{"id":"https://openalex.org/W2022758405","doi":"https://doi.org/10.1109/icassp.2013.6638895","title":"Particle PHD forward filter-backward simulator for targets in close proximity","display_name":"Particle PHD forward filter-backward simulator for targets in close proximity","publication_year":2013,"publication_date":"2013-05-01","ids":{"openalex":"https://openalex.org/W2022758405","doi":"https://doi.org/10.1109/icassp.2013.6638895","mag":"2022758405"},"language":"en","primary_location":{"id":"doi:10.1109/icassp.2013.6638895","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2013.6638895","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2013 IEEE International Conference on Acoustics, Speech and Signal Processing","raw_type":"proceedings-article"},"type":"conference-paper","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/A5109923658","display_name":"Ramona Georgescu","orcid":null},"institutions":[{"id":"https://openalex.org/I140172145","display_name":"University of Connecticut","ror":"https://ror.org/02der9h97","country_code":"US","type":"education","lineage":["https://openalex.org/I140172145"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ramona Georgescu","raw_affiliation_strings":["Department of Electrical and Computer Engineering, University of Connecticut, Storrs, CT, USA","Dept. of Electr. & Comput. Eng., Univ. of Connecticut, Storrs, CT, USA#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of Connecticut, Storrs, CT, USA","institution_ids":["https://openalex.org/I140172145"]},{"raw_affiliation_string":"Dept. of Electr. & Comput. Eng., Univ. of Connecticut, Storrs, CT, USA#TAB#","institution_ids":["https://openalex.org/I140172145"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5019392883","display_name":"Peter Willett","orcid":"https://orcid.org/0000-0001-8443-5586"},"institutions":[{"id":"https://openalex.org/I140172145","display_name":"University of Connecticut","ror":"https://ror.org/02der9h97","country_code":"US","type":"education","lineage":["https://openalex.org/I140172145"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Peter Willett","raw_affiliation_strings":["Department of Electrical and Computer Engineering, University of Connecticut, Storrs, CT, USA","Dept. of Electr. & Comput. Eng., Univ. of Connecticut, Storrs, CT, USA#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of Connecticut, Storrs, CT, USA","institution_ids":["https://openalex.org/I140172145"]},{"raw_affiliation_string":"Dept. of Electr. & Comput. Eng., Univ. of Connecticut, Storrs, CT, USA#TAB#","institution_ids":["https://openalex.org/I140172145"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5029413988","display_name":"Lennart Svensson","orcid":"https://orcid.org/0000-0003-0206-9186"},"institutions":[{"id":"https://openalex.org/I66862912","display_name":"Chalmers University of Technology","ror":"https://ror.org/040wg7k59","country_code":"SE","type":"education","lineage":["https://openalex.org/I66862912"]}],"countries":["SE"],"is_corresponding":false,"raw_author_name":"Lennart Svensson","raw_affiliation_strings":["Department of Signals and Systems, Chalmers University of Technology, Gothenburg, Sweden","[Dept. of Signals and systems, Chalmers University of Technology, Gothenburg, Sweden]"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Signals and Systems, Chalmers University of Technology, Gothenburg, Sweden","institution_ids":["https://openalex.org/I66862912"]},{"raw_affiliation_string":"[Dept. of Signals and systems, Chalmers University of Technology, Gothenburg, Sweden]","institution_ids":["https://openalex.org/I66862912"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.11001469,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":"1953","issue":null,"first_page":"6387","last_page":"6391"},"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/T12814","display_name":"Gaussian Processes and Bayesian Inference","score":0.9962000250816345,"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/T10534","display_name":"Structural Health Monitoring Techniques","score":0.9876999855041504,"subfield":{"id":"https://openalex.org/subfields/2205","display_name":"Civil and Structural 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/tracking","display_name":"Tracking (education)","score":0.698251485824585},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.6597961187362671},{"id":"https://openalex.org/keywords/particle-filter","display_name":"Particle filter","score":0.6290151476860046},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5948753356933594},{"id":"https://openalex.org/keywords/smoothing","display_name":"Smoothing","score":0.5072905421257019},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.4878135025501251},{"id":"https://openalex.org/keywords/simulation","display_name":"Simulation","score":0.4548724889755249},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4162994921207428},{"id":"https://openalex.org/keywords/control-theory","display_name":"Control theory (sociology)","score":0.40374019742012024},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.1763160526752472},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.1726384460926056}],"concepts":[{"id":"https://openalex.org/C2775936607","wikidata":"https://www.wikidata.org/wiki/Q466845","display_name":"Tracking (education)","level":2,"score":0.698251485824585},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.6597961187362671},{"id":"https://openalex.org/C52421305","wikidata":"https://www.wikidata.org/wiki/Q1151499","display_name":"Particle