{"id":"https://openalex.org/W2009807183","doi":"https://doi.org/10.1109/tro.2014.2378432","title":"A Bank of Maximum &lt;italic&gt;A Posteriori&lt;/italic&gt; (MAP) Estimators for Target Tracking","display_name":"A Bank of Maximum &lt;italic&gt;A Posteriori&lt;/italic&gt; (MAP) Estimators for Target Tracking","publication_year":2015,"publication_date":"2015-01-05","ids":{"openalex":"https://openalex.org/W2009807183","doi":"https://doi.org/10.1109/tro.2014.2378432","mag":"2009807183"},"language":"en","primary_location":{"id":"doi:10.1109/tro.2014.2378432","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tro.2014.2378432","pdf_url":null,"source":{"id":"https://openalex.org/S144620930","display_name":"IEEE Transactions on Robotics","issn_l":"1552-3098","issn":["1552-3098","1546-1904","1941-0468"],"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 Robotics","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/A5008502528","display_name":"Guoquan Huang","orcid":"https://orcid.org/0000-0001-9932-0685"},"institutions":[{"id":"https://openalex.org/I86501945","display_name":"University of Delaware","ror":"https://ror.org/01sbq1a82","country_code":"US","type":"education","lineage":["https://openalex.org/I86501945"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Guoquan Huang","raw_affiliation_strings":["Department of Mechanical Engineering, University of Delaware, Newark, DE, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Mechanical Engineering, University of Delaware, Newark, DE, USA","institution_ids":["https://openalex.org/I86501945"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100689230","display_name":"Ke Zhou","orcid":"https://orcid.org/0000-0002-2005-0932"},"institutions":[{"id":"https://openalex.org/I4210137835","display_name":"Starkey Hearing Technologies (United States)","ror":"https://ror.org/02yhzgr66","country_code":"US","type":"company","lineage":["https://openalex.org/I4210137835"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ke Zhou","raw_affiliation_strings":["Starkey Hearing Technologies, Eden Prairie, MN, USA",", Starkey Hearing Technologies, Eden Prairie, MN, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Starkey Hearing Technologies, Eden Prairie, MN, USA","institution_ids":["https://openalex.org/I4210137835"]},{"raw_affiliation_string":", Starkey Hearing Technologies, Eden Prairie, MN, USA","institution_ids":["https://openalex.org/I4210137835"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5086062660","display_name":"Nikolas Trawny","orcid":null},"institutions":[{"id":"https://openalex.org/I1334627681","display_name":"Jet Propulsion Laboratory","ror":"https://ror.org/027k65916","country_code":"US","type":"facility","lineage":["https://openalex.org/I122411786","https://openalex.org/I1334627681","https://openalex.org/I4210124779"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Nikolas Trawny","raw_affiliation_strings":["NASA Jet Propulsion Laboratory, Pasadena, CA, USA","NASA Jet Propulsion Laboratory, Pasadena, CA USA#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"NASA Jet Propulsion Laboratory, Pasadena, CA, USA","institution_ids":["https://openalex.org/I1334627681"]},{"raw_affiliation_string":"NASA Jet Propulsion Laboratory, Pasadena, CA USA#TAB#","institution_ids":["https://openalex.org/I1334627681"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5025573831","display_name":"Stergios I. Roumeliotis","orcid":"https://orcid.org/0009-0001-3056-0426"},"institutions":[{"id":"https://openalex.org/I130238516","display_name":"University of Minnesota","ror":"https://ror.org/017zqws13","country_code":"US","type":"education","lineage":["https://openalex.org/I130238516"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Stergios I. Roumeliotis","raw_affiliation_strings":["Department of Computer Science and Engineering, University of Minnesota, Minneapolis, MN, USA","Department of Computer Science and Engineering University of Minnesota , Minneapolis , MN , USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, University of Minnesota, Minneapolis, MN, USA","institution_ids":["https://openalex.org/I130238516"]},{"raw_affiliation_string":"Department of Computer Science and Engineering University of Minnesota , Minneapolis , MN , USA","institution_ids":["https://openalex.org/I130238516"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":2.6192,"has_fulltext":false,"cited_by_count":23,"citation_normalized_percentile":{"value":0.91449462,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":"31","issue":"1","first_page":"85","last_page":"103"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10711","display_name":"Target Tracking and Data Fusion in Sensor Networks","score":0.9998999834060669,"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"}},"topics":[{"id":"https://openalex.org/T10711","display_name":"Target Tracking and Data Fusion in Sensor Networks","score":0.9998999834060669,"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":0.9944000244140625,"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"}},{"id":"https://openalex.org/T10326","display_name":"Indoor and Outdoor Localization