{"id":"https://openalex.org/W2892143400","doi":"https://doi.org/10.23919/icif.2018.8455459","title":"Multi-Sensor Multi-Frame Detection Based on Posterior Probability Density Fusion","display_name":"Multi-Sensor Multi-Frame Detection Based on Posterior Probability Density Fusion","publication_year":2018,"publication_date":"2018-07-01","ids":{"openalex":"https://openalex.org/W2892143400","doi":"https://doi.org/10.23919/icif.2018.8455459","mag":"2892143400"},"language":"en","primary_location":{"id":"doi:10.23919/icif.2018.8455459","is_oa":false,"landing_page_url":"https://doi.org/10.23919/icif.2018.8455459","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 21st International Conference on Information Fusion (FUSION)","raw_type":"proceedings-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/A5033299709","display_name":"Jinghe Wang","orcid":"https://orcid.org/0000-0003-0757-3437"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Jinghe Wang","raw_affiliation_strings":["University of Electronic Science and Technology of China, Chengdu, P.R. China"],"affiliations":[{"raw_affiliation_string":"University of Electronic Science and Technology of China, Chengdu, P.R. China","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100339151","display_name":"Wei Yi","orcid":"https://orcid.org/0000-0001-9878-7048"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wei Yi","raw_affiliation_strings":["University of Electronic Science and Technology of China, Chengdu, P.R. China"],"affiliations":[{"raw_affiliation_string":"University of Electronic Science and Technology of China, Chengdu, P.R. China","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5022778463","display_name":"Lingjiang Kong","orcid":"https://orcid.org/0000-0002-0991-4517"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lingjiang Kong","raw_affiliation_strings":["University of Electronic Science and Technology of China, Chengdu, P.R. China"],"affiliations":[{"raw_affiliation_string":"University of Electronic Science and Technology of China, Chengdu, P.R. China","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5027840989","display_name":"Ye Yuan","orcid":"https://orcid.org/0000-0001-5845-0037"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ye Yuan","raw_affiliation_strings":["University of Electronic Science and Technology of China, Chengdu, P.R. China"],"affiliations":[{"raw_affiliation_string":"University of Electronic Science and Technology of China, Chengdu, P.R. China","institution_ids":["https://openalex.org/I150229711"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5033299709"],"corresponding_institution_ids":["https://openalex.org/I150229711"],"apc_list":null,"apc_paid":null,"fwci":0.5536,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.7063018,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12879","display_name":"Distributed Sensor Networks and Detection Algorithms","score":0.9983000159263611,"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"}},"topics":[{"id":"https://openalex.org/T12879","display_name":"Distributed Sensor Networks and Detection Algorithms","score":0.9983000159263611,"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/T10711","display_name":"Target Tracking and Data Fusion in Sensor Networks","score":0.9980999827384949,"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/T12389","display_name":"Infrared Target Detection Methodologies","score":0.9937999844551086,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.672170102596283},{"id":"https://openalex.org/keywords/frame","display_name":"Frame (networking)","score":0.6396481394767761},{"id":"https://openalex.org/keywords/sensor-fusion","display_name":"Sensor fusion","score":0.5972161293029785},{"id":"https://openalex.org/keywords/posterior-probability","display_name":"Posterior probability","score":0.5940039753913879},{"id":"https://openalex.org/keywords/probability-density-function","display_name":"Probability density function","score":0.5380480289459229},{"id":"https://openalex.org/keywords/fusion","display_name":"Fusion","score":0.44840338826179504},{"id":"https://openalex.org/keywords/node","display_name":"Node (physics)","score":0.44681835174560547},{"id":"https://openalex.org/keywords/mixture-model","display_name":"Mixture model","score":0.4422118663787842},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.4412415027618408},{"id":"https://openalex.org/keywords/probability-distribution","display_name":"Probability distribution","score":0.43475398421287537},{"id":"https://openalex.org/keywords/fusion-center","display_name":"Fusion center","score":0.4330149292945862},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3448227643966675},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3271636366844177},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.20096319913864136},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.13913410902023315},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.13434907793998718},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.10876142978668213},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.0678735077381134}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.672170102596283},{"id":"https://openalex.org/C126042441","wikidata":"https://www.wikidata.org/wiki/Q1324888","display_name":"Frame (networking)","level":2,"score":0.6396481394767761},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.5972161293029785},{"id":"https://openalex.org/C57830394","wikidata":"https://www.wikidata.org/wiki/Q278079","display_name":"Posterior probability","level":3,"score":0.5940039753913879},{"id":"https://openalex.org/C197055811","wikidata":"https://www.wikidata.org/wiki/Q207522","display_name":"Probability