{"id":"https://openalex.org/W3020402385","doi":"https://doi.org/10.1109/lsp.2020.2988178","title":"Range and Bearing Data Fusion for Precise Convex Network Localization","display_name":"Range and Bearing Data Fusion for Precise Convex Network Localization","publication_year":2020,"publication_date":"2020-01-01","ids":{"openalex":"https://openalex.org/W3020402385","doi":"https://doi.org/10.1109/lsp.2020.2988178","mag":"3020402385"},"language":"en","primary_location":{"id":"doi:10.1109/lsp.2020.2988178","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lsp.2020.2988178","pdf_url":null,"source":{"id":"https://openalex.org/S120629676","display_name":"IEEE Signal Processing Letters","issn_l":"1070-9908","issn":["1070-9908","1558-2361"],"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 Signal Processing Letters","raw_type":"journal-article"},"type":"article","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2110.03523","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Claudia Soares","orcid":"https://orcid.org/0000-0003-3071-6627"},"institutions":[{"id":"https://openalex.org/I141596103","display_name":"University of Lisbon","ror":"https://ror.org/01c27hj86","country_code":"PT","type":"education","lineage":["https://openalex.org/I141596103"]},{"id":"https://openalex.org/I4210166615","display_name":"INESC TEC","ror":"https://ror.org/05fa8ka61","country_code":"PT","type":"nonprofit","lineage":["https://openalex.org/I4210125590","https://openalex.org/I4210166615"]}],"countries":["PT"],"is_corresponding":false,"raw_author_name":"Claudia Soares","raw_affiliation_strings":["Instituto Superior T\u00e9cnico, Institute for Systems and Robotics, Universidade de Lisboa, Lisbon, Portugal"],"raw_orcid":"https://orcid.org/0000-0003-3071-6627","affiliations":[{"raw_affiliation_string":"Instituto Superior T\u00e9cnico, Institute for Systems and Robotics, Universidade de Lisboa, Lisbon, Portugal","institution_ids":["https://openalex.org/I141596103","https://openalex.org/I4210166615"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Filipa Valdeira","orcid":"https://orcid.org/0000-0003-1290-4798"},"institutions":[{"id":"https://openalex.org/I189158943","display_name":"University of Milan","ror":"https://ror.org/00wjc7c48","country_code":"IT","type":"education","lineage":["https://openalex.org/I189158943"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Filipa Valdeira","raw_affiliation_strings":["University of Milan, Milan, Italy"],"raw_orcid":"https://orcid.org/0000-0003-1290-4798","affiliations":[{"raw_affiliation_string":"University of Milan, Milan, Italy","institution_ids":["https://openalex.org/I189158943"]}]},{"author_position":"last","author":{"id":null,"display_name":"Joao Gomes","orcid":"https://orcid.org/0000-0002-3524-5556"},"institutions":[{"id":"https://openalex.org/I141596103","display_name":"University of Lisbon","ror":"https://ror.org/01c27hj86","country_code":"PT","type":"education","lineage":["https://openalex.org/I141596103"]},{"id":"https://openalex.org/I4210166615","display_name":"INESC TEC","ror":"https://ror.org/05fa8ka61","country_code":"PT","type":"nonprofit","lineage":["https://openalex.org/I4210125590","https://openalex.org/I4210166615"]}],"countries":["PT"],"is_corresponding":false,"raw_author_name":"Joao Gomes","raw_affiliation_strings":["Instituto Superior T\u00e9cnico, Institute for Systems and Robotics, Universidade de Lisboa, Lisbon, Portugal"],"raw_orcid":"https://orcid.org/0000-0002-3524-5556","affiliations":[{"raw_affiliation_string":"Instituto Superior T\u00e9cnico, Institute for Systems and Robotics, Universidade de Lisboa, Lisbon, Portugal","institution_ids":["https://openalex.org/I141596103","https://openalex.org/I4210166615"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0813,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.37523555,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":"27","issue":null,"first_page":"670","last_page":"674"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10326","display_name":"Indoor and Outdoor Localization Technologies","score":0.9351000189781189,"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":0.9351000189781189,"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":0.010999999940395355,"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":0.005799999926239252,"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/pairwise-comparison","display_name":"Pairwise