filter","level":3,"score":0.6290151476860046},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5948753356933594},{"id":"https://openalex.org/C3770464","wikidata":"https://www.wikidata.org/wiki/Q775963","display_name":"Smoothing","level":2,"score":0.5072905421257019},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.4878135025501251},{"id":"https://openalex.org/C44154836","wikidata":"https://www.wikidata.org/wiki/Q45045","display_name":"Simulation","level":1,"score":0.4548724889755249},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4162994921207428},{"id":"https://openalex.org/C47446073","wikidata":"https://www.wikidata.org/wiki/Q5165890","display_name":"Control theory (sociology)","level":3,"score":0.40374019742012024},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.1763160526752472},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.1726384460926056},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"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/C2775924081","wikidata":"https://www.wikidata.org/wiki/Q55608371","display_name":"Control (management)","level":2,"score":0.0},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/icassp.2013.6638895","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2013.6638895","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2013 IEEE International Conference on Acoustics, Speech and Signal Processing","raw_type":"proceedings-article"},{"id":"pmh:oai:publications.lib.chalmers.se:191766","is_oa":false,"landing_page_url":"http://publications.lib.chalmers.se/publication/191766-particle-phd-forward-filter-backward-simulator-for-targets-in-close-proximity","pdf_url":null,"source":{"id":"https://openalex.org/S4377196470","display_name":"Chalmers Publication Library (Chalmers University of Technology)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I66862912","host_organization_name":"Chalmers University of Technology","host_organization_lineage":["https://openalex.org/I66862912"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Text.Article.Conference.PeerReviewed"},{"id":"pmh:oai:research.chalmers.se:191766","is_oa":false,"landing_page_url":"https://research.chalmers.se/en/publication/191766","pdf_url":null,"source":{"id":"https://openalex.org/S4306402469","display_name":"Chalmers Research (Chalmers University of Technology)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I66862912","host_organization_name":"Chalmers University of Technology","host_organization_lineage":["https://openalex.org/I66862912"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10","score":0.75}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":18,"referenced_works":["https://openalex.org/W170647656","https://openalex.org/W1486632395","https://openalex.org/W1601879150","https://openalex.org/W1965828084","https://openalex.org/W2076526444","https://openalex.org/W2088369031","https://openalex.org/W2102547079","https://openalex.org/W2103124057","https://openalex.org/W2104146079","https://openalex.org/W2105959128","https://openalex.org/W2108627383","https://openalex.org/W2165742115","https://openalex.org/W3143184696","https://openalex.org/W6635967269","https://openalex.org/W6641416324","https://openalex.org/W6675414472","https://openalex.org/W6675697470","https://openalex.org/W6676108063"],"related_works":["https://openalex.org/W1978572805","https://openalex.org/W1989212443","https://openalex.org/W2103644279","https://openalex.org/W4302986566","https://openalex.org/W1968585197","https://openalex.org/W2135362996","https://openalex.org/W2163445067","https://openalex.org/W4247544095","https://openalex.org/W2122155275","https://openalex.org/W2215635302"],"abstract_inverted_index":{"In":[0],"this":[1],"work,":[2],"we":[3],"introduce":[4],"the":[5,20,55,58,74,92,105,110,119],"particle":[6,71,112],"PHD":[7],"forward":[8,67],"filter":[9,68,79,113],"-":[10],"backward":[11],"simulator":[12],"(PHD-FFBSi)":[13],"capable":[14],"of":[15,22,57,60,73,94,114,121,131],"dealing":[16],"with":[17,33],"uncertainties":[18],"in":[19,30,118],"labeling":[21],"tracks":[23],"that":[24,35,80,88],"appear":[25],"when":[26],"tracking":[27],"two":[28],"targets":[29,63],"close":[31],"proximity":[32],"measurements":[34],"do":[36],"not":[37],"discriminate":[38],"between":[39,62],"them.":[40],"The":[41,66],"Forward":[42],"Filter":[43],"Backward":[44],"Simulator":[45],"is":[46,69],"a":[47,70],"smoothing":[48],"technique":[49],"based":[50],"on":[51],"rejection":[52],"sampling":[53],"for":[54],"calculation":[56],"probabilities":[59,127],"association":[61],"and":[64,97],"tracks.":[65],"implementation":[72],"Probability":[75],"Hypothesis":[76],"Density":[77],"(PHD)":[78],"presents":[81],"advantages":[82],"over":[83],"an":[84],"SIR":[85],"filter.":[86],"Difficulties":[87],"arise":[89],"due":[90],"to":[91,104],"presence":[93],"target":[95,125],"birth":[96],"death":[98],"processes":[99],"are":[100],"addressed":[101],"through":[102],"modifications":[103],"fast":[106],"FFBSi.":[107],"Simulations":[108],"show":[109],"new":[111],"asymptotically":[115],"linear":[116],"complexity":[117],"number":[120],"particles":[122],"calculates":[123],"correct":[124],"label":[126],"at":[128],"varying":[129],"levels":[130],"measurement":[132],"noise.":[133]},"counts_by_year":[{"year":2024,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}