{"id":"https://openalex.org/W3085147148","doi":"https://doi.org/10.23919/fusion45008.2020.9190385","title":"Multiple Basic Proposal Distributions Model Based Sampling Particle Filter","display_name":"Multiple Basic Proposal Distributions Model Based Sampling Particle Filter","publication_year":2020,"publication_date":"2020-07-01","ids":{"openalex":"https://openalex.org/W3085147148","doi":"https://doi.org/10.23919/fusion45008.2020.9190385","mag":"3085147148"},"language":"en","primary_location":{"id":"doi:10.23919/fusion45008.2020.9190385","is_oa":false,"landing_page_url":"https://doi.org/10.23919/fusion45008.2020.9190385","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE 23rd 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/A5031895350","display_name":"Lihong Shi","orcid":"https://orcid.org/0000-0001-5215-2549"},"institutions":[{"id":"https://openalex.org/I17145004","display_name":"Northwestern Polytechnical University","ror":"https://ror.org/01y0j0j86","country_code":"CN","type":"education","lineage":["https://openalex.org/I17145004"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Lihong Shi","raw_affiliation_strings":["School of Automation Northwestern Polytechnical University, Xi'an, China"],"affiliations":[{"raw_affiliation_string":"School of Automation Northwestern Polytechnical University, Xi'an, China","institution_ids":["https://openalex.org/I17145004"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5062038689","display_name":"Feng Yang","orcid":"https://orcid.org/0000-0001-6991-1628"},"institutions":[{"id":"https://openalex.org/I17145004","display_name":"Northwestern Polytechnical University","ror":"https://ror.org/01y0j0j86","country_code":"CN","type":"education","lineage":["https://openalex.org/I17145004"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Feng Yang","raw_affiliation_strings":["School of Automation Northwestern Polytechnical University, Xi'an, China"],"affiliations":[{"raw_affiliation_string":"School of Automation Northwestern Polytechnical University, Xi'an, China","institution_ids":["https://openalex.org/I17145004"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103184078","display_name":"Litao Zheng","orcid":"https://orcid.org/0000-0003-1050-300X"},"institutions":[{"id":"https://openalex.org/I17145004","display_name":"Northwestern Polytechnical University","ror":"https://ror.org/01y0j0j86","country_code":"CN","type":"education","lineage":["https://openalex.org/I17145004"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Litao Zheng","raw_affiliation_strings":["School of Automation Northwestern Polytechnical University, Xi'an, China"],"affiliations":[{"raw_affiliation_string":"School of Automation Northwestern Polytechnical University, Xi'an, China","institution_ids":["https://openalex.org/I17145004"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5014916744","display_name":"Xiaoxu Wang","orcid":"https://orcid.org/0000-0002-7106-1017"},"institutions":[{"id":"https://openalex.org/I17145004","display_name":"Northwestern Polytechnical University","ror":"https://ror.org/01y0j0j86","country_code":"CN","type":"education","lineage":["https://openalex.org/I17145004"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaoxu Wang","raw_affiliation_strings":["School of Automation Northwestern Polytechnical University, Xi'an, China"],"affiliations":[{"raw_affiliation_string":"School of Automation Northwestern Polytechnical University, Xi'an, China","institution_ids":["https://openalex.org/I17145004"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5031520395","display_name":"Liang Chen","orcid":"https://orcid.org/0000-0001-6644-477X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liang Chen","raw_affiliation_strings":["CETC Key Laboratory of Data Link Technology, Xi'an, China"],"affiliations":[{"raw_affiliation_string":"CETC Key Laboratory of Data Link Technology, Xi'an, China","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5031895350"],"corresponding_institution_ids":["https://openalex.org/I17145004"],"apc_list":null,"apc_paid":null,"fwci":0.1326,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.54529283,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":93},"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":0.9991999864578247,"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":0.9991999864578247,"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/T10326","display_name":"Indoor and Outdoor Localization Technologies","score":0.9955000281333923,"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/T11220","display_name":"Water Systems and Optimization","score":0.9927999973297119,"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/particle-filter","display_name":"Particle filter","score":0.7161592841148376},{"id":"https://openalex.org/keywords/sampling","display_name":"Sampling (signal processing)","score":0.6631721258163452},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5436564683914185},{"id":"https://openalex.org/keywords/importance-sampling","display_name":"Importance sampling","score":0.5356229543685913},{"id":"https://openalex.org/keywords/degeneracy","display_name":"Degeneracy (biology)","score":0.5339637398719788},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5328130722045898},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.5281118154525757},{"id":"https://openalex.org/keywords/auxiliary-particle-filter","display_name":"Auxiliary particle filter","score":0.5156096816062927},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.39885956048965454},{"id":"https://openalex.org/keywords/ensemble-kalman-filter","display_name":"Ensemble Kalman