{"id":"https://openalex.org/W1976974773","doi":"https://doi.org/10.1109/lsp.2013.2289975","title":"A Robust Particle Filtering Algorithm With Non-Gaussian Measurement Noise Using Student-t Distribution","display_name":"A Robust Particle Filtering Algorithm With Non-Gaussian Measurement Noise Using Student-t Distribution","publication_year":2013,"publication_date":"2013-11-13","ids":{"openalex":"https://openalex.org/W1976974773","doi":"https://doi.org/10.1109/lsp.2013.2289975","mag":"1976974773"},"language":"en","primary_location":{"id":"doi:10.1109/lsp.2013.2289975","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lsp.2013.2289975","pdf_url":null,"source":{"id":"https://openalex.org/S120629676","display_name":"IEEE Signal Processing Letters","issn_l":"1070-9908","issn":["1070-9908","1558-2361"],"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 Signal Processing Letters","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/A5101522258","display_name":"Dingjie Xu","orcid":"https://orcid.org/0000-0001-7598-0638"},"institutions":[{"id":"https://openalex.org/I151727225","display_name":"Harbin Engineering University","ror":"https://ror.org/03x80pn82","country_code":"CN","type":"education","lineage":["https://openalex.org/I151727225"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dingjie Xu","raw_affiliation_strings":["College of Automation, Harbin Engineering University, Harbin, China","College of automation, Harbin Engineering University, Harbin, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Automation, Harbin Engineering University, Harbin, China","institution_ids":["https://openalex.org/I151727225"]},{"raw_affiliation_string":"College of automation, Harbin Engineering University, Harbin, China","institution_ids":["https://openalex.org/I151727225"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5061738948","display_name":"C. P. Shen","orcid":"https://orcid.org/0009-0001-0386-0108"},"institutions":[{"id":"https://openalex.org/I151727225","display_name":"Harbin Engineering University","ror":"https://ror.org/03x80pn82","country_code":"CN","type":"education","lineage":["https://openalex.org/I151727225"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chen Shen","raw_affiliation_strings":["College of Automation, Harbin Engineering University, Harbin, China","College of automation, Harbin Engineering University, Harbin, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Automation, Harbin Engineering University, Harbin, China","institution_ids":["https://openalex.org/I151727225"]},{"raw_affiliation_string":"College of automation, Harbin Engineering University, Harbin, China","institution_ids":["https://openalex.org/I151727225"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5069987140","display_name":"Feng Shen","orcid":"https://orcid.org/0000-0003-3671-7014"},"institutions":[{"id":"https://openalex.org/I151727225","display_name":"Harbin Engineering University","ror":"https://ror.org/03x80pn82","country_code":"CN","type":"education","lineage":["https://openalex.org/I151727225"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Feng Shen","raw_affiliation_strings":["College of Automation, Harbin Engineering University, Harbin, China","College of automation, Harbin Engineering University, Harbin, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Automation, Harbin Engineering University, Harbin, China","institution_ids":["https://openalex.org/I151727225"]},{"raw_affiliation_string":"College of automation, Harbin Engineering University, Harbin, China","institution_ids":["https://openalex.org/I151727225"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I151727225"],"apc_list":null,"apc_paid":null,"fwci":5.5504,"has_fulltext":false,"cited_by_count":83,"citation_normalized_percentile":{"value":0.952482,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"21","issue":"1","first_page":"30","last_page":"34"},"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":0.9998000264167786,"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":0.9998000264167786,"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/T12814","display_name":"Gaussian Processes and Bayesian Inference","score":0.9962000250816345,"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/T10876","display_name":"Fault Detection and Control Systems","score":0.9933000206947327,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems 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/outlier","display_name":"Outlier","score":0.7529089450836182},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.6899065971374512},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.6829087734222412},{"id":"https://openalex.org/keywords/gaussian-noise","display_name":"Gaussian noise","score":0.6538840532302856},{"id":"https://openalex.org/keywords/particle-filter","display_name":"Particle filter","score":0.6275714635848999},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.6181568503379822},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.5860787034034729},{"id":"https://openalex.org/keywords/students-t-distribution","display_name":"Student's t-distribution","score":0.5334406495094299},{"id":"https://openalex.org/keywords/noise-measurement","display_name":"Noise measurement","score":0.5244170427322388},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5049088597297668},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.4276476502418518},{"id":"https://openalex.org/keywords/kalman-filter","display_name":"Kalman filter","score":0.34802794456481934},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3323233127593994},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3303142189979553},{"id":"https://openalex.org/keywords/noise-reduction","display_name":"Noise