{"id":"https://openalex.org/W7133309303","doi":"https://doi.org/10.1109/taes.2026.3669886","title":"RCS Information-Aided Distributed Multisensor LMB Filtering Algorithm","display_name":"RCS Information-Aided Distributed Multisensor LMB Filtering Algorithm","publication_year":2026,"publication_date":"2026-01-01","ids":{"openalex":"https://openalex.org/W7133309303","doi":"https://doi.org/10.1109/taes.2026.3669886"},"language":null,"primary_location":{"id":"doi:10.1109/taes.2026.3669886","is_oa":false,"landing_page_url":"https://doi.org/10.1109/taes.2026.3669886","pdf_url":null,"source":{"id":"https://openalex.org/S193624734","display_name":"IEEE Transactions on Aerospace and Electronic Systems","issn_l":"0018-9251","issn":["0018-9251","1557-9603","2371-9877"],"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 Aerospace and Electronic 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/A5019918285","display_name":"Kuiwu Wang","orcid":"https://orcid.org/0000-0002-8847-2672"},"institutions":[{"id":"https://openalex.org/I4210104252","display_name":"Air Force Engineering University","ror":"https://ror.org/00seraz22","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210104252"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wang Kuiwu","raw_affiliation_strings":["Air Force Engineering University, Xi'an, China"],"raw_orcid":"https://orcid.org/0000-0002-8847-2672","affiliations":[{"raw_affiliation_string":"Air Force Engineering University, Xi'an, China","institution_ids":["https://openalex.org/I4210104252"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5127920214","display_name":"Zhang Qin","orcid":null},"institutions":[{"id":"https://openalex.org/I4210104252","display_name":"Air Force Engineering University","ror":"https://ror.org/00seraz22","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210104252"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhang Qin","raw_affiliation_strings":["Air Force Engineering University, Xi'an, China"],"raw_orcid":"https://orcid.org/0000-0001-6672-320X","affiliations":[{"raw_affiliation_string":"Air Force Engineering University, Xi'an, China","institution_ids":["https://openalex.org/I4210104252"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5127913117","display_name":"Jin Zhenlu","orcid":null},"institutions":[{"id":"https://openalex.org/I4210104252","display_name":"Air Force Engineering University","ror":"https://ror.org/00seraz22","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210104252"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jin Zhenlu","raw_affiliation_strings":["Air Force Engineering University, Xi'an, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Air Force Engineering University, Xi'an, China","institution_ids":["https://openalex.org/I4210104252"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100948894","display_name":"Wan Pengfei","orcid":null},"institutions":[{"id":"https://openalex.org/I4210104252","display_name":"Air Force Engineering University","ror":"https://ror.org/00seraz22","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210104252"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wan Pengfei","raw_affiliation_strings":["Air Force Engineering University, Xi'an, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Air Force Engineering University, Xi'an, China","institution_ids":["https://openalex.org/I4210104252"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5128019065","display_name":"Hu Xiaolong","orcid":null},"institutions":[{"id":"https://openalex.org/I4210104252","display_name":"Air Force Engineering University","ror":"https://ror.org/00seraz22","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210104252"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hu Xiaolong","raw_affiliation_strings":["Air Force Engineering University, Xi'an, China"],"raw_orcid":"https://orcid.org/0000-0003-2173-9229","affiliations":[{"raw_affiliation_string":"Air Force Engineering University, Xi'an, China","institution_ids":["https://openalex.org/I4210104252"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I4210104252"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.26687177,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"62","issue":null,"first_page":"6939","last_page":"6956"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11233","display_name":"Advanced Adaptive Filtering Techniques","score":0.2418999969959259,"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"}},"topics":[{"id":"https://openalex.org/T11233","display_name":"Advanced Adaptive Filtering Techniques","score":0.2418999969959259,"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/T10711","display_name":"Target Tracking and Data Fusion in Sensor Networks","score":0.1527000069618225,"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/T10931","display_name":"Direction-of-Arrival Estimation Techniques","score":0.08869999647140503,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/clutter","display_name":"Clutter","score":0.7052000164985657},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.6521999835968018},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.5145000219345093},{"id":"https://openalex.org/keywords/autoregressive-model","display_name":"Autoregressive model","score":0.49079999327659607},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.4837000072002411},{"id":"https://openalex.org/keywords/radar-tracker","display_name":"Radar tracker","score":0.4765999913215637},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.45339998602867126},{"id":"https://openalex.org/keywords/tracking","display_name":"Tracking (education)","score":0.3986000120639801},{"id":"https://openalex.org/keywords/sensor-fusion","display_name":"Sensor fusion","score":0.38749998807907104},{"id":"https://openalex.org/keywords/prior-information","display_name":"Prior