{"id":"https://openalex.org/W2743694142","doi":"https://doi.org/10.23919/icif.2017.8009846","title":"Distributed sensor fusion for RFS density with consideration of limited sensing ability","display_name":"Distributed sensor fusion for RFS density with consideration of limited sensing ability","publication_year":2017,"publication_date":"2017-07-01","ids":{"openalex":"https://openalex.org/W2743694142","doi":"https://doi.org/10.23919/icif.2017.8009846","mag":"2743694142"},"language":"en","primary_location":{"id":"doi:10.23919/icif.2017.8009846","is_oa":false,"landing_page_url":"https://doi.org/10.23919/icif.2017.8009846","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/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"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Electronic Science and Technology of China","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100659115","display_name":"Meng Jiang","orcid":"https://orcid.org/0009-0006-7283-6343"},"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":"Meng Jiang","raw_affiliation_strings":["University of Electronic Science and Technology of China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Electronic Science and Technology of China","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5017641817","display_name":"Suqi Li","orcid":"https://orcid.org/0000-0003-2584-5766"},"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":"Suqi Li","raw_affiliation_strings":["University of Electronic Science and Technology of China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Electronic Science and Technology of China","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5032855635","display_name":"Bailu Wang","orcid":"https://orcid.org/0000-0002-0101-934X"},"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":"Bailu Wang","raw_affiliation_strings":["University of Electronic Science and Technology of China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Electronic Science and Technology of China","institution_ids":["https://openalex.org/I150229711"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I150229711"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":23,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"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/T10711","display_name":"Target Tracking and Data Fusion in Sensor Networks","score":0.9995999932289124,"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":0.9995999932289124,"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/T12879","display_name":"Distributed Sensor Networks and Detection Algorithms","score":0.9972000122070312,"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/T12321","display_name":"Insect Pheromone Research and Control","score":0.9480999708175659,"subfield":{"id":"https://openalex.org/subfields/1109","display_name":"Insect Science"},"field":{"id":"https://openalex.org/fields/11","display_name":"Agricultural and Biological Sciences"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/covariance-intersection","display_name":"Covariance intersection","score":0.7357497811317444},{"id":"https://openalex.org/keywords/fusion","display_name":"Fusion","score":0.6695098280906677},{"id":"https://openalex.org/keywords/heuristic","display_name":"Heuristic","score":0.6546989679336548},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6272751688957214},{"id":"https://openalex.org/keywords/sensor-fusion","display_name":"Sensor fusion","score":0.6113747358322144},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5327157378196716},{"id":"https://openalex.org/keywords/intersection","display_name":"Intersection (aeronautics)","score":0.5277018547058105},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.5063046216964722},{"id":"https://openalex.org/keywords/covariance","display_name":"Covariance","score":0.4538487493991852},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4146106541156769},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4139694273471832},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3775554895401001},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.3558844327926636},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.225187748670578},{"id":"https://openalex.org/keywords/covariance-matrix","display_name":"Covariance matrix","score":0.1963246464729309},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.1595824658870697},{"id":"https://openalex.org/keywords/covariance-function","display_name":"Covariance function","score":0.09253042936325073},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.08433040976524353}],"concepts":[{"id":"https://openalex.org/C83042196","wikidata":"https://www.wikidata.org/wiki/Q5178898","display_name":"Covariance intersection","level":4,"score":0.7357497811317444},{"id":"https://openalex.org/C158525013","wikidata":"https://www.wikidata.org/wiki/Q2593739","display_name":"Fusion","level":2,"score":0.6695098280906677},{"id":"https://openalex.org/C173801870","wikidata":"https://www.wikidata.org/wiki/Q201413","display_name":"Heuristic","level":2,"score":0.6546989679336548},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6272751688957214},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.6113747358322144},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5327157378196716},{"id":"https://openalex.org/C64543145","wikidata":"https://www.wikidata.org/wiki/Q162942","display_name":"Intersection (aeronautics)","level":2,"score":0.5277018547058105},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.5063046216964722},{"id":"https://openalex.org/C178650346","wikidata":"https://www.wikidata.org/wiki/Q201984","display_name":"Covariance","level":2,"score":0.4538487493991852},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4146106541156769},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4139694273471832},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3775554895401001},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.3558844327926636},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.225187748670578},{"id":"https://openalex.org/C185142706","wikidata":"https://www.wikidata.org/wiki/Q1134404","display_name":"Covariance matrix","level":2,"score":0.1963246464729309},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.1595824658870697},{"id":"https://openalex.org/C137250428","wikidata":"https://www.wikidata.org/wiki/Q5178897","display_name":"Covariance function","level":3,"score":0.09253042936325073},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.08433040976524353},{"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/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","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/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.23919/icif.2017.8009846","is_oa":false,"landing_page_url":"https://doi.org/10.23919/icif.2017.8009846","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":19,"referenced_works":["https://openalex.org/W34992941","https://openalex.org/W652333456","https://openalex.org/W1571662278","https://openalex.org/W1845932225","https://openalex.org/W1909771825","https://openalex.org/W1994684794","https://openalex.org/W1997942227","https://openalex.org/W2040100938","https://openalex.org/W2045834636","https://openalex.org/W2049244691","https://openalex.org/W2078742450","https://openalex.org/W2084551895","https://openalex.org/W2106360727","https://openalex.org/W2137585588","https://openalex.org/W2154353836","https://openalex.org/W2398058914","https://openalex.org/W2612094279","https://openalex.org/W3217006579","https://openalex.org/W6804679018"],"related_works":["https://openalex.org/W2718384077","https://openalex.org/W4385938064","https://openalex.org/W1597192237","https://openalex.org/W2022823194","https://openalex.org/W2543883930","https://openalex.org/W2317323511","https://openalex.org/W2395573186","https://openalex.org/W2034294006","https://openalex.org/W338040569","https://openalex.org/W2152662039"],"abstract_inverted_index":{"The":[0,16,99],"paper":[1],"addresses":[2],"the":[3,10,59,88],"problem":[4],"of":[5,12,22,44,58,62],"distributed":[6,71],"sensor":[7],"fusion":[8,45,72,78,90],"in":[9,28,38,96],"framework":[11],"random":[13],"finite":[14],"set.":[15],"Generalized":[17],"Covariance":[18],"Intersection":[19],"(GCI)":[20],"rule":[21],"multi-target":[23,29],"densities":[24],"is":[25,104],"extensively":[26],"used":[27],"Bayesian":[30],"filtering":[31],"scheme.":[32],"But":[33],"there":[34],"are":[35,41],"two":[36,64,76,97],"problems":[37],"GCI":[39,89],"which":[40],"unreasonable":[42],"design":[43],"weight":[46,79],"and":[47,81,107],"unable":[48],"to":[49,55],"tackle":[50],"informative":[51],"differentiation.":[52],"In":[53],"order":[54],"get":[56],"rid":[57],"bad":[60],"influence":[61],"these":[63],"problems,":[65],"we":[66,86],"propose":[67],"a":[68],"heuristic":[69],"Heuristic":[70],"(HDF)":[73],"method":[74,95],"by":[75],"steps:":[77],"reconstruction":[80],"information":[82],"difference":[83],"preservation.":[84],"Finally,":[85],"compare":[87],"with":[91],"our":[92],"proposed":[93],"HDF":[94,103],"scenarios.":[98],"results":[100],"show":[101],"that":[102],"more":[105],"robust":[106],"can":[108],"achieve":[109],"better":[110],"performance.":[111]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":5},{"year":2020,"cited_by_count":5},{"year":2019,"cited_by_count":3},{"year":2018,"cited_by_count":3},{"year":2017,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}