{"id":"https://openalex.org/W2795844823","doi":"https://doi.org/10.1109/iccchina.2017.8330332","title":"Robust fingerprinting-based localization using directed graphical models","display_name":"Robust fingerprinting-based localization using directed graphical models","publication_year":2017,"publication_date":"2017-10-01","ids":{"openalex":"https://openalex.org/W2795844823","doi":"https://doi.org/10.1109/iccchina.2017.8330332","mag":"2795844823"},"language":"en","primary_location":{"id":"doi:10.1109/iccchina.2017.8330332","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccchina.2017.8330332","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE/CIC International Conference on Communications in China (ICCC)","raw_type":"proceedings-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/A5101983049","display_name":"Yueyue Zhang","orcid":"https://orcid.org/0000-0002-0993-6708"},"institutions":[{"id":"https://openalex.org/I76569877","display_name":"Southeast University","ror":"https://ror.org/04ct4d772","country_code":"CN","type":"education","lineage":["https://openalex.org/I76569877"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yueyue Zhang","raw_affiliation_strings":["National Mobile Communications Research Laboratory, Southeast University, Nanjing, Jiangsu, P.R. China"],"affiliations":[{"raw_affiliation_string":"National Mobile Communications Research Laboratory, Southeast University, Nanjing, Jiangsu, P.R. China","institution_ids":["https://openalex.org/I76569877"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5084056787","display_name":"Yaping Zhu","orcid":"https://orcid.org/0000-0003-3163-3815"},"institutions":[{"id":"https://openalex.org/I76569877","display_name":"Southeast University","ror":"https://ror.org/04ct4d772","country_code":"CN","type":"education","lineage":["https://openalex.org/I76569877"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yaping Zhu","raw_affiliation_strings":["National Mobile Communications Research Laboratory, Southeast University, Nanjing, Jiangsu, P.R. China"],"affiliations":[{"raw_affiliation_string":"National Mobile Communications Research Laboratory, Southeast University, Nanjing, Jiangsu, P.R. China","institution_ids":["https://openalex.org/I76569877"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101962019","display_name":"Weiwei Xia","orcid":"https://orcid.org/0000-0001-6069-5375"},"institutions":[{"id":"https://openalex.org/I76569877","display_name":"Southeast University","ror":"https://ror.org/04ct4d772","country_code":"CN","type":"education","lineage":["https://openalex.org/I76569877"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Weiwei Xia","raw_affiliation_strings":["National Mobile Communications Research Laboratory, Southeast University, Nanjing, Jiangsu, P.R. China"],"affiliations":[{"raw_affiliation_string":"National Mobile Communications Research Laboratory, Southeast University, Nanjing, Jiangsu, P.R. China","institution_ids":["https://openalex.org/I76569877"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101527302","display_name":"Feng Yan","orcid":"https://orcid.org/0000-0002-8387-1754"},"institutions":[{"id":"https://openalex.org/I76569877","display_name":"Southeast University","ror":"https://ror.org/04ct4d772","country_code":"CN","type":"education","lineage":["https://openalex.org/I76569877"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Feng Yan","raw_affiliation_strings":["National Mobile Communications Research Laboratory, Southeast University, Nanjing, Jiangsu, P.R. China"],"affiliations":[{"raw_affiliation_string":"National Mobile Communications Research Laboratory, Southeast University, Nanjing, Jiangsu, P.R. China","institution_ids":["https://openalex.org/I76569877"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101610535","display_name":"Lianfeng Shen","orcid":"https://orcid.org/0000-0002-7250-3462"},"institutions":[{"id":"https://openalex.org/I76569877","display_name":"Southeast University","ror":"https://ror.org/04ct4d772","country_code":"CN","type":"education","lineage":["https://openalex.org/I76569877"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lianfeng Shen","raw_affiliation_strings":["National Mobile Communications Research Laboratory, Southeast University, Nanjing, Jiangsu, P.R. China"],"affiliations":[{"raw_affiliation_string":"National Mobile Communications Research Laboratory, Southeast University, Nanjing, Jiangsu, P.R. China","institution_ids":["https://openalex.org/I76569877"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5025990925","display_name":"Yi Wu","orcid":"https://orcid.org/0000-0001-5704-2111"},"institutions":[{"id":"https://openalex.org/I111753288","display_name":"Fujian Normal University","ror":"https://ror.org/020azk594","country_code":"CN","type":"education","lineage":["https://openalex.org/I111753288"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yi Wu","raw_affiliation_strings":["Key Laboratory of OptoElectronic Science and Technology for Medicine of Ministry of Education, Fujian Normal University, Fuzhou, P.R. China"],"affiliations":[{"raw_affiliation_string":"Key Laboratory of OptoElectronic Science and Technology for Medicine of Ministry of Education, Fujian Normal University, Fuzhou, P.R. China","institution_ids":["https://openalex.org/I111753288"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5101983049"],"corresponding_institution_ids":["https://openalex.org/I76569877"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.20689194,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"18","issue":null,"first_page":"1","last_page":"6"},"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/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.993399977684021,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace 