{"id":"https://openalex.org/W2155881359","doi":"https://doi.org/10.1109/tro.2008.2004488","title":"Optimal Motion Strategies for Range-Only Constrained Multisensor Target Tracking","display_name":"Optimal Motion Strategies for Range-Only Constrained Multisensor Target Tracking","publication_year":2008,"publication_date":"2008-09-26","ids":{"openalex":"https://openalex.org/W2155881359","doi":"https://doi.org/10.1109/tro.2008.2004488","mag":"2155881359"},"language":"en","primary_location":{"id":"doi:10.1109/tro.2008.2004488","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tro.2008.2004488","pdf_url":null,"source":{"id":"https://openalex.org/S144620930","display_name":"IEEE Transactions on Robotics","issn_l":"1552-3098","issn":["1552-3098","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/A5100689230","display_name":"Ke Zhou","orcid":"https://orcid.org/0000-0002-2005-0932"},"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":true,"raw_author_name":"Ke Zhou","raw_affiliation_strings":["Department of Electrical and Computer Engineering, University of Minnesota, Minneapolis, MI, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of Minnesota, Minneapolis, MI, USA","institution_ids":["https://openalex.org/I130238516"]}]},{"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":"S.I. Roumeliotis","raw_affiliation_strings":["Department of Computer Science and Engineering, University of Minnesota, Minneapolis, MI, USA"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, University of Minnesota, Minneapolis, MI, USA","institution_ids":["https://openalex.org/I130238516"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5100689230"],"corresponding_institution_ids":["https://openalex.org/I130238516"],"apc_list":null,"apc_paid":null,"fwci":9.3854,"has_fulltext":false,"cited_by_count":90,"citation_normalized_percentile":{"value":0.97747486,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":"24","issue":"5","first_page":"1168","last_page":"1185"},"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":0.9993000030517578,"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":0.9993000030517578,"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/T10249","display_name":"Distributed Control Multi-Agent Systems","score":0.9980000257492065,"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/T12879","display_name":"Distributed Sensor Networks and Detection Algorithms","score":0.9941999912261963,"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/trajectory","display_name":"Trajectory","score":0.6407021284103394},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.609779953956604},{"id":"https://openalex.org/keywords/position","display_name":"Position (finance)","score":0.5916649103164673},{"id":"https://openalex.org/keywords/tracking","display_name":"Tracking (education)","score":0.5909154415130615},{"id":"https://openalex.org/keywords/relaxation","display_name":"Relaxation (psychology)","score":0.5271375179290771},{"id":"https://openalex.org/keywords/computational-complexity-theory","display_name":"Computational complexity theory","score":0.518022358417511},{"id":"https://openalex.org/keywords/range","display_name":"Range (aeronautics)","score":0.4758203327655792},{"id":"https://openalex.org/keywords/grid","display_name":"Grid","score":0.4507179856300354},{"id":"https://openalex.org/keywords/motion-planning","display_name":"Motion planning","score":0.43169742822647095},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.42822569608688354},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4241678714752197},{"id":"https://openalex.org/keywords/linear-programming","display_name":"Linear programming","score":0.4166833162307739},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.3942982256412506},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3304551839828491},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2628246545791626},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.12000122666358948},{"id":"https://openalex.org/keywords/robot","display_name":"Robot","score":0.11603167653083801}],"concepts":[{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.6407021284103394},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.609779953956604},{"id":"https://openalex.org/C198082294","wikidata":"https://www.wikidata.org/wiki/Q3399648","display_name":"Position (finance)","level":2,"score":0.5916649103164673},{"id":"https://openalex.org/C2775936607","wikidata":"https://www.wikidata.org/wiki/Q466845","display_name":"Tracking (education)","level":2,"score":0.5909154415130615},{"id":"https://openalex.org/C2776029896","wikidata":"https://www.wikidata.org/wiki/Q3935810","display_name":"Relaxation (psychology)","level":2,"score":0.5271375179290771},{"id":"https://openalex.org/C179799912","wikidata":"https://www.wikidata.org/wiki/Q205084","display_name":"Computational complexity theory","level":2,"score":0.518022358417511},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.4758203327655792},{"id":"https://openalex.org/C187691185","wikidata":"https://www.wikidata.org/wiki/Q2020720","display_name":"Grid","level":2,"score":0.4507179856300354},{"id":"https://openalex.org/C81074085","wikidata":"https://www.wikidata.org/wiki/Q366872","display_name":"Motion planning","level":3,"score":0.43169742822647095},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.42822569608688354},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4241678714752197},{"id":"https://openalex.org/C41045048","wikidata":"https://www.wikidata.org/wiki/Q202843","display_name":"Linear