053413413","display_name":"Ryoya Momose","orcid":null},"institutions":[{"id":"https://openalex.org/I150744194","display_name":"Waseda University","ror":"https://ror.org/00ntfnx83","country_code":"JP","type":"education","lineage":["https://openalex.org/I150744194"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Ryoya Momose","raw_affiliation_strings":["Dept. of Computer Science and Communications Engineering, Waseda University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Dept. of Computer Science and Communications Engineering, Waseda University","institution_ids":["https://openalex.org/I150744194"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5110465260","display_name":"Tomoyuki Nitta","orcid":null},"institutions":[{"id":"https://openalex.org/I110995367","display_name":"Sprint (United States)","ror":"https://ror.org/04rxdpa15","country_code":"US","type":"company","lineage":["https://openalex.org/I110995367"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Tomoyuki Nitta","raw_affiliation_strings":["Zenrin DataCom Co., LTD"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Zenrin DataCom Co., LTD","institution_ids":["https://openalex.org/I110995367"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5061982025","display_name":"Masao Yanagisawa","orcid":"https://orcid.org/0000-0002-5168-3214"},"institutions":[{"id":"https://openalex.org/I150744194","display_name":"Waseda University","ror":"https://ror.org/00ntfnx83","country_code":"JP","type":"education","lineage":["https://openalex.org/I150744194"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Masao Yanagisawa","raw_affiliation_strings":["Dept. of Computer Science and Communications Engineering, Waseda University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Dept. of Computer Science and Communications Engineering, Waseda University","institution_ids":["https://openalex.org/I150744194"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5087516286","display_name":"Nozomu Togawa","orcid":"https://orcid.org/0000-0003-3400-3587"},"institutions":[{"id":"https://openalex.org/I150744194","display_name":"Waseda University","ror":"https://ror.org/00ntfnx83","country_code":"JP","type":"education","lineage":["https://openalex.org/I150744194"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Nozomu Togawa","raw_affiliation_strings":["Dept. of Computer Science and Communications Engineering, Waseda University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Dept. of Computer Science and Communications Engineering, Waseda University","institution_ids":["https://openalex.org/I150744194"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":15,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10326","display_name":"Indoor and Outdoor Localization Technologies","score":1.0,"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":1.0,"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/T11192","display_name":"Underwater Vehicles and Communication Systems","score":0.9919999837875366,"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"}},{"id":"https://openalex.org/T10860","display_name":"Speech and Audio Processing","score":0.9854000210762024,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/beacon","display_name":"Beacon","score":0.9129433035850525},{"id":"https://openalex.org/keywords/bluetooth","display_name":"Bluetooth","score":0.7788563370704651},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6736652255058289},{"id":"https://openalex.org/keywords/particle-filter","display_name":"Particle filter","score":0.652918815612793},{"id":"https://openalex.org/keywords/global-positioning-system","display_name":"Global Positioning System","score":0.5929888486862183},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.5578657388687134},{"id":"https://openalex.org/keywords/acceleration","display_name":"Acceleration","score":0.4978921413421631},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4752790033817291},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.4356839060783386},{"id":"https://openalex.org/keywords/kalman-filter","display_name":"Kalman filter","score":0.4147733747959137},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.2823870778083801},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.22182464599609375},{"id":"https://openalex.org/keywords/wireless","display_name":"Wireless","score":0.2200586497783661},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.1583491563796997},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.09884500503540039}],"concepts":[{"id":"https://openalex.org/C102168758","wikidata":"https://www.wikidata.org/wiki/Q7321258","display_name":"Beacon","level":2,"score":0.9129433035850525},{"id":"https://openalex.org/C546215728","wikidata":"https://www.wikidata.org/wiki/Q39531","display_name":"Bluetooth","level":3,"score":0.7788563370704651},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6736652255058289},{"id":"https://openalex.org/C52421305","wikidata":"https://www.wikidata.org/wiki/Q1151499","display_name":"Particle