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":0.9868000149726868,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/maximum-a-posteriori-estimation","display_name":"Maximum a posteriori estimation","score":0.7570856809616089},{"id":"https://openalex.org/keywords/rss","display_name":"RSS","score":0.7022473812103271},{"id":"https://openalex.org/keywords/estimator","display_name":"Estimator","score":0.6437329053878784},{"id":"https://openalex.org/keywords/graphical-model","display_name":"Graphical model","score":0.619879424571991},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6179796457290649},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.560454249382019},{"id":"https://openalex.org/keywords/maximum-likelihood","display_name":"Maximum likelihood","score":0.46726956963539124},{"id":"https://openalex.org/keywords/smoothing","display_name":"Smoothing","score":0.43410399556159973},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.38482433557510376},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.37925803661346436},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.3320190906524658},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.29894545674324036},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.16596317291259766},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.1305178999900818}],"concepts":[{"id":"https://openalex.org/C9810830","wikidata":"https://www.wikidata.org/wiki/Q635384","display_name":"Maximum a posteriori estimation","level":3,"score":0.7570856809616089},{"id":"https://openalex.org/C2385561","wikidata":"https://www.wikidata.org/wiki/Q45432","display_name":"RSS","level":2,"score":0.7022473812103271},{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.6437329053878784},{"id":"https://openalex.org/C155846161","wikidata":"https://www.wikidata.org/wiki/Q1143367","display_name":"Graphical model","level":2,"score":0.619879424571991},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6179796457290649},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.560454249382019},{"id":"https://openalex.org/C49781872","wikidata":"https://www.wikidata.org/wiki/Q1045555","display_name":"Maximum likelihood","level":2,"score":0.46726956963539124},{"id":"https://openalex.org/C3770464","wikidata":"https://www.wikidata.org/wiki/Q775963","display_name":"Smoothing","level":2,"score":0.43410399556159973},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.38482433557510376},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.37925803661346436},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.3320190906524658},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.29894545674324036},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.16596317291259766},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.1305178999900818},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iccchina.2017.8330332","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccchina.2017.8330332","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE/CIC International Conference on Communications in China (ICCC)","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":16,"referenced_works":["https://openalex.org/W1480661394","https://openalex.org/W1987209873","https://openalex.org/W2010518947","https://openalex.org/W2011502582","https://openalex.org/W2041501450","https://openalex.org/W2124216931","https://openalex.org/W2205259141","https://openalex.org/W2265608995","https://openalex.org/W2287252941","https://openalex.org/W2320046825","https://openalex.org/W2341774241","https://openalex.org/W2396946315","https://openalex.org/W2571194767","https://openalex.org/W2601927531","https://openalex.org/W2623902153","https://openalex.org/W4238535082"],"related_works":["https://openalex.org/W1503532423","https://openalex.org/W1967494390","https://openalex.org/W245717845","https://openalex.org/W3013496002","https://openalex.org/W2465363361","https://openalex.org/W2896820906","https://openalex.org/W2101542441","https://openalex.org/W4284711868","https://openalex.org/W2110322980","https://openalex.org/W2283950057"],"abstract_inverted_index":{"In":[0],"this":[1,95],"paper,":[2],"we":[3,97],"propose":[4,98],"a":[5,60,62,123],"robust":[6],"fingerprinting-based":[7],"localization":[8,55],"using":[9,47],"directed":[10],"graphical":[11,50],"model.":[12],"To":[13,94],"overcome":[14],"the":[15,19,26,38,43,48,54,78,91,106,110,114,119],"influence":[16],"caused":[17],"by":[18,35],"jitter":[20],"of":[21,28,109],"received":[22],"signal":[23],"strength":[24],"(RSS),":[25],"location":[27,45],"one":[29],"mobile":[30],"node":[31],"can":[32,82],"be":[33,83],"estimated":[34],"fusing":[36],"both":[37],"current":[39],"matching":[40],"result":[41],"and":[42],"previous":[44],"estimation,":[46],"Bayesian":[49],"model":[51],"(BGM).":[52],"Then,":[53],"problem":[56],"is":[57,67],"cast":[58],"as":[59],"maximum":[61,73],"posteriori":[63],"(MAP)":[64],"estimator,":[65],"which":[66],"also":[68],"proved":[69],"to":[70,72,104],"coincide":[71],"likelihood":[74],"(ML)":[75],"estimator.":[76],"However,":[77],"initialized":[79],"MAP":[80],"estimator":[81],"hardly":[84],"solved":[85],"with":[86],"incomplete":[87],"statistical":[88],"property":[89],"concerning":[90],"random":[92],"vectors.":[93],"end,":[96],"an":[99],"adaptive":[100],"smoothing":[101],"algorithm":[102,121],"(ASA)":[103],"attain":[105],"suboptimal":[107],"solution":[108],"original":[111],"problem.":[112],"Finally,":[113],"experimental":[115],"results":[116],"show":[117],"that":[118],"proposed":[120],"obtains":[122],"significant":[124],"performance":[125],"gain.":[126]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