Technologies","score":0.9736999869346619,"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/estimator","display_name":"Estimator","score":0.7860703468322754},{"id":"https://openalex.org/keywords/extended-kalman-filter","display_name":"Extended Kalman filter","score":0.568652331829071},{"id":"https://openalex.org/keywords/maxima-and-minima","display_name":"Maxima and minima","score":0.5682307481765747},{"id":"https://openalex.org/keywords/linearization","display_name":"Linearization","score":0.5562293529510498},{"id":"https://openalex.org/keywords/kalman-filter","display_name":"Kalman filter","score":0.5303778052330017},{"id":"https://openalex.org/keywords/particle-filter","display_name":"Particle filter","score":0.5177708864212036},{"id":"https://openalex.org/keywords/maximum-a-posteriori-estimation","display_name":"Maximum a posteriori estimation","score":0.5112903118133545},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.5069058537483215},{"id":"https://openalex.org/keywords/trajectory","display_name":"Trajectory","score":0.47781068086624146},{"id":"https://openalex.org/keywords/pruning","display_name":"Pruning","score":0.4462837874889374},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.42893967032432556},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.4274856448173523},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.39016425609588623},{"id":"https://openalex.org/keywords/control-theory","display_name":"Control theory (sociology)","score":0.3735870122909546},{"id":"https://openalex.org/keywords/nonlinear-system","display_name":"Nonlinear system","score":0.27983909845352173},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.22006404399871826},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.16897034645080566}],"concepts":[{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.7860703468322754},{"id":"https://openalex.org/C206833254","wikidata":"https://www.wikidata.org/wiki/Q5421817","display_name":"Extended Kalman filter","level":3,"score":0.568652331829071},{"id":"https://openalex.org/C186633575","wikidata":"https://www.wikidata.org/wiki/Q845060","display_name":"Maxima and minima","level":2,"score":0.5682307481765747},{"id":"https://openalex.org/C11210021","wikidata":"https://www.wikidata.org/wiki/Q1520713","display_name":"Linearization","level":3,"score":0.5562293529510498},{"id":"https://openalex.org/C157286648","wikidata":"https://www.wikidata.org/wiki/Q846780","display_name":"Kalman filter","level":2,"score":0.5303778052330017},{"id":"https://openalex.org/C52421305","wikidata":"https://www.wikidata.org/wiki/Q1151499","display_name":"Particle filter","level":3,"score":0.5177708864212036},{"id":"https://openalex.org/C9810830","wikidata":"https://www.wikidata.org/wiki/Q635384","display_name":"Maximum a posteriori estimation","level":3,"score":0.5112903118133545},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.5069058537483215},{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.47781068086624146},{"id":"https://openalex.org/C108010975","wikidata":"https://www.wikidata.org/wiki/Q500094","display_name":"Pruning","level":2,"score":0.4462837874889374},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.42893967032432556},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.4274856448173523},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.39016425609588623},{"id":"https://openalex.org/C47446073","wikidata":"https://www.wikidata.org/wiki/Q5165890","display_name":"Control theory (sociology)","level":3,"score":0.3735870122909546},{"id":"https://openalex.org/C158622935","wikidata":"https://www.wikidata.org/wiki/Q660848","display_name":"Nonlinear system","level":2,"score":0.27983909845352173},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.22006404399871826},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.16897034645080566},{"id":"https://openalex.org/C2775924081","wikidata":"https://www.wikidata.org/wiki/Q55608371","display_name":"Control (management)","level":2,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C49781872","wikidata":"https://www.wikidata.org/wiki/Q1045555","display_name":"Maximum likelihood","level":2,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","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/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C6557445","wikidata":"https://www.wikidata.org/wiki/Q173113","display_name":"Agronomy","level":1,"score":0.0},{"id":"https://openalex.org/C1276947","wikidata":"https://www.wikidata.org/wiki/Q333","display_name":"Astronomy","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tro.2014.2378432","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tro.2014.2378432","pdf_url":null,"source":{"id":"https://openalex.org/S144620930","display_name":"IEEE Transactions on Robotics","issn_l":"1552-3098","issn":["1552-3098","1546-1904","1941-0468"],"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 Robotics","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10","score":0.699999988079071}],"awards":[{"id":"https://openalex.org/G4465997932","display_name":null,"funder_award_id":"FA9550-10-1-0567","funder_id":"https://openalex.org/F4320338279","funder_display_name":"Air Force Office of Scientific