{"id":"https://openalex.org/W2608484395","doi":"https://doi.org/10.1109/icpr.2016.7900250","title":"MLPF algorithm for tracking fast moving target against light interference","display_name":"MLPF algorithm for tracking fast moving target against light interference","publication_year":2016,"publication_date":"2016-12-01","ids":{"openalex":"https://openalex.org/W2608484395","doi":"https://doi.org/10.1109/icpr.2016.7900250","mag":"2608484395"},"language":"en","primary_location":{"id":"doi:10.1109/icpr.2016.7900250","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpr.2016.7900250","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 23rd International Conference on Pattern Recognition (ICPR)","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/A5100337161","display_name":"Libo Zhang","orcid":"https://orcid.org/0000-0001-8450-0958"},"institutions":[{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Libo Zhang","raw_affiliation_strings":["University of Chinese Academy of Sciences, Beijing, China"],"affiliations":[{"raw_affiliation_string":"University of Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210165038"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100760616","display_name":"Yuanqiang Cai","orcid":"https://orcid.org/0000-0001-8041-012X"},"institutions":[{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuanqiang Cai","raw_affiliation_strings":["University of Chinese Academy of Sciences, Beijing, China"],"affiliations":[{"raw_affiliation_string":"University of Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210165038"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5042577447","display_name":"Zakir Ullah","orcid":"https://orcid.org/0000-0001-8921-6550"},"institutions":[{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zakir Ullah","raw_affiliation_strings":["University of Chinese Academy of Sciences, Beijing, China"],"affiliations":[{"raw_affiliation_string":"University of Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210165038"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5108534872","display_name":"Tiejian Luo","orcid":null},"institutions":[{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tiejian Luo","raw_affiliation_strings":["University of Chinese Academy of Sciences, Beijing, China"],"affiliations":[{"raw_affiliation_string":"University of Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210165038"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5100337161"],"corresponding_institution_ids":["https://openalex.org/I4210165038"],"apc_list":null,"apc_paid":null,"fwci":0.334,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.69454747,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"3939","last_page":"3944"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9995999932289124,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9995999932289124,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T12597","display_name":"Fire Detection and Safety Systems","score":0.9868000149726868,"subfield":{"id":"https://openalex.org/subfields/2213","display_name":"Safety, Risk, Reliability and Quality"},"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/T10689","display_name":"Remote-Sensing Image Classification","score":0.9857000112533569,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"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/resampling","display_name":"Resampling","score":0.7483065128326416},{"id":"https://openalex.org/keywords/tracking","display_name":"Tracking (education)","score":0.7420509457588196},{"id":"https://openalex.org/keywords/particle-filter","display_name":"Particle filter","score":0.6947002410888672},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.6643336415290833},{"id":"https://openalex.org/keywords/interference","display_name":"Interference (communication)","score":0.60249263048172},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.5883861780166626},{"id":"https://openalex.org/keywords/particle","display_name":"Particle (ecology)","score":0.5799318552017212},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5538620948791504},{"id":"https://openalex.org/keywords/particle-number","display_name":"Particle number","score":0.478975772857666},{"id":"https://openalex.org/keywords/auxiliary-particle-filter","display_name":"Auxiliary particle filter","score":0.42864301800727844},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.3310515284538269},{"id":"https://openalex.org/keywords/kalman-filter","display_name":"Kalman filter","score":0.2953373193740845},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.273165225982666},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.2695390582084656},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.2663998007774353},{"id":"https://openalex.org/keywords/extended-kalman-filter","display_name":"Extended Kalman filter","score":0.11093267798423767},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.07187953591346741}],"concepts":[{"id":"https://openalex.org/C150921843","wikidata":"https://www.wikidata.org/wiki/Q1170431","display_name":"Resampling","level":2,"score":0.7483065128326416},{"id":"https://openalex.org/C2775936607","wikidata":"https://www.wikidata.org/wiki/Q466845","display_name":"Tracking (education)","level":2,"score":0.7420509457588196},{"id":"https://openalex.org/C52421305","wikidata":"https://www.wikidata.org/wiki/Q1151499","display_name":"Particle