density function","level":2,"score":0.5380480289459229},{"id":"https://openalex.org/C158525013","wikidata":"https://www.wikidata.org/wiki/Q2593739","display_name":"Fusion","level":2,"score":0.44840338826179504},{"id":"https://openalex.org/C62611344","wikidata":"https://www.wikidata.org/wiki/Q1062658","display_name":"Node (physics)","level":2,"score":0.44681835174560547},{"id":"https://openalex.org/C61224824","wikidata":"https://www.wikidata.org/wiki/Q2260434","display_name":"Mixture model","level":2,"score":0.4422118663787842},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.4412415027618408},{"id":"https://openalex.org/C149441793","wikidata":"https://www.wikidata.org/wiki/Q200726","display_name":"Probability distribution","level":2,"score":0.43475398421287537},{"id":"https://openalex.org/C2781234732","wikidata":"https://www.wikidata.org/wiki/Q943505","display_name":"Fusion center","level":4,"score":0.4330149292945862},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3448227643966675},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3271636366844177},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.20096319913864136},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.13913410902023315},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.13434907793998718},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.10876142978668213},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.0678735077381134},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C555944384","wikidata":"https://www.wikidata.org/wiki/Q249","display_name":"Wireless","level":2,"score":0.0},{"id":"https://openalex.org/C149946192","wikidata":"https://www.wikidata.org/wiki/Q3235733","display_name":"Cognitive radio","level":3,"score":0.0},{"id":"https://openalex.org/C66938386","wikidata":"https://www.wikidata.org/wiki/Q633538","display_name":"Structural engineering","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/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.23919/icif.2018.8455459","is_oa":false,"landing_page_url":"https://doi.org/10.23919/icif.2018.8455459","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 21st International Conference on Information Fusion (FUSION)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":27,"referenced_works":["https://openalex.org/W1500987287","https://openalex.org/W1501739804","https://openalex.org/W1780608253","https://openalex.org/W1971008109","https://openalex.org/W1985690171","https://openalex.org/W1996452649","https://openalex.org/W1999565686","https://openalex.org/W2011457345","https://openalex.org/W2031702911","https://openalex.org/W2038908796","https://openalex.org/W2040100938","https://openalex.org/W2067341428","https://openalex.org/W2078742450","https://openalex.org/W2086855863","https://openalex.org/W2096403282","https://openalex.org/W2129078811","https://openalex.org/W2129708101","https://openalex.org/W2139460836","https://openalex.org/W2142315243","https://openalex.org/W2163496225","https://openalex.org/W2169396814","https://openalex.org/W2479138194","https://openalex.org/W2545563415","https://openalex.org/W2586283610","https://openalex.org/W2612889333","https://openalex.org/W2748542155","https://openalex.org/W6629934484"],"related_works":["https://openalex.org/W2893341095","https://openalex.org/W4241043257","https://openalex.org/W1990418105","https://openalex.org/W2358572162","https://openalex.org/W1971430736","https://openalex.org/W4242391381","https://openalex.org/W1980528650","https://openalex.org/W4249885815","https://openalex.org/W3199393239","https://openalex.org/W1534282248"],"abstract_inverted_index":{"Multi-frame":[0],"detection":[1,12,41],"(MFD)":[2],"and":[3,13],"multi-sensor":[4,39],"fusion":[5,124],"are":[6],"two":[7,33,96],"popular":[8],"methods":[9,34,183],"of":[10,24,52,95,142,156,166],"target":[11,54,72,132],"estimation":[14],"which":[15],"can":[16,49,69,171],"improve":[17,138],"the":[18,22,45,53,61,65,71,78,91,101,109,119,123,130,139,154,163,181],"performance":[19],"by":[20,75,178],"increasing":[21],"number":[23],"measurement":[25,79],"samples.":[26],"In":[27,89],"this":[28],"paper,":[29],"we":[30],"combine":[31],"these":[32],"together,":[35],"proposing":[36],"a":[37,144],"novel":[38],"multi-frame":[40,62,111],"(MS-MFD)":[42],"method.":[43],"On":[44,64],"one":[46],"hand,":[47,67],"MS-MFD":[48],"make":[50],"use":[51],"information":[55],"as":[56,58],"much":[57],"possible":[59],"through":[60],"integration.":[63],"other":[66],"it":[68,99,117],"acquire":[70],"space-diversity":[73],"gain":[74],"jointly":[76,112],"processing":[77,103],"samples":[80],"on":[81],"different":[82],"observation":[83],"orientations,":[84],"providing":[85],"more":[86],"accurate":[87],"estimates.":[88,133],"particular,":[90],"proposed":[92,151,182],"method":[93,149],"consists":[94],"steps.":[97],"First,":[98],"conducts":[100],"MFD":[102],"in":[104,135],"each":[105],"sensor":[106],"node,":[107],"computing":[108],"local":[110,120,157,167],"posterior":[113,158,168],"probability":[114,159,169],"density.":[115],"Then,":[116],"transmits":[118],"densities":[121],"to":[122,137,152],"center":[125],"for":[126],"further":[127],"processing,":[128],"calculating":[129],"global":[131],"Furthermore,":[134],"order":[136],"implementation":[140],"efficiency":[141],"MS-MFD,":[143],"Gaussian":[145],"Mixture":[146],"model":[147],"based":[148],"is":[150,176],"approximate":[153],"distribution":[155],"density,":[160],"so":[161],"that":[162,180],"transmission":[164],"costs":[165],"density":[170],"be":[172],"significantly":[173],"reduced.":[174],"It":[175],"demonstrated":[177],"simulations":[179],"show":[184],"superior":[185],"performance.":[186]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