Research"}],"funders":[{"id":"https://openalex.org/F4320309636","display_name":"University of Minnesota","ror":"https://ror.org/03grvy078"},{"id":"https://openalex.org/F4320338279","display_name":"Air Force Office of Scientific Research","ror":"https://ror.org/011e9bt93"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":52,"referenced_works":["https://openalex.org/W576462759","https://openalex.org/W603096258","https://openalex.org/W1483218536","https://openalex.org/W1483307070","https://openalex.org/W1513008779","https://openalex.org/W1531532259","https://openalex.org/W1557368534","https://openalex.org/W1568122762","https://openalex.org/W1592635802","https://openalex.org/W1965392255","https://openalex.org/W1967884132","https://openalex.org/W1976741337","https://openalex.org/W1982711454","https://openalex.org/W1991100990","https://openalex.org/W1999685759","https://openalex.org/W2004958558","https://openalex.org/W2016087001","https://openalex.org/W2018253224","https://openalex.org/W2031837364","https://openalex.org/W2039921094","https://openalex.org/W2041064634","https://openalex.org/W2058946587","https://openalex.org/W2096126935","https://openalex.org/W2097415784","https://openalex.org/W2098613108","https://openalex.org/W2099111195","https://openalex.org/W2103166731","https://openalex.org/W2110501838","https://openalex.org/W2111787305","https://openalex.org/W2114144879","https://openalex.org/W2114914959","https://openalex.org/W2119539043","https://openalex.org/W2121990344","https://openalex.org/W2124313187","https://openalex.org/W2125961820","https://openalex.org/W2129411531","https://openalex.org/W2130363011","https://openalex.org/W2143737806","https://openalex.org/W2155881359","https://openalex.org/W2157066499","https://openalex.org/W2157597051","https://openalex.org/W2158976021","https://openalex.org/W2159297420","https://openalex.org/W2160337655","https://openalex.org/W2478708596","https://openalex.org/W2595897327","https://openalex.org/W2798766386","https://openalex.org/W2798909945","https://openalex.org/W4230946174","https://openalex.org/W4231407710","https://openalex.org/W4242209908","https://openalex.org/W4285719527"],"related_works":["https://openalex.org/W2381377965","https://openalex.org/W2385166520","https://openalex.org/W2358623053","https://openalex.org/W1827457796","https://openalex.org/W2086880567","https://openalex.org/W2186492226","https://openalex.org/W2363887815","https://openalex.org/W1968237764","https://openalex.org/W2009807183","https://openalex.org/W2766161037"],"abstract_inverted_index":{"Nonlinear":[0],"estimation":[1,57],"problems,":[2],"such":[3],"as":[4,29,31,54],"range-only":[5],"and":[6,69,106,124,142,159,174,191],"bearing-only":[7],"target":[8],"tracking,":[9,68],"are":[10,164],"often":[11],"addressed":[12],"using":[13,82],"linearized":[14],"estimators,":[15],"e.g.,":[16],"the":[17,32,63,78,89,102,114,127,139,146,149,168,180,185,188,192],"extended":[18],"Kalman":[19],"filter":[20],"(EKF).":[21],"These":[22,131],"estimators":[23,53],"generally":[24],"suffer":[25],"from":[26],"linearization":[27],"errors":[28],"well":[30],"inability":[33],"to":[34,166],"track":[35],"multimodal":[36],"probability":[37],"density":[38],"functions.":[39],"In":[40],"this":[41],"paper,":[42],"we":[43,100,112],"propose":[44],"a":[45,50,55,83,95],"bank":[46,79],"of":[47,62,148,155,161],"batch":[48],"maximum":[49],"posteriori":[51],"(MAP)":[52],"general":[56],"framework":[58],"that":[59,179],"provides":[60],"relinearization":[61],"entire":[64],"state":[65,86],"trajectory,":[66],"multihypothesis":[67],"an":[70],"efficient":[71],"hypothesis":[72],"generation":[73],"scheme.":[74],"Each":[75],"estimator":[76],"in":[77],"is":[80],"initialized":[81],"locally":[84],"optimal":[85],"estimate":[87],"for":[88,138],"current":[90],"time":[91,94],"step.":[92],"Every":[93],"new":[96],"measurement":[97],"becomes":[98],"available,":[99],"relax":[101],"original":[103],"batch-MAP":[104,189],"problem":[105],"solve":[107],"it":[108],"incrementally.":[109],"More":[110],"specifically,":[111],"convert":[113],"relaxed":[115],"one-step-ahead":[116],"cost":[117],"function":[118],"into":[119],"polynomial":[120],"or":[121],"rational":[122],"form":[123],"compute":[125],"all":[126],"local":[128,132],"minima":[129,133],"analytically.":[130],"generate":[134],"highly":[135],"probable":[136,157],"hypotheses":[137,158],"target's":[140],"trajectory":[141],"hence":[143],"greatly":[144],"improve":[145],"quality":[147],"overall":[150],"MAP":[151],"estimate.":[152],"Additionally,":[153],"pruning":[154],"least":[156],"marginalization":[160],"old":[162],"states":[163],"employed":[165],"control":[167],"computational":[169],"cost.":[170],"Monte":[171],"Carlo":[172],"simulation":[173],"real-world":[175],"experimental":[176],"results":[177],"show":[178],"proposed":[181],"approach":[182],"significantly":[183],"outperforms":[184],"standard":[186],"EKF,":[187],"estimator,":[190],"particle":[193],"filter.":[194]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":6},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":4},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":3},{"year":2016,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
