{"id":"https://openalex.org/W2743577840","doi":"https://doi.org/10.23919/icif.2017.8009679","title":"Gaussian mixture particle flow probability hypothesis density filter","display_name":"Gaussian mixture particle flow probability hypothesis density filter","publication_year":2017,"publication_date":"2017-07-01","ids":{"openalex":"https://openalex.org/W2743577840","doi":"https://doi.org/10.23919/icif.2017.8009679","mag":"2743577840"},"language":"en","primary_location":{"id":"doi:10.23919/icif.2017.8009679","is_oa":false,"landing_page_url":"https://doi.org/10.23919/icif.2017.8009679","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 20th International Conference on Information Fusion (Fusion)","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/A5100634342","display_name":"Mingjie Wang","orcid":"https://orcid.org/0000-0001-5542-4079"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Mingjie Wang","raw_affiliation_strings":["School of Electronic Engineering, Xidian University, Xian, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electronic Engineering, Xidian University, Xian, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102805077","display_name":"Hongbing Ji","orcid":"https://orcid.org/0000-0002-6775-518X"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hongbing Ji","raw_affiliation_strings":["School of Electronic Engineering, Xidian University, Xian, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electronic Engineering, Xidian University, Xian, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5039539402","display_name":"Xiaolong Hu","orcid":"https://orcid.org/0000-0003-2173-9229"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaolong Hu","raw_affiliation_strings":["School of Electronic Engineering, Xidian University, Xian, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electronic Engineering, Xidian University, Xian, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101473474","display_name":"Yongquan Zhang","orcid":"https://orcid.org/0000-0003-4768-7279"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yongquan Zhang","raw_affiliation_strings":["School of Electronic Engineering, Xidian University, Xian, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electronic Engineering, Xidian University, Xian, China","institution_ids":["https://openalex.org/I149594827"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I149594827"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"8"},"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9851999878883362,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9703999757766724,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.691290020942688},{"id":"https://openalex.org/keywords/particle-filter","display_name":"Particle filter","score":0.6851645112037659},{"id":"https://openalex.org/keywords/gaussian-filter","display_name":"Gaussian filter","score":0.6592836976051331},{"id":"https://openalex.org/keywords/auxiliary-particle-filter","display_name":"Auxiliary particle filter","score":0.6452231407165527},{"id":"https://openalex.org/keywords/ensemble-kalman-filter","display_name":"Ensemble Kalman filter","score":0.541928768157959},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.5415663123130798},{"id":"https://openalex.org/keywords/tracking","display_name":"Tracking (education)","score":0.46658164262771606},{"id":"https://openalex.org/keywords/nonlinear-filter","display_name":"Nonlinear filter","score":0.46056753396987915},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.45623067021369934},{"id":"https://openalex.org/keywords/kernel-adaptive-filter","display_name":"Kernel adaptive filter","score":0.45508769154548645},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4474484920501709},{"id":"https://openalex.org/keywords/control-theory","display_name":"Control theory (sociology)","score":0.3828904330730438},{"id":"https://openalex.org/keywords/filter-design","display_name":"Filter design","score":0.3722352981567383},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.36273881793022156},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2322603166103363},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.2255510687828064},{"id":"https://openalex.org/keywords/kalman-filter","display_name":"Kalman filter","score":0.18679547309875488},{"id":"https://openalex.org/keywords/extended-kalman-filter","display_name":"Extended Kalman filter","score":0.17640763521194458},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.1579461693763733}],"concepts":[{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.691290020942688},{"id":"https://openalex.org/C52421305","wikidata":"https://www.wikidata.org/wiki/Q1151499","display_name":"Particle filter","level":3,"score":0.6851645112037659},{"id":"https://openalex.org/C65892221","wikidata":"https://www.wikidata.org/wiki/Q1113935","display_name":"Gaussian filter","level":3,"score":0.6592836976051331},{"id":"https://openalex.org/C52483021","wikidata":"https://www.wikidata.org/wiki/Q4827310","display_name":"Auxiliary particle