comparison","score":0.7113999724388123},{"id":"https://openalex.org/keywords/range","display_name":"Range (aeronautics)","score":0.6807000041007996},{"id":"https://openalex.org/keywords/relaxation","display_name":"Relaxation (psychology)","score":0.5573999881744385},{"id":"https://openalex.org/keywords/convex-optimization","display_name":"Convex optimization","score":0.5195000171661377},{"id":"https://openalex.org/keywords/sensor-fusion","display_name":"Sensor fusion","score":0.5181999802589417},{"id":"https://openalex.org/keywords/regular-polygon","display_name":"Regular polygon","score":0.4771000146865845},{"id":"https://openalex.org/keywords/fuse","display_name":"Fuse (electrical)","score":0.4713999927043915},{"id":"https://openalex.org/keywords/fusion","display_name":"Fusion","score":0.4512999951839447},{"id":"https://openalex.org/keywords/state","display_name":"State (computer science)","score":0.4138999879360199}],"concepts":[{"id":"https://openalex.org/C184898388","wikidata":"https://www.wikidata.org/wiki/Q1435712","display_name":"Pairwise comparison","level":2,"score":0.7113999724388123},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.6807000041007996},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.559499979019165},{"id":"https://openalex.org/C2776029896","wikidata":"https://www.wikidata.org/wiki/Q3935810","display_name":"Relaxation (psychology)","level":2,"score":0.5573999881744385},{"id":"https://openalex.org/C157972887","wikidata":"https://www.wikidata.org/wiki/Q463359","display_name":"Convex optimization","level":3,"score":0.5195000171661377},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.5181999802589417},{"id":"https://openalex.org/C112680207","wikidata":"https://www.wikidata.org/wiki/Q714886","display_name":"Regular polygon","level":2,"score":0.4771000146865845},{"id":"https://openalex.org/C141353440","wikidata":"https://www.wikidata.org/wiki/Q182221","display_name":"Fuse (electrical)","level":2,"score":0.4713999927043915},{"id":"https://openalex.org/C158525013","wikidata":"https://www.wikidata.org/wiki/Q2593739","display_name":"Fusion","level":2,"score":0.4512999951839447},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4442000091075897},{"id":"https://openalex.org/C48103436","wikidata":"https://www.wikidata.org/wiki/Q599031","display_name":"State (computer science)","level":2,"score":0.4138999879360199},{"id":"https://openalex.org/C137836250","wikidata":"https://www.wikidata.org/wiki/Q984063","display_name":"Optimization problem","level":2,"score":0.41029998660087585},{"id":"https://openalex.org/C199978012","wikidata":"https://www.wikidata.org/wiki/Q1273815","display_name":"Bearing (navigation)","level":2,"score":0.4016000032424927},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3666999936103821},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.365200012922287},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.3555000126361847},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3273000121116638},{"id":"https://openalex.org/C148764684","wikidata":"https://www.wikidata.org/wiki/Q621751","display_name":"Approximation algorithm","level":2,"score":0.3059999942779541},{"id":"https://openalex.org/C147764199","wikidata":"https://www.wikidata.org/wiki/Q6865248","display_name":"Minification","level":2,"score":0.304500013589859},{"id":"https://openalex.org/C160920958","wikidata":"https://www.wikidata.org/wiki/Q7662746","display_name":"Synthetic data","level":2,"score":0.30219998955726624},{"id":"https://openalex.org/C29265498","wikidata":"https://www.wikidata.org/wiki/Q7047719","display_name":"Noise measurement","level":3,"score":0.29980000853538513},{"id":"https://openalex.org/C145446738","wikidata":"https://www.wikidata.org/wiki/Q319913","display_name":"Convex function","level":3,"score":0.289000004529953},{"id":"https://openalex.org/C32022120","wikidata":"https://www.wikidata.org/wiki/Q797225","display_name":"Interference (communication)","level":3,"score":0.28279998898506165},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.27639999985694885},{"id":"https://openalex.org/C24590314","wikidata":"https://www.wikidata.org/wiki/Q336038","display_name":"Wireless