{"id":"https://openalex.org/W4312520746","doi":"https://doi.org/10.1109/tsmc.2022.3212975","title":"A Background-Impulse Kalman Filter With Non-Gaussian Measurement Noises","display_name":"A Background-Impulse Kalman Filter With Non-Gaussian Measurement Noises","publication_year":2022,"publication_date":"2022-11-03","ids":{"openalex":"https://openalex.org/W4312520746","doi":"https://doi.org/10.1109/tsmc.2022.3212975"},"language":"en","primary_location":{"id":"doi:10.1109/tsmc.2022.3212975","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tsmc.2022.3212975","pdf_url":null,"source":{"id":"https://openalex.org/S4210209078","display_name":"IEEE Transactions on Systems Man and Cybernetics Systems","issn_l":"2168-2216","issn":["2168-2216","2168-2232"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Systems, Man, and Cybernetics: Systems","raw_type":"journal-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/A5058646311","display_name":"Xuxiang Fan","orcid":"https://orcid.org/0000-0003-4997-8344"},"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":"Xuxiang Fan","raw_affiliation_strings":["School of Information and Communication Engineering, University of Electronic Science and Technology of China, Chengdu, China"],"raw_orcid":"https://orcid.org/0000-0003-4997-8344","affiliations":[{"raw_affiliation_string":"School of Information and Communication Engineering, University of Electronic Science and Technology of China, Chengdu, China","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100688670","display_name":"Gang Wang","orcid":"https://orcid.org/0000-0002-7150-1000"},"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":"Gang Wang","raw_affiliation_strings":["School of Information and Communication Engineering, University of Electronic Science and Technology of China, Chengdu, China"],"raw_orcid":"https://orcid.org/0000-0002-7150-1000","affiliations":[{"raw_affiliation_string":"School of Information and Communication Engineering, University of Electronic Science and Technology of China, Chengdu, China","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5051530417","display_name":"Jiachen Han","orcid":"https://orcid.org/0000-0002-4811-5048"},"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":"Jiachen Han","raw_affiliation_strings":["School of Information and Communication Engineering, University of Electronic Science and Technology of China, Chengdu, China"],"raw_orcid":"https://orcid.org/0000-0002-4811-5048","affiliations":[{"raw_affiliation_string":"School of Information and Communication Engineering, University of Electronic Science and Technology of China, Chengdu, China","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100443379","display_name":"Yinghui Wang","orcid":"https://orcid.org/0000-0001-5853-4513"},"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":"Yinghui Wang","raw_affiliation_strings":["School of Information and Communication Engineering, University of Electronic Science and Technology of China, Chengdu, China"],"raw_orcid":"https://orcid.org/0000-0001-5853-4513","affiliations":[{"raw_affiliation_string":"School of Information and Communication Engineering, University of Electronic Science and Technology of China, Chengdu, China","institution_ids":["https://openalex.org/I150229711"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":8.1851,"has_fulltext":false,"cited_by_count":61,"citation_normalized_percentile":{"value":0.97936769,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":100},"biblio":{"volume":"53","issue":"4","first_page":"2434","last_page":"2443"},"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":0.9993000030517578,"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":0.9993000030517578,"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/T11233","display_name":"Advanced Adaptive Filtering Techniques","score":0.9911999702453613,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"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/T10534","display_name":"Structural Health Monitoring Techniques","score":0.9851999878883362,"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/impulse-noise","display_name":"Impulse noise","score":0.7566242218017578},{"id":"https://openalex.org/keywords/gaussian-noise","display_name":"Gaussian noise","score":0.6841869354248047},{"id":"https://openalex.org/keywords/kalman-filter","display_name":"Kalman filter","score":0.6265593767166138},{"id":"https://openalex.org/keywords/value-noise","display_name":"Value noise","score":0.6069018840789795},{"id":"https://openalex.org/keywords/gradient-noise","display_name":"Gradient noise","score":0.5641672015190125},{"id":"https://openalex.org/keywords/noise-measurement","display_name":"Noise measurement","score":0.5532707571983337},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.5227822661399841},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.509306788444519},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.5008676052093506},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.49968552589416504},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.40648943185806274},{"id":"https://openalex.org/keywords/noise-floor","display_name":"Noise floor","score":0.28380483388900757},{"id":"https://openalex.org/keywords/noise-reduction","display_name":"Noise reduction","score":0.2514333128929138},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.12230426073074341}],"concepts":[{"id":"https://openalex.org/C127372701","wikidata":"https://www.wikidata.org/wiki/Q16979398","display_name":"Impulse noise","level":3,"score":0.7566242218017578},{"id":"https://openalex.org/C4199805","wikidata":"https://www.wikidata.org/wiki/Q2725903","display_name":"Gaussian noise","level":2,"score":0.6841869354248047},{"id":"https://openalex.org/C157286648","wikidata":"https://www.wikidata.org/wiki/Q846780","display_name":"Kalman filter","level":2,"score":0.6265593767166138},{"id":"https://openalex.org/C182163834","wikidata":"https://www.wikidata.org/wiki/Q2926529","display_name":"Value noise","level":5,"score":0.6069018840789795},{"id":"https://openalex.org/C200378446","wikidata":"https://www.wikidata.org/wiki/Q4147391","display_name":"Gradient