{"id":"https://openalex.org/W2124663461","doi":"https://doi.org/10.1109/tsp.2012.2187645","title":"Geolocation Performance With Biased Range Measurements","display_name":"Geolocation Performance With Biased Range Measurements","publication_year":2012,"publication_date":"2012-02-13","ids":{"openalex":"https://openalex.org/W2124663461","doi":"https://doi.org/10.1109/tsp.2012.2187645","mag":"2124663461"},"language":"en","primary_location":{"id":"doi:10.1109/tsp.2012.2187645","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tsp.2012.2187645","pdf_url":null,"source":{"id":"https://openalex.org/S168680287","display_name":"IEEE Transactions on Signal Processing","issn_l":"1053-587X","issn":["1053-587X","1941-0476"],"is_oa":false,"is_in_doaj":false,"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 Transactions on Signal Processing","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/A5077295091","display_name":"Ning Liu","orcid":"https://orcid.org/0000-0002-2195-8424"},"institutions":[{"id":"https://openalex.org/I103635307","display_name":"University of California, Riverside","ror":"https://ror.org/03nawhv43","country_code":"US","type":"education","lineage":["https://openalex.org/I103635307"]},{"id":"https://openalex.org/I4210127325","display_name":"Broadcom (United States)","ror":"https://ror.org/035gt5s03","country_code":"US","type":"company","lineage":["https://openalex.org/I4210127325"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Ning Liu","raw_affiliation_strings":["Broadcom Corporation, Irvine, CA, USA","University of California, Riverside, CA, USA"],"affiliations":[{"raw_affiliation_string":"Broadcom Corporation, Irvine, CA, USA","institution_ids":["https://openalex.org/I4210127325"]},{"raw_affiliation_string":"University of California, Riverside, CA, USA","institution_ids":["https://openalex.org/I103635307"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5072373301","display_name":"Zhengyuan Xu","orcid":"https://orcid.org/0000-0001-9075-8875"},"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":"Zhengyuan Xu","raw_affiliation_strings":["Department of Electronic Engineering and Tsinghua National Laboratory of Information Science and Technology, Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Department of Electronic Engineering and Tsinghua National Laboratory of Information Science and Technology, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5053858045","display_name":"Brian M. Sadler","orcid":"https://orcid.org/0000-0002-9564-3812"},"institutions":[{"id":"https://openalex.org/I166416128","display_name":"DEVCOM Army Research Laboratory","ror":"https://ror.org/011hc8f90","country_code":"US","type":"government","lineage":["https://openalex.org/I1304082316","https://openalex.org/I1330347796","https://openalex.org/I166416128","https://openalex.org/I2802705668","https://openalex.org/I4210154437"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Brian M. Sadler","raw_affiliation_strings":["Army Research Laboratory, Adelphi, MD, USA"],"affiliations":[{"raw_affiliation_string":"Army Research Laboratory, Adelphi, MD, USA","institution_ids":["https://openalex.org/I166416128"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5077295091"],"corresponding_institution_ids":["https://openalex.org/I103635307","https://openalex.org/I4210127325"],"apc_list":null,"apc_paid":null,"fwci":2.9461,"has_fulltext":false,"cited_by_count":20,"citation_normalized_percentile":{"value":0.91732772,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":"60","issue":"5","first_page":"2315","last_page":"2329"},"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/T10711","display_name":"Target Tracking and Data Fusion in Sensor Networks","score":0.9987000226974487,"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/T12879","display_name":"Distributed Sensor Networks and Detection Algorithms","score":0.9966999888420105,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/geolocation","display_name":"Geolocation","score":0.9565202593803406},{"id":"https://openalex.org/keywords/estimator","display_name":"Estimator","score":0.7457388639450073},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.5449896454811096},{"id":"https://openalex.org/keywords/multipath-propagation","display_name":"Multipath propagation","score":0.5401282906532288},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.505381166934967},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5030891299247742},{"id":"https://openalex.org/keywords/upper-and-lower-bounds","display_name":"Upper and lower bounds","score":0.48972752690315247},{"id":"https://openalex.org/keywords/cram\u00e9r\u2013rao-bound","display_name":"Cram\u00e9r\u2013Rao bound","score":0.48025014996528625},{"id":"https://openalex.org/keywords/fading","display_name":"Fading","score":0.4671449363231659},{"id":"https://openalex.org/keywords/range","display_name":"Range (aeronautics)","score":0.46673285961151123},{"id":"https://openalex.org/keywords/mean-squared-error","display_name":"Mean squared error","score":0.43882229924201965},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.36844807863235474}],"concepts":[{"id":"https://openalex.org/C22041718","wikidata":"https://www.wikidata.org/wiki/Q638949","display_name":"Geolocation","level":2,"score":0.9565202593803406},{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.7457388639450073},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.5449896454811096},{"id":"https://openalex.org/C161218011","wikidata":"https://www.wikidata.org/wiki/Q11827794","display_name":"Multipath