sensor network","level":2,"score":0.2694000005722046},{"id":"https://openalex.org/C179799912","wikidata":"https://www.wikidata.org/wiki/Q205084","display_name":"Computational complexity theory","level":2,"score":0.26910001039505005},{"id":"https://openalex.org/C2780009758","wikidata":"https://www.wikidata.org/wiki/Q6804172","display_name":"Measure (data warehouse)","level":2,"score":0.2596000134944916},{"id":"https://openalex.org/C111110010","wikidata":"https://www.wikidata.org/wiki/Q2627315","display_name":"Convex combination","level":4,"score":0.2551000118255615},{"id":"https://openalex.org/C54829058","wikidata":"https://www.wikidata.org/wiki/Q172937","display_name":"Polyhedron","level":2,"score":0.2547999918460846}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/lsp.2020.2988178","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lsp.2020.2988178","pdf_url":null,"source":{"id":"https://openalex.org/S120629676","display_name":"IEEE Signal Processing Letters","issn_l":"1070-9908","issn":["1070-9908","1558-2361"],"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 Signal Processing Letters","raw_type":"journal-article"},{"id":"pmh:oai:arXiv.org:2110.03523","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2110.03523","pdf_url":"https://arxiv.org/pdf/2110.03523","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2110.03523","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2110.03523","pdf_url":"https://arxiv.org/pdf/2110.03523","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":31,"referenced_works":["https://openalex.org/W1606988878","https://openalex.org/W1969142081","https://openalex.org/W1974074109","https://openalex.org/W1988543519","https://openalex.org/W2008141156","https://openalex.org/W2026717988","https://openalex.org/W2038946940","https://openalex.org/W2110862165","https://openalex.org/W2114674709","https://openalex.org/W2121355928","https://openalex.org/W2121408477","https://openalex.org/W2296150501","https://openalex.org/W2305658817","https://openalex.org/W2343448572","https://openalex.org/W2405272596","https://openalex.org/W2415492947","https://openalex.org/W2524898498","https://openalex.org/W2528961900","https://openalex.org/W2609416538","https://openalex.org/W2770299322","https://openalex.org/W2794385989","https://openalex.org/W2809824420","https://openalex.org/W2889413276","https://openalex.org/W2902029518","https://openalex.org/W2908764396","https://openalex.org/W2963575222","https://openalex.org/W2963784016","https://openalex.org/W2964173589","https://openalex.org/W4242880064","https://openalex.org/W6679995126","https://openalex.org/W6765869118"],"related_works":[],"abstract_inverted_index":{"Hybrid":[0],"localization":[1,29,112],"in":[2,14,89,109],"GNSS-challenged":[3],"environments":[4],"using":[5,31],"measured":[6],"ranges":[7,32],"and":[8,33,60,83,114],"angles":[9],"is":[10,115],"becoming":[11],"increasingly":[12],"popular,":[13],"particular":[15],"with":[16],"the":[17,26,38,56,70,78,81,100],"advent":[18],"of":[19,40,43,80,99,107,111],"multimodal":[20],"communication":[21],"systems.":[22],"Here,":[23],"we":[24,73,84],"address":[25],"hybrid":[27],"network":[28],"problem":[30,51],"bearings":[34],"to":[35,69,117],"jointly":[36],"determine":[37],"positions":[39],"a":[41,46,65,97],"number":[42],"agents":[44],"through":[45],"single":[47],"maximum-likelihood":[48],"(ML)":[49],"optimization":[50],"that":[52,93],"seamlessly":[53],"fuses":[54],"all":[55],"available":[57],"pairwise":[58],"range":[59],"angle":[61],"measurements.":[62],"We":[63,91],"propose":[64],"tight":[66],"convex":[67],"surrogate":[68],"ML":[71],"estimator,":[72],"examine":[74],"practical":[75],"measures":[76],"for":[77],"accuracy":[79],"relaxation,":[82],"comprehensively":[85],"characterize":[86],"its":[87],"behavior":[88],"simulation.":[90],"found":[92],"our":[94],"relaxation":[95,103],"outperforms":[96],"state":[98],"art":[101],"SDP":[102],"by":[104],"one":[105],"order":[106],"magnitude":[108],"terms":[110],"error,":[113],"amenable":[116],"much":[118],"more":[119],"lightweight":[120],"solution":[121],"algorithms.":[122]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1}],"updated_date":"2026-07-22T07:51:19.307946","created_date":"2020-05-01T00:00:00"}