{"id":"https://openalex.org/W2133669808","doi":"https://doi.org/10.1109/icsmc.2009.5346071","title":"A new approach based on particle filter for target tracking with glint noise","display_name":"A new approach based on particle filter for target tracking with glint noise","publication_year":2009,"publication_date":"2009-10-01","ids":{"openalex":"https://openalex.org/W2133669808","doi":"https://doi.org/10.1109/icsmc.2009.5346071","mag":"2133669808"},"language":"en","primary_location":{"id":"doi:10.1109/icsmc.2009.5346071","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icsmc.2009.5346071","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2009 IEEE International Conference on Systems, Man and Cybernetics","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/A5035937202","display_name":"Jungen Zhang","orcid":null},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Jungen Zhang","raw_affiliation_strings":["School of Electronic Engineering, Xidian University, Xi'an, China","School of Electronic Engineering, Xidian University, Xi\u2019an, China"],"affiliations":[{"raw_affiliation_string":"School of Electronic Engineering, Xidian University, Xi'an, China","institution_ids":["https://openalex.org/I149594827"]},{"raw_affiliation_string":"School of Electronic Engineering, Xidian University, Xi\u2019an, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102805077","display_name":"Hongbing Ji","orcid":"https://orcid.org/0000-0002-6775-518X"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hongbing Ji","raw_affiliation_strings":["School of Electronic Engineering, Xidian University, Xi'an, China","School of Electronic Engineering, Xidian University, Xi\u2019an, China"],"affiliations":[{"raw_affiliation_string":"School of Electronic Engineering, Xidian University, Xi'an, China","institution_ids":["https://openalex.org/I149594827"]},{"raw_affiliation_string":"School of Electronic Engineering, Xidian University, Xi\u2019an, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100558022","display_name":"Qi-Kun Xue","orcid":"https://orcid.org/0000-0002-4129-1284"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qikun Xue","raw_affiliation_strings":["School of Electronic Engineering, Xidian University, Xi'an, China","School of Electronic Engineering, Xidian University, Xi\u2019an, China"],"affiliations":[{"raw_affiliation_string":"School of Electronic Engineering, Xidian University, Xi'an, China","institution_ids":["https://openalex.org/I149594827"]},{"raw_affiliation_string":"School of Electronic Engineering, Xidian University, Xi\u2019an, China","institution_ids":["https://openalex.org/I149594827"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5035937202"],"corresponding_institution_ids":["https://openalex.org/I149594827"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.13010749,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"4791","last_page":"4795"},"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":0.9998999834060669,"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":0.9998999834060669,"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/T11901","display_name":"Bayesian Methods and Mixture Models","score":0.9848999977111816,"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/T11698","display_name":"Underwater Acoustics Research","score":0.983299970626831,"subfield":{"id":"https://openalex.org/subfields/1910","display_name":"Oceanography"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/particle-filter","display_name":"Particle filter","score":0.7813706994056702},{"id":"https://openalex.org/keywords/markov-chain-monte-carlo","display_name":"Markov chain Monte Carlo","score":0.7328025102615356},{"id":"https://openalex.org/keywords/tracking","display_name":"Tracking (education)","score":0.6084933876991272},{"id":"https://openalex.org/keywords/auxiliary-particle-filter","display_name":"Auxiliary particle filter","score":0.6015046238899231},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5146063566207886},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.4940245747566223},{"id":"https://openalex.org/keywords/radar-tracker","display_name":"Radar tracker","score":0.47433584928512573},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.45191413164138794},{"id":"https://openalex.org/keywords/kalman-filter","display_name":"Kalman filter","score":0.42363592982292175},{"id":"https://openalex.org/keywords/monte-carlo-method","display_name":"Monte Carlo method","score":0.41590166091918945},{"id":"https://openalex.org/keywords/extended-kalman-filter","display_name":"Extended Kalman filter","score":0.3656599521636963},{"id":"https://openalex.org/keywords/ensemble-kalman-filter","display_name":"Ensemble Kalman filter","score":0.364940881729126},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.32135725021362305},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.28039348125457764},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.27168983221054077},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.261801540851593},{"id":"https://openalex.org/keywords/radar","display_name":"Radar","score":0.22450080513954163},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.1369805932044983},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.1185799241065979},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.08921879529953003}],"concepts":[{"id":"https://openalex.org/C52421305","wikidata":"https://www.wikidata.org/wiki/Q1151499","display_name":"Particle