filter","level":3,"score":0.652918815612793},{"id":"https://openalex.org/C60229501","wikidata":"https://www.wikidata.org/wiki/Q18822","display_name":"Global Positioning System","level":2,"score":0.5929888486862183},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.5578657388687134},{"id":"https://openalex.org/C117896860","wikidata":"https://www.wikidata.org/wiki/Q11376","display_name":"Acceleration","level":2,"score":0.4978921413421631},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4752790033817291},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.4356839060783386},{"id":"https://openalex.org/C157286648","wikidata":"https://www.wikidata.org/wiki/Q846780","display_name":"Kalman filter","level":2,"score":0.4147733747959137},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.2823870778083801},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.22182464599609375},{"id":"https://openalex.org/C555944384","wikidata":"https://www.wikidata.org/wiki/Q249","display_name":"Wireless","level":2,"score":0.2200586497783661},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.1583491563796997},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.09884500503540039},{"id":"https://openalex.org/C74650414","wikidata":"https://www.wikidata.org/wiki/Q11397","display_name":"Classical mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/gcce.2017.8229229","is_oa":false,"landing_page_url":"https://doi.org/10.1109/gcce.2017.8229229","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE 6th Global Conference on Consumer Electronics (GCCE)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":10,"referenced_works":["https://openalex.org/W2022829229","https://openalex.org/W2077611006","https://openalex.org/W2096187762","https://openalex.org/W2146745466","https://openalex.org/W2168988101","https://openalex.org/W2299515439","https://openalex.org/W2572175367","https://openalex.org/W2576937033","https://openalex.org/W2741294234","https://openalex.org/W6742279775"],"related_works":["https://openalex.org/W2353358273","https://openalex.org/W2386246461","https://openalex.org/W2778547285","https://openalex.org/W2138998224","https://openalex.org/W2042720709","https://openalex.org/W2775473110","https://openalex.org/W3089923007","https://openalex.org/W2770753514","https://openalex.org/W2592220187","https://openalex.org/W3047571881"],"abstract_inverted_index":{"Indoor":[0],"positioning":[1,23,95,146],"without":[2],"GPS":[3],"is":[4],"one":[5],"of":[6,38,63],"the":[7,36,39,51,55,61,64,73,93,99,109,113,129,133,144],"most":[8],"important":[9],"problems":[10],"in":[11,54,127,132],"indoor":[12,22,145],"pedestrian":[13],"navigation.":[14],"In":[15,49,84],"this":[16],"paper,":[17],"we":[18,34,58,120],"propose":[19],"an":[20],"accurate":[21],"algorithm":[24,141],"using":[25],"a":[26,31,91],"particle":[27,56,134],"filter":[28],"based":[29],"on":[30],"floormap,":[32,92],"where":[33],"use":[35,60],"proximity":[37,62],"Bluetooth":[40,65,114],"beacons":[41,115],"as":[42,44],"well":[43],"acceleration":[45,100],"and":[46,101],"geomagnetic":[47,102],"sensors.":[48],"designing":[50,128],"likelihood":[52,130],"function":[53,131],"filter,":[57],"effectively":[59,89],"beacons,":[66],"which":[67],"just":[68],"gives":[69],"rough":[70],"distance":[71,82],"to":[72,86,98,150,153],"target":[74],"beacon":[75],"but":[76],"more":[77],"stable":[78],"than":[79],"conventional":[80,155],"RSSI-based":[81],"estimation.":[83],"addition":[85],"that,":[87],"by":[88,118,148],"utilizing":[90],"accumulated":[94],"errors":[96,147],"due":[97],"sensors":[103],"are":[104,116],"much":[105],"reduced.":[106],"Moreover,":[107],"when":[108],"radio":[110],"waves":[111],"from":[112],"blocked":[117],"obstacles,":[119],"can":[121,142],"also":[122],"take":[123],"it":[124],"into":[125],"account":[126],"filter.":[135],"Experimental":[136],"results":[137],"demonstrate":[138],"that":[139],"our":[140],"reduce":[143],"up":[149],"79%":[151],"compared":[152],"several":[154],"algorithms.":[156]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":2},{"year":2018,"cited_by_count":4}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}