reduction","score":0.15159308910369873}],"concepts":[{"id":"https://openalex.org/C79337645","wikidata":"https://www.wikidata.org/wiki/Q779824","display_name":"Outlier","level":2,"score":0.7529089450836182},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.6899065971374512},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.6829087734222412},{"id":"https://openalex.org/C4199805","wikidata":"https://www.wikidata.org/wiki/Q2725903","display_name":"Gaussian noise","level":2,"score":0.6538840532302856},{"id":"https://openalex.org/C52421305","wikidata":"https://www.wikidata.org/wiki/Q1151499","display_name":"Particle filter","level":3,"score":0.6275714635848999},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.6181568503379822},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.5860787034034729},{"id":"https://openalex.org/C49232408","wikidata":"https://www.wikidata.org/wiki/Q576072","display_name":"Student's t-distribution","level":4,"score":0.5334406495094299},{"id":"https://openalex.org/C29265498","wikidata":"https://www.wikidata.org/wiki/Q7047719","display_name":"Noise measurement","level":3,"score":0.5244170427322388},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5049088597297668},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.4276476502418518},{"id":"https://openalex.org/C157286648","wikidata":"https://www.wikidata.org/wiki/Q846780","display_name":"Kalman filter","level":2,"score":0.34802794456481934},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3323233127593994},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3303142189979553},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.15159308910369873},{"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/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C23922673","wikidata":"https://www.wikidata.org/wiki/Q180752","display_name":"Autoregressive conditional heteroskedasticity","level":3,"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/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C91602232","wikidata":"https://www.wikidata.org/wiki/Q756115","display_name":"Volatility (finance)","level":2,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/lsp.2013.2289975","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lsp.2013.2289975","pdf_url":null,"source":{"id":"https://openalex.org/S120629676","display_name":"IEEE Signal Processing Letters","issn_l":"1070-9908","issn":["1070-9908","1558-2361"],"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 Signal Processing Letters","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6299999952316284,"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":16,"referenced_works":["https://openalex.org/W1516111018","https://openalex.org/W1531532259","https://openalex.org/W1965943163","https://openalex.org/W2042688433","https://openalex.org/W2050114157","https://openalex.org/W2079732597","https://openalex.org/W2095376999","https://openalex.org/W2096678341","https://openalex.org/W2115979064","https://openalex.org/W2117723483","https://openalex.org/W2146065452","https://openalex.org/W2148061324","https://openalex.org/W2148613679","https://openalex.org/W2167823677","https://openalex.org/W2172085063","https://openalex.org/W4211128380"],"related_works":["https://openalex.org/W2986378528","https://openalex.org/W3178345791","https://openalex.org/W2092661960","https://openalex.org/W1550854977","https://openalex.org/W2949211747","https://openalex.org/W3005742472","https://openalex.org/W2588855097","https://openalex.org/W2162441712","https://openalex.org/W2161234930","https://openalex.org/W2057263719"],"abstract_inverted_index":{"The":[0,104],"Gaussian":[1],"noise":[2,31,67,82],"assumption":[3],"may":[4],"result":[5],"in":[6,10,71],"a":[7,43,48,110],"major":[8],"decline":[9],"state":[11],"estimation":[12],"accuracy":[13],"when":[14],"the":[15,19,28,33,38,65,75,80,115],"measurements":[16],"are":[17,86],"with":[18,32,109],"presence":[20],"of":[21,42,117],"outliers.":[22],"In":[23],"this":[24],"letter,":[25],"we":[26,56],"endow":[27],"unknown":[29,66,81],"measurement":[30],"Student-t":[34],"distribution":[35],"to":[36,62,73,89,93],"model":[37,113],"underlying":[39],"non-Gaussian":[40],"dynamics":[41],"real":[44],"physical":[45],"system.":[46],"Thereafter":[47],"robust":[49],"particle":[50,92],"filtering":[51],"algorithm":[52,106,119],"is":[53,107],"developed.":[54],"First,":[55],"employ":[57],"variational":[58],"Bayesian":[59],"(VB)":[60],"approach":[61],"robustly":[63],"infer":[64],"parameters":[68,85],"recursively.":[69],"Second,":[70],"order":[72],"decrease":[74],"computational":[76],"complexity":[77],"resulted":[78],"by":[79,96,101],"parameters,":[83],"those":[84],"marginalized":[87],"out":[88],"allow":[90],"each":[91],"be":[94],"updated":[95],"using":[97],"sufficient":[98],"statistics":[99],"estimated":[100],"VB":[102],"approach.":[103],"proposed":[105],"tested":[108],"typical":[111],"non-linear":[112],"and":[114],"robustness":[116],"our":[118],"has":[120],"been":[121],"borne":[122],"out.":[123]},"counts_by_year":[{"year":2026,"cited_by_count":4},{"year":2025,"cited_by_count":6},{"year":2024,"cited_by_count":8},{"year":2023,"cited_by_count":5},{"year":2022,"cited_by_count":6},{"year":2021,"cited_by_count":9},{"year":2020,"cited_by_count":12},{"year":2019,"cited_by_count":10},{"year":2018,"cited_by_count":10},{"year":2017,"cited_by_count":3},{"year":2016,"cited_by_count":5},{"year":2015,"cited_by_count":4},{"year":2014,"cited_by_count":1}],"updated_date":"2026-08-01T09:00:35.917206","created_date":"2025-10-10T00:00:00"}