noise","level":5,"score":0.5641672015190125},{"id":"https://openalex.org/C29265498","wikidata":"https://www.wikidata.org/wiki/Q7047719","display_name":"Noise measurement","level":3,"score":0.5532707571983337},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.5227822661399841},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.509306788444519},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.5008676052093506},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.49968552589416504},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.40648943185806274},{"id":"https://openalex.org/C187612029","wikidata":"https://www.wikidata.org/wiki/Q17083130","display_name":"Noise floor","level":4,"score":0.28380483388900757},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.2514333128929138},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.12230426073074341},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tsmc.2022.3212975","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tsmc.2022.3212975","pdf_url":null,"source":{"id":"https://openalex.org/S4210209078","display_name":"IEEE Transactions on Systems Man and Cybernetics Systems","issn_l":"2168-2216","issn":["2168-2216","2168-2232"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Systems, Man, and Cybernetics: Systems","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G8643645171","display_name":null,"funder_award_id":"2022YFG0343","funder_id":"https://openalex.org/F4320333335","funder_display_name":"Sichuan Province Science and Technology Support Program"}],"funders":[{"id":"https://openalex.org/F4320333335","display_name":"Sichuan Province Science and Technology Support Program","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":42,"referenced_works":["https://openalex.org/W1979731521","https://openalex.org/W2015457939","https://openalex.org/W2076222362","https://openalex.org/W2100924160","https://openalex.org/W2105934661","https://openalex.org/W2106144084","https://openalex.org/W2119115893","https://openalex.org/W2127394248","https://openalex.org/W2145313039","https://openalex.org/W2156064084","https://openalex.org/W2171998198","https://openalex.org/W2294296888","https://openalex.org/W2344935686","https://openalex.org/W2566269102","https://openalex.org/W2594495318","https://openalex.org/W2608865523","https://openalex.org/W2760511685","https://openalex.org/W2783617685","https://openalex.org/W2802343782","https://openalex.org/W2884237909","https://openalex.org/W2914726464","https://openalex.org/W2917903122","https://openalex.org/W2946305700","https://openalex.org/W2951837999","https://openalex.org/W2953792346","https://openalex.org/W2954678237","https://openalex.org/W2963134661","https://openalex.org/W2965313220","https://openalex.org/W2981143642","https://openalex.org/W2981562293","https://openalex.org/W2997297215","https://openalex.org/W2997877629","https://openalex.org/W3000004788","https://openalex.org/W3000813620","https://openalex.org/W3033060502","https://openalex.org/W3037166960","https://openalex.org/W3039347953","https://openalex.org/W3094402815","https://openalex.org/W3111679652","https://openalex.org/W3112682751","https://openalex.org/W3136138523","https://openalex.org/W3152626405"],"related_works":["https://openalex.org/W2120405331","https://openalex.org/W2027616686","https://openalex.org/W2980586888","https://openalex.org/W3114722801","https://openalex.org/W2588855097","https://openalex.org/W1991133639","https://openalex.org/W2157134024","https://openalex.org/W2165141499","https://openalex.org/W2811019791","https://openalex.org/W2081933987"],"abstract_inverted_index":{"In":[0,117],"the":[1,5,13,24,30,39,46,54,58,75,91,100,105,111,122,129,137,146,152,189,203],"Kalman":[2],"filter":[3],"(KF),":[4],"estimated":[6],"state":[7],"is":[8,49,66,108,165,176],"a":[9,81,156],"linear":[10],"combination":[11,20],"of":[12,33,74,83],"one-step":[14],"prediction":[15,25],"and":[16,29,57,80,135,154,179,194],"measurement.":[17],"The":[18,87],"two":[19,126],"weights":[21],"depend":[22],"on":[23],"mean-square":[26],"error":[27,196],"matrix":[28,32],"covariances":[31],"measurement":[34,40,48,68,123],"noise":[35,41,76,93,101,124,131,139],"(CMMN),":[36],"respectively.":[37],"When":[38],"values":[42,77],"are":[43,78,85],"small":[44,133],"(large),":[45],"corresponding":[47],"close":[50],"to":[51,95,149,160],"(far":[52],"from)":[53],"real":[55],"value,":[56],"weight":[59],"should":[60],"be":[61,96],"large":[62,141],"(small).":[63],"If":[64],"there":[65,175],"non-Gaussian":[67],"noise,":[69,72],"especially":[70],"heavy-tailed":[71],"most":[73],"small,":[79],"few":[82],"them":[84,162,209],"large.":[86],"occasional":[88],"impulses":[89],"cause":[90],"overall":[92,106],"variance":[94,134],"much":[97,184],"greater":[98],"than":[99,208],"without":[102],"impulses.":[103],"Since":[104],"CMMN":[107],"adopted":[109],"in":[110],"KF,":[112],"its":[113,181],"performance":[114],"will":[115],"deteriorate.":[116],"this":[118],"article,":[119],"we":[120,144],"divide":[121],"into":[125],"parts:":[127],"1)":[128],"background":[130],"with":[132,140,188,210],"2)":[136],"impulse":[138,178],"variance.":[142],"Then,":[143],"use":[145],"expectation\u2013maximization":[147],"algorithm":[148,159],"dynamically":[150,172],"calculate":[151],"parameters":[153],"propose":[155],"new":[157],"KF":[158,168],"process":[161],"separately,":[163],"which":[164],"called":[166],"background-impulse":[167],"(BIKF).":[169],"It":[170],"can":[171],"determine":[173],"whether":[174],"an":[177],"eliminate":[180],"impact":[182],"as":[183,185],"possible.":[186],"Compared":[187],"recent":[190],"maximum":[191],"correntropy":[192],"criterion":[193],"minimum":[195],"entropy":[197],"criterion-based":[198],"KFs,":[199],"simulations":[200],"show":[201],"that":[202],"proposed":[204],"BIKF":[205],"works":[206],"better":[207],"lower":[211],"computational":[212],"complexity.":[213]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":25},{"year":2024,"cited_by_count":23},{"year":2023,"cited_by_count":9},{"year":2022,"cited_by_count":2}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