filter","level":5,"score":0.6452231407165527},{"id":"https://openalex.org/C79334102","wikidata":"https://www.wikidata.org/wiki/Q3072268","display_name":"Ensemble Kalman filter","level":4,"score":0.541928768157959},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.5415663123130798},{"id":"https://openalex.org/C2775936607","wikidata":"https://www.wikidata.org/wiki/Q466845","display_name":"Tracking (education)","level":2,"score":0.46658164262771606},{"id":"https://openalex.org/C137685913","wikidata":"https://www.wikidata.org/wiki/Q4316763","display_name":"Nonlinear filter","level":4,"score":0.46056753396987915},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.45623067021369934},{"id":"https://openalex.org/C13107197","wikidata":"https://www.wikidata.org/wiki/Q6394192","display_name":"Kernel adaptive filter","level":4,"score":0.45508769154548645},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4474484920501709},{"id":"https://openalex.org/C47446073","wikidata":"https://www.wikidata.org/wiki/Q5165890","display_name":"Control theory (sociology)","level":3,"score":0.3828904330730438},{"id":"https://openalex.org/C22597639","wikidata":"https://www.wikidata.org/wiki/Q5449227","display_name":"Filter design","level":3,"score":0.3722352981567383},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.36273881793022156},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2322603166103363},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.2255510687828064},{"id":"https://openalex.org/C157286648","wikidata":"https://www.wikidata.org/wiki/Q846780","display_name":"Kalman filter","level":2,"score":0.18679547309875488},{"id":"https://openalex.org/C206833254","wikidata":"https://www.wikidata.org/wiki/Q5421817","display_name":"Extended Kalman filter","level":3,"score":0.17640763521194458},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.1579461693763733},{"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/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"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/C19417346","wikidata":"https://www.wikidata.org/wiki/Q7922","display_name":"Pedagogy","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.23919/icif.2017.8009679","is_oa":false,"landing_page_url":"https://doi.org/10.23919/icif.2017.8009679","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 20th International Conference on Information Fusion (Fusion)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":23,"referenced_works":["https://openalex.org/W70609629","https://openalex.org/W1557595030","https://openalex.org/W1970319972","https://openalex.org/W1976500541","https://openalex.org/W2002594585","https://openalex.org/W2014787937","https://openalex.org/W2024731832","https://openalex.org/W2053257056","https://openalex.org/W2076840531","https://openalex.org/W2077611006","https://openalex.org/W2111324943","https://openalex.org/W2111787305","https://openalex.org/W2137585588","https://openalex.org/W2150330930","https://openalex.org/W2160337655","https://openalex.org/W2161435744","https://openalex.org/W2232374002","https://openalex.org/W2396175075","https://openalex.org/W2503670596","https://openalex.org/W2540670477","https://openalex.org/W6633511732","https://openalex.org/W6676780147","https://openalex.org/W6689777066"],"related_works":["https://openalex.org/W2390366503","https://openalex.org/W2005571217","https://openalex.org/W2153348464","https://openalex.org/W1594773552","https://openalex.org/W2378583827","https://openalex.org/W3172287968","https://openalex.org/W2587350851","https://openalex.org/W2388197328","https://openalex.org/W2133044015","https://openalex.org/W2946745448"],"abstract_inverted_index":{"The":[0],"probability":[1],"hypothesis":[2],"density":[3],"(PHD)":[4],"filter":[5,9,32,128],"is":[6,33,57],"a":[7,25,37,54,64,72,131,135],"promising":[8],"for":[10],"multi-target":[11,20,91],"tracking":[12,92],"which":[13,35],"propagates":[14],"the":[15,19,43,47,61,77,82,85,97,102,107,110,118,126],"posterior":[16,78],"intensity":[17],"of":[18,39,76,84],"state.":[21],"In":[22],"this":[23],"paper,":[24],"Gaussian":[26,44,48,111],"mixture":[27,49,112],"particle":[28,55,113,119],"flow":[29,56],"PHD":[30,50,114,120],"(GMPF-PHD)":[31],"proposed":[34,127],"uses":[36],"bank":[38],"particles":[40,62],"to":[41,59,63,70],"represent":[42],"components":[45],"in":[46,68],"(GM-PHD)":[51],"filter.":[52,121],"Then":[53],"implemented":[58],"migrate":[60],"more":[65,73],"appropriate":[66],"region":[67],"order":[69],"obtain":[71],"accurate":[74],"approximation":[75],"intensity.":[79],"To":[80],"verify":[81],"effectiveness":[83],"algorithm,":[86],"both":[87],"linear":[88],"and":[89,96,117],"nonlinear":[90],"problem":[93],"are":[94,99],"designed,":[95],"performance":[98,133],"compared":[100],"with":[101,134],"classical":[103],"approaches":[104],"such":[105],"as":[106],"GM-PHD":[108],"filter,":[109,116],"(GMP-PHD)":[115],"Simulation":[122],"results":[123],"show":[124],"that":[125],"can":[129],"achieve":[130],"good":[132],"reasonable":[136],"computational":[137],"cost.":[138]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}