propagation","level":3,"score":0.5401282906532288},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.505381166934967},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5030891299247742},{"id":"https://openalex.org/C77553402","wikidata":"https://www.wikidata.org/wiki/Q13222579","display_name":"Upper and lower bounds","level":2,"score":0.48972752690315247},{"id":"https://openalex.org/C4978587","wikidata":"https://www.wikidata.org/wiki/Q1138810","display_name":"Cram\u00e9r\u2013Rao bound","level":3,"score":0.48025014996528625},{"id":"https://openalex.org/C81978471","wikidata":"https://www.wikidata.org/wiki/Q1196572","display_name":"Fading","level":3,"score":0.4671449363231659},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.46673285961151123},{"id":"https://openalex.org/C139945424","wikidata":"https://www.wikidata.org/wiki/Q1940696","display_name":"Mean squared error","level":2,"score":0.43882229924201965},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.36844807863235474},{"id":"https://openalex.org/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.0},{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.0},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tsp.2012.2187645","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tsp.2012.2187645","pdf_url":null,"source":{"id":"https://openalex.org/S168680287","display_name":"IEEE Transactions on Signal Processing","issn_l":"1053-587X","issn":["1053-587X","1941-0476"],"is_oa":false,"is_in_doaj":false,"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 Transactions on Signal Processing","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":22,"referenced_works":["https://openalex.org/W1513478597","https://openalex.org/W1596939795","https://openalex.org/W1984448020","https://openalex.org/W1984855213","https://openalex.org/W1988543519","https://openalex.org/W1989110752","https://openalex.org/W2014658388","https://openalex.org/W2090705694","https://openalex.org/W2095968873","https://openalex.org/W2103433997","https://openalex.org/W2104479788","https://openalex.org/W2120669138","https://openalex.org/W2123497374","https://openalex.org/W2124178852","https://openalex.org/W2130326036","https://openalex.org/W2130959131","https://openalex.org/W2146027721","https://openalex.org/W2161859912","https://openalex.org/W2296013757","https://openalex.org/W2544775777","https://openalex.org/W4301359260","https://openalex.org/W6674775576"],"related_works":["https://openalex.org/W2376969857","https://openalex.org/W2790822259","https://openalex.org/W207732638","https://openalex.org/W2009659552","https://openalex.org/W2801592279","https://openalex.org/W4252788403","https://openalex.org/W2136261773","https://openalex.org/W2171869298","https://openalex.org/W2034040913","https://openalex.org/W2257001073"],"abstract_inverted_index":{"We":[0,31,54,151],"study":[1,134,199],"geolocation":[2,64,74,136,149,159,173],"based":[3],"on":[4,158,168],"biased":[5,73],"range":[6,34,107],"estimates.":[7,75],"Positive":[8],"bias":[9,45,52,84,109,120],"arises":[10],"using":[11],"time":[12],"delay":[13],"ranging":[14],"methods":[15],"in":[16,69,187],"a":[17,166],"multipath":[18],"fading":[19],"environment,":[20],"when":[21],"the":[22,33,92,106,118,126,147,154,172,182,185,196],"line":[23],"of":[24,105,117,202],"sight":[25],"direct":[26],"path":[27],"is":[28,80,165],"severely":[29],"attenuated.":[30],"model":[32],"measurement":[35,108,119],"as":[36,123,125],"contaminated":[37],"with":[38],"Gaussian":[39],"noise":[40],"and":[41,47,50,60,66,85,94,121,138,178,198],"an":[42],"additive":[43],"nonnegative":[44],"term,":[46],"consider":[48],"deterministic":[49],"random":[51],"cases.":[53,189],"develop":[55,153],"weighted":[56],"least":[57],"squares":[58],"(WLS)":[59],"maximum":[61],"likelihood":[62],"(ML)":[63],"estimators,":[65],"show":[67,180],"that":[68],"general":[70],"they":[71],"yield":[72],"A":[76],"perturbation":[77],"analysis":[78,197],"technique":[79],"applied":[81,140],"to":[82,133,141,194],"find":[83],"mean":[86],"square":[87],"error":[88,113],"(MSE)":[89],"expressions":[90,114],"for":[91,145,160],"WLS":[93],"MLE":[95,97,102],"algorithms.":[96],"generally":[98],"outperforms":[99],"WLS,":[100],"because":[101],"exploits":[103],"knowledge":[104],"distribution.":[110],"The":[111,163],"location":[112],"are":[115,131,139,192],"functions":[116],"variance,":[122],"well":[124],"network":[127],"geometry.":[128],"These":[129],"results":[130],"useful":[132],"achievable":[135],"performance,":[137],"optimize":[142],"sensor":[143],"placement":[144],"improving":[146],"overall":[148],"accuracy.":[150],"also":[152],"Cram\u00e9r-Rao":[155],"bound":[156,167],"(CRB)":[157],"our":[161],"model.":[162],"CRB":[164,186],"unbiased":[169],"estimation,":[170],"whereas":[171],"algorithms":[174],"may":[175],"be":[176],"biased,":[177],"we":[179],"how":[181],"estimators":[183],"approach":[184],"certain":[188],"Numerical":[190],"examples":[191],"presented":[193],"verify":[195],"some":[200],"cases":[201],"interest.":[203]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":1},{"year":2015,"cited_by_count":5},{"year":2014,"cited_by_count":5},{"year":2013,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