programming","level":2,"score":0.4166833162307739},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.3942982256412506},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3304551839828491},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2628246545791626},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.12000122666358948},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.11603167653083801},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C77805123","wikidata":"https://www.wikidata.org/wiki/Q161272","display_name":"Social psychology","level":1,"score":0.0},{"id":"https://openalex.org/C146978453","wikidata":"https://www.wikidata.org/wiki/Q3798668","display_name":"Aerospace engineering","level":1,"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/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C1276947","wikidata":"https://www.wikidata.org/wiki/Q333","display_name":"Astronomy","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/C10138342","wikidata":"https://www.wikidata.org/wiki/Q43015","display_name":"Finance","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1109/tro.2008.2004488","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tro.2008.2004488","pdf_url":null,"source":{"id":"https://openalex.org/S144620930","display_name":"IEEE Transactions on Robotics","issn_l":"1552-3098","issn":["1552-3098","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"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.132.6058","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.132.6058","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.cs.umn.edu/research/mars/tr/reports/Ke06.pdf","raw_type":"text"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.157.9962","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.157.9962","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.cs.umn.edu/research/mars/tr/reports/Ke06.pdf","raw_type":"text"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.158.3441","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.158.3441","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.cs.umn.edu/~stergios/papers/TRO_08-optimal-motion-distances.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":32,"referenced_works":["https://openalex.org/W1531532259","https://openalex.org/W1549122080","https://openalex.org/W1580972951","https://openalex.org/W1599534165","https://openalex.org/W1603765807","https://openalex.org/W1653547394","https://openalex.org/W1967769980","https://openalex.org/W1984747682","https://openalex.org/W1989923929","https://openalex.org/W1992200270","https://openalex.org/W2011039300","https://openalex.org/W2021455238","https://openalex.org/W2056288820","https://openalex.org/W2095010934","https://openalex.org/W2107638881","https://openalex.org/W2111063475","https://openalex.org/W2115033790","https://openalex.org/W2123703234","https://openalex.org/W2133054594","https://openalex.org/W2135497071","https://openalex.org/W2140206057","https://openalex.org/W2142425726","https://openalex.org/W2142916297","https://openalex.org/W2143670637","https://openalex.org/W2149083914","https://openalex.org/W2152654928","https://openalex.org/W2160484294","https://openalex.org/W2160540358","https://openalex.org/W2162810566","https://openalex.org/W2296319761","https://openalex.org/W2610857016","https://openalex.org/W4250589301"],"related_works":["https://openalex.org/W1941703695","https://openalex.org/W3131574667","https://openalex.org/W4323768008","https://openalex.org/W4248382324","https://openalex.org/W2084086966","https://openalex.org/W4360995134","https://openalex.org/W2373557848","https://openalex.org/W2088970451","https://openalex.org/W2157008402","https://openalex.org/W2592302855"],"abstract_inverted_index":{"In":[0],"this":[1],"paper,":[2],"we":[3],"study":[4],"the":[5,38,41,57,72,81,84,87,95,103,106,115,126,130,148,161],"problem":[6,25],"of":[7,14,40,59,86,94,105,117,150,157],"optimal":[8],"trajectory":[9],"generation":[10],"for":[11,55,101],"a":[12,18,158],"team":[13],"mobile":[15],"sensors":[16],"tracking":[17],"moving":[19],"target":[20],"using":[21],"distance-only":[22],"measurements.":[23],"This":[24],"is":[26,99,112,133,145],"shown":[27],"to":[28,67,70,135],"be":[29],"NP-hard,":[30],"in":[31,68,114,147],"general,":[32],"when":[33],"constraints":[34],"are":[35,91,122],"imposed":[36],"on":[37],"speed":[39],"sensors.":[42,118],"We":[43],"propose":[44],"two":[45],"algorithms,":[46],"modified":[47],"Gauss-Seidel":[48],"relaxation":[49],"and":[50,152],"linear":[51,113],"programming":[52],"(LP)":[53],"relaxation,":[54],"determining":[56],"set":[58],"feasible":[60],"locations":[61],"that":[62,79,98,125,136,156],"each":[63],"sensor":[64],"should":[65],"move":[66],"order":[69],"collect":[71],"most":[73],"informative":[74],"measurements;":[75],"i.e.,":[76],"distance":[77],"measurements":[78],"minimize":[80],"uncertainty":[82],"about":[83],"position":[85],"target.":[88],"These":[89],"algorithms":[90],"applicable":[92],"regardless":[93],"process":[96],"model":[97],"employed":[100],"describing":[102],"motion":[104,163],"target,":[107,162],"while":[108],"their":[109],"computational":[110,143],"complexity":[111],"number":[116,149],"Extensive":[119],"simulation":[120],"results":[121],"presented":[123],"demonstrating":[124],"performance":[127],"attained":[128],"with":[129,138],"proposed":[131],"methods":[132],"comparable":[134],"obtained":[137],"grid-based":[139],"exhaustive":[140],"search,":[141],"whose":[142],"cost":[144],"exponential":[146],"sensors,":[151],"significantly":[153],"better":[154],"than":[155],"random,":[159],"toward":[160],"strategy.":[164]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":5},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":8},{"year":2019,"cited_by_count":6},{"year":2018,"cited_by_count":3},{"year":2017,"cited_by_count":4},{"year":2016,"cited_by_count":5},{"year":2015,"cited_by_count":8},{"year":2014,"cited_by_count":8},{"year":2013,"cited_by_count":9},{"year":2012,"cited_by_count":8}],"updated_date":"2026-04-05T17:49:38.594831","created_date":"2025-10-10T00:00:00"}