filter","level":3,"score":0.7813706994056702},{"id":"https://openalex.org/C111350023","wikidata":"https://www.wikidata.org/wiki/Q1191869","display_name":"Markov chain Monte Carlo","level":3,"score":0.7328025102615356},{"id":"https://openalex.org/C2775936607","wikidata":"https://www.wikidata.org/wiki/Q466845","display_name":"Tracking (education)","level":2,"score":0.6084933876991272},{"id":"https://openalex.org/C52483021","wikidata":"https://www.wikidata.org/wiki/Q4827310","display_name":"Auxiliary particle filter","level":5,"score":0.6015046238899231},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5146063566207886},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.4940245747566223},{"id":"https://openalex.org/C32283439","wikidata":"https://www.wikidata.org/wiki/Q1407014","display_name":"Radar tracker","level":3,"score":0.47433584928512573},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.45191413164138794},{"id":"https://openalex.org/C157286648","wikidata":"https://www.wikidata.org/wiki/Q846780","display_name":"Kalman filter","level":2,"score":0.42363592982292175},{"id":"https://openalex.org/C19499675","wikidata":"https://www.wikidata.org/wiki/Q232207","display_name":"Monte Carlo method","level":2,"score":0.41590166091918945},{"id":"https://openalex.org/C206833254","wikidata":"https://www.wikidata.org/wiki/Q5421817","display_name":"Extended Kalman filter","level":3,"score":0.3656599521636963},{"id":"https://openalex.org/C79334102","wikidata":"https://www.wikidata.org/wiki/Q3072268","display_name":"Ensemble Kalman filter","level":4,"score":0.364940881729126},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.32135725021362305},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.28039348125457764},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.27168983221054077},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.261801540851593},{"id":"https://openalex.org/C554190296","wikidata":"https://www.wikidata.org/wiki/Q47528","display_name":"Radar","level":2,"score":0.22450080513954163},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.1369805932044983},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.1185799241065979},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.08921879529953003},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.0},{"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/C19417346","wikidata":"https://www.wikidata.org/wiki/Q7922","display_name":"Pedagogy","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icsmc.2009.5346071","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icsmc.2009.5346071","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2009 IEEE International Conference on Systems, Man and Cybernetics","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":25,"referenced_works":["https://openalex.org/W1483307070","https://openalex.org/W1982255168","https://openalex.org/W1996706444","https://openalex.org/W1998752816","https://openalex.org/W2004535457","https://openalex.org/W2016456873","https://openalex.org/W2020934227","https://openalex.org/W2055936398","https://openalex.org/W2064480843","https://openalex.org/W2077611006","https://openalex.org/W2082542916","https://openalex.org/W2103632679","https://openalex.org/W2113926057","https://openalex.org/W2124156864","https://openalex.org/W2126736494","https://openalex.org/W2128909582","https://openalex.org/W2133231560","https://openalex.org/W2146065452","https://openalex.org/W2160337655","https://openalex.org/W2171618211","https://openalex.org/W2203563723","https://openalex.org/W4285719527","https://openalex.org/W6650113563","https://openalex.org/W6655473528","https://openalex.org/W6675379618"],"related_works":["https://openalex.org/W2126907425","https://openalex.org/W2368144031","https://openalex.org/W3144709167","https://openalex.org/W2114656557","https://openalex.org/W2355962871","https://openalex.org/W1497303808","https://openalex.org/W2075503097","https://openalex.org/W2514372983","https://openalex.org/W2208639223","https://openalex.org/W2195963939"],"abstract_inverted_index":{"In":[0],"radar":[1],"target":[2],"tracking":[3,52,85],"application,":[4],"the":[5,27,55,62,67,81],"observation":[6],"noise":[7],"is":[8,12,46,57,78],"usually":[9],"non-Gaussian,":[10],"which":[11],"also":[13],"referred":[14],"to":[15,48,61],"as":[16],"glint":[17,30],"noise.":[18,31],"The":[19,51],"performances":[20],"of":[21,29,54],"conventional":[22],"trackers":[23],"degrade":[24],"severely":[25],"in":[26],"presence":[28],"An":[32],"improved":[33],"particle":[34,43,63,72],"filter,":[35],"Markov":[36,68],"chain":[37,69],"Monte":[38,70],"Carlo":[39,71],"iterated":[40],"extended":[41],"Kalman":[42],"filter":[44,56,64,73],"(MCMC-IEKPF),":[45],"applied":[47],"this":[49],"problem.":[50],"performance":[53],"evaluated":[58],"and":[59,66],"compared":[60],"(PF)":[65],"(MCMC-PF)":[74],"via":[75],"simulations.":[76],"It":[77],"shown":[79],"that":[80],"MCMC-IEKPF":[82],"has":[83],"better":[84],"performance.":[86]},"counts_by_year":[{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"year":2017,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