filter","score":0.2635064721107483},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2568223774433136},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2179027497768402},{"id":"https://openalex.org/keywords/kalman-filter","display_name":"Kalman filter","score":0.14558544754981995},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.1398341953754425},{"id":"https://openalex.org/keywords/monte-carlo-method","display_name":"Monte Carlo method","score":0.13030877709388733},{"id":"https://openalex.org/keywords/extended-kalman-filter","display_name":"Extended Kalman filter","score":0.09143736958503723}],"concepts":[{"id":"https://openalex.org/C52421305","wikidata":"https://www.wikidata.org/wiki/Q1151499","display_name":"Particle filter","level":3,"score":0.7161592841148376},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.6631721258163452},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5436564683914185},{"id":"https://openalex.org/C52740198","wikidata":"https://www.wikidata.org/wiki/Q1539564","display_name":"Importance sampling","level":3,"score":0.5356229543685913},{"id":"https://openalex.org/C2777727622","wikidata":"https://www.wikidata.org/wiki/Q5251772","display_name":"Degeneracy (biology)","level":2,"score":0.5339637398719788},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5328130722045898},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.5281118154525757},{"id":"https://openalex.org/C52483021","wikidata":"https://www.wikidata.org/wiki/Q4827310","display_name":"Auxiliary particle filter","level":5,"score":0.5156096816062927},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.39885956048965454},{"id":"https://openalex.org/C79334102","wikidata":"https://www.wikidata.org/wiki/Q3072268","display_name":"Ensemble Kalman filter","level":4,"score":0.2635064721107483},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2568223774433136},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2179027497768402},{"id":"https://openalex.org/C157286648","wikidata":"https://www.wikidata.org/wiki/Q846780","display_name":"Kalman filter","level":2,"score":0.14558544754981995},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.1398341953754425},{"id":"https://openalex.org/C19499675","wikidata":"https://www.wikidata.org/wiki/Q232207","display_name":"Monte Carlo method","level":2,"score":0.13030877709388733},{"id":"https://openalex.org/C206833254","wikidata":"https://www.wikidata.org/wiki/Q5421817","display_name":"Extended Kalman filter","level":3,"score":0.09143736958503723},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.0},{"id":"https://openalex.org/C60644358","wikidata":"https://www.wikidata.org/wiki/Q128570","display_name":"Bioinformatics","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.23919/fusion45008.2020.9190385","is_oa":false,"landing_page_url":"https://doi.org/10.23919/fusion45008.2020.9190385","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE 23rd 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":18,"referenced_works":["https://openalex.org/W1513008779","https://openalex.org/W1968669537","https://openalex.org/W1984626044","https://openalex.org/W2006722592","https://openalex.org/W2040196349","https://openalex.org/W2047978273","https://openalex.org/W2090346540","https://openalex.org/W2098613108","https://openalex.org/W2121990344","https://openalex.org/W2124156864","https://openalex.org/W2126736494","https://openalex.org/W2131946827","https://openalex.org/W2160337655","https://openalex.org/W2401859733","https://openalex.org/W2469934982","https://openalex.org/W2491151330","https://openalex.org/W2770385712","https://openalex.org/W2890557548"],"related_works":["https://openalex.org/W2368144031","https://openalex.org/W3144709167","https://openalex.org/W2355962871","https://openalex.org/W2127981223","https://openalex.org/W2162253570","https://openalex.org/W2109576686","https://openalex.org/W2593675237","https://openalex.org/W2353687059","https://openalex.org/W2124156864","https://openalex.org/W2381817522"],"abstract_inverted_index":{"A":[0],"hybrid":[1,40,60,76],"sampling":[2,8,61,146],"strategy":[3],"is":[4,35,52,66,92],"considered":[5],"in":[6,23,54,86,132],"multimode":[7,145],"based":[9,147],"particle":[10,25,50,91,137,141,148],"filter":[11,51,118,142],"to":[12,28,94,112],"alleviate":[13],"the":[14,19,24,39,72,75,80,88,96,100,116,125,135,139,144],"degeneracy":[15],"as":[16],"one":[17],"of":[18,49,74,82,90,102,115],"most":[20],"typical":[21],"problems":[22],"filter.":[26,149],"However,":[27],"achieve":[29],"high":[30],"accuracy,":[31],"expensive":[32],"computation":[33],"cost":[34],"inevitable":[36],"when":[37],"generating":[38],"distribution.":[41],"To":[42],"overcome":[43],"this":[44,55,68],"problem,":[45],"a":[46],"novel":[47],"framework":[48,69,127],"proposed":[53,117,126],"paper":[56],"with":[57,134],"an":[58],"improved":[59],"strategy.":[62],"The":[63,120],"main":[64],"novelty":[65],"that":[67,124],"can":[70],"simplify":[71],"generation":[73],"distribution":[77],"and":[78,98,143],"makes":[79],"selection":[81],"particles":[83,97],"more":[84],"reasonable,":[85],"which":[87],"likelihood":[89],"used":[93],"select":[95],"determine":[99],"weights":[101],"multiple":[103],"basic":[104],"proposal":[105],"distributions.":[106],"Two":[107],"simulation":[108],"examples":[109],"are":[110],"implemented":[111],"test":[113],"performances":[114,131],"algorithm.":[119],"obtained":[121],"results":[122],"show":[123],"has":[128],"several":[129],"superior":[130],"comparison":[133],"standard":[136],"filter,":[138],"unscented":[140]},"counts_by_year":[{"year":2021,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}