filter","level":3,"score":0.6947002410888672},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.6643336415290833},{"id":"https://openalex.org/C32022120","wikidata":"https://www.wikidata.org/wiki/Q797225","display_name":"Interference (communication)","level":3,"score":0.60249263048172},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.5883861780166626},{"id":"https://openalex.org/C2778517922","wikidata":"https://www.wikidata.org/wiki/Q7140482","display_name":"Particle (ecology)","level":2,"score":0.5799318552017212},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5538620948791504},{"id":"https://openalex.org/C74412414","wikidata":"https://www.wikidata.org/wiki/Q181155","display_name":"Particle number","level":3,"score":0.478975772857666},{"id":"https://openalex.org/C52483021","wikidata":"https://www.wikidata.org/wiki/Q4827310","display_name":"Auxiliary particle filter","level":5,"score":0.42864301800727844},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.3310515284538269},{"id":"https://openalex.org/C157286648","wikidata":"https://www.wikidata.org/wiki/Q846780","display_name":"Kalman filter","level":2,"score":0.2953373193740845},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.273165225982666},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.2695390582084656},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.2663998007774353},{"id":"https://openalex.org/C206833254","wikidata":"https://www.wikidata.org/wiki/Q5421817","display_name":"Extended Kalman filter","level":3,"score":0.11093267798423767},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.07187953591346741},{"id":"https://openalex.org/C111368507","wikidata":"https://www.wikidata.org/wiki/Q43518","display_name":"Oceanography","level":1,"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/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.0},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.0},{"id":"https://openalex.org/C82706917","wikidata":"https://www.wikidata.org/wiki/Q10251","display_name":"Plasma","level":2,"score":0.0},{"id":"https://openalex.org/C79334102","wikidata":"https://www.wikidata.org/wiki/Q3072268","display_name":"Ensemble Kalman filter","level":4,"score":0.0},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"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/icpr.2016.7900250","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpr.2016.7900250","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 23rd International Conference on Pattern Recognition (ICPR)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":13,"referenced_works":["https://openalex.org/W818325216","https://openalex.org/W1964846093","https://openalex.org/W1995903777","https://openalex.org/W2016075127","https://openalex.org/W2026393195","https://openalex.org/W2040749143","https://openalex.org/W2098941887","https://openalex.org/W2105728775","https://openalex.org/W2160337655","https://openalex.org/W2165037244","https://openalex.org/W2277305587","https://openalex.org/W6623108133","https://openalex.org/W6684332838"],"related_works":["https://openalex.org/W3144709167","https://openalex.org/W1973225318","https://openalex.org/W2368144031","https://openalex.org/W2162253570","https://openalex.org/W2355962871","https://openalex.org/W1824810860","https://openalex.org/W2126226614","https://openalex.org/W2758742130","https://openalex.org/W2862160893","https://openalex.org/W2376126247"],"abstract_inverted_index":{"In":[0,29,51,152],"order":[1],"to":[2,135,164,172,187,194],"deal":[3],"with":[4,14],"the":[5,9,31,38,42,47,52,64,74,84,90,100,104,108,112,136,142,153,156,167,176,179],"difficulty":[6],"of":[7,54,86,107,114,119],"tracking":[8,22,132],"fast":[10,146],"moving":[11,145],"aerial":[12],"targets":[13],"light":[15,150],"interference,":[16],"we":[17],"propose":[18],"an":[19],"improved":[20],"particle":[21,26,138],"algorithm":[23,82,122],"named":[24],"multi-layers":[25],"filter":[27,139],"(MLPF).":[28],"MLPF,":[30],"particles":[32,40,44,49,87],"are":[33,61,66],"divided":[34],"into":[35],"three":[36],"categories:":[37],"main":[39],"(M-particles),":[41],"subordinate":[43],"(S-particles)":[45],"and":[46,56,68,88,110,147],"regenerate":[48],"(R-particles).":[50],"phase":[53],"resampling":[55],"state":[57],"estimating,":[58],"only":[59],"M-particles":[60],"involved,":[62],"then":[63],"R-particles":[65],"generated":[67],"considered":[69],"as":[70],"new":[71],"S-particles":[72],"in":[73],"next":[75],"cycle.":[76],"To":[77],"a":[78],"certain":[79],"extent,":[80],"our":[81,120],"maintains":[83],"diversity":[85],"reduces":[89],"computation":[91],"time.":[92],"Besides,":[93],"MLPF":[94,129],"has":[95,130,159,182],"significant":[96],"improvements":[97],"on":[98],"overcoming":[99],"tracing":[101],"error":[102],"after":[103],"sudden":[105],"disappearance":[106],"target":[109,143],"solving":[111],"degradation":[113],"particles.":[115],"We":[116],"demonstrate":[117],"effectiveness":[118],"proposed":[121],"through":[123],"systematic":[124],"experiments.":[125],"Experimental":[126],"results":[127],"show":[128],"better":[131],"effect":[133],"compared":[134],"traditional":[137],"(PF)":[140],"when":[141],"is":[144],"affected":[148],"by":[149],"interference.":[151],"first":[154],"experiment,":[155,178],"running":[157,180],"time":[158,181],"been":[160,183],"reduced":[161,184],"from":[162,170,185,192],"47s":[163],"21s":[165],"while":[166,189],"precision":[168,190],"increased":[169,191],"64%":[171],"96%.":[173],"And":[174],"for":[175],"second":[177],"237s":[186],"121s":[188],"46%":[193],"89%.":[195]},"counts_by_year":[{"year":2018,"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"}