information","score":0.3564000129699707}],"concepts":[{"id":"https://openalex.org/C132094186","wikidata":"https://www.wikidata.org/wiki/Q641585","display_name":"Clutter","level":3,"score":0.7052000164985657},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.682200014591217},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.6521999835968018},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.603600025177002},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.5145000219345093},{"id":"https://openalex.org/C159877910","wikidata":"https://www.wikidata.org/wiki/Q2202883","display_name":"Autoregressive model","level":2,"score":0.49079999327659607},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.4837000072002411},{"id":"https://openalex.org/C32283439","wikidata":"https://www.wikidata.org/wiki/Q1407014","display_name":"Radar tracker","level":3,"score":0.4765999913215637},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.45339998602867126},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.41999998688697815},{"id":"https://openalex.org/C2775936607","wikidata":"https://www.wikidata.org/wiki/Q466845","display_name":"Tracking (education)","level":2,"score":0.3986000120639801},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.38749998807907104},{"id":"https://openalex.org/C3020402766","wikidata":"https://www.wikidata.org/wiki/Q104376712","display_name":"Prior information","level":2,"score":0.3564000129699707},{"id":"https://openalex.org/C106516650","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm design","level":2,"score":0.3481999933719635},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.329800009727478},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.32739999890327454},{"id":"https://openalex.org/C2983325608","wikidata":"https://www.wikidata.org/wiki/Q17084606","display_name":"Data association","level":3,"score":0.3125},{"id":"https://openalex.org/C178674793","wikidata":"https://www.wikidata.org/wiki/Q6031077","display_name":"Information filtering system","level":2,"score":0.30140000581741333},{"id":"https://openalex.org/C157286648","wikidata":"https://www.wikidata.org/wiki/Q846780","display_name":"Kalman filter","level":2,"score":0.29660001397132874},{"id":"https://openalex.org/C158525013","wikidata":"https://www.wikidata.org/wiki/Q2593739","display_name":"Fusion","level":2,"score":0.2930000126361847},{"id":"https://openalex.org/C52421305","wikidata":"https://www.wikidata.org/wiki/Q1151499","display_name":"Particle filter","level":3,"score":0.29170000553131104},{"id":"https://openalex.org/C117623542","wikidata":"https://www.wikidata.org/wiki/Q621974","display_name":"Automatic target recognition","level":3,"score":0.28940001130104065},{"id":"https://openalex.org/C8272713","wikidata":"https://www.wikidata.org/wiki/Q176737","display_name":"Stochastic process","level":2,"score":0.2856000065803528},{"id":"https://openalex.org/C554190296","wikidata":"https://www.wikidata.org/wiki/Q47528","display_name":"Radar","level":2,"score":0.2824000120162964},{"id":"https://openalex.org/C148764684","wikidata":"https://www.wikidata.org/wiki/Q621751","display_name":"Approximation algorithm","level":2,"score":0.28200000524520874},{"id":"https://openalex.org/C2982962833","wikidata":"https://www.wikidata.org/wiki/Q17092450","display_name":"Information fusion","level":2,"score":0.2809999883174896},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.27549999952316284},{"id":"https://openalex.org/C104267543","wikidata":"https://www.wikidata.org/wiki/Q208163","display_name":"Signal processing","level":3,"score":0.2743000090122223},{"id":"https://openalex.org/C61455927","wikidata":"https://www.wikidata.org/wiki/Q1030529","display_name":"Blossom algorithm","level":3,"score":0.27149999141693115},{"id":"https://openalex.org/C179799912","wikidata":"https://www.wikidata.org/wiki/Q205084","display_name":"Computational complexity theory","level":2,"score":0.2653999924659729},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.26429998874664307},{"id":"https://openalex.org/C160234255","wikidata":"https://www.wikidata.org/wiki/Q812535","display_name":"Bayesian inference","level":3,"score":0.2639999985694885},{"id":"https://openalex.org/C70437156","wikidata":"https://www.wikidata.org/wiki/Q7228652","display_name":"Pooling","level":2,"score":0.2612999975681305},{"id":"https://openalex.org/C29265498","wikidata":"https://www.wikidata.org/wiki/Q7047719","display_name":"Noise measurement","level":3,"score":0.26010000705718994}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/taes.2026.3669886","is_oa":false,"landing_page_url":"https://doi.org/10.1109/taes.2026.3669886","pdf_url":null,"source":{"id":"https://openalex.org/S193624734","display_name":"IEEE Transactions on Aerospace and Electronic Systems","issn_l":"0018-9251","issn":["0018-9251","1557-9603","2371-9877"],"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 Aerospace and Electronic Systems","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Affordable and clean energy","score":0.41784876585006714,"id":"https://metadata.un.org/sdg/7"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"In":[0],"complex":[1],"electromagnetic":[2],"environments,":[3],"existing":[4],"multi-target":[5],"tracking":[6,141],"algorithms":[7],"often":[8],"suffer":[9],"from":[10],"performance":[11],"degradation.":[12],"To":[13],"address":[14],"this":[15,17,108],"challenge,":[16],"paper":[18],"proposes":[19],"a":[20,38,112],"Distributed":[21],"Multi-Sensor":[22],"LMB":[23],"algorithm":[24,31],"based":[25,106],"on":[26,107],"RCS":[27,34,46,74,95],"information":[28,35,59,75,96],"assistance.":[29],"The":[30],"models":[32],"target":[33,67],"parameters":[36,76],"using":[37],"non-stationary":[39],"autoregressive":[40],"Gamma":[41],"process":[42,90,131],"to":[43,77,97,122],"achieve":[44,123],"Bayesian":[45],"estimation.":[47],"This":[48,89,129],"method":[49,150],"comprises":[50],"two":[51],"main":[52],"steps:":[53],"single-node":[54],"local":[55,63],"filtering":[56,64],"and":[57,86,103,117,154,160],"multi-node":[58],"fusion.":[60],"During":[61],"the":[62,66,79,93,99,148],"phase,":[65],"state":[68],"is":[69],"first":[70],"extended":[71],"by":[72],"introducing":[73],"establish":[78,111],"likelihood":[80],"function,":[81],"thereby":[82,138],"deriving":[83],"updated":[84],"prediction":[85],"update":[87],"equations.":[88],"fully":[91],"utilizes":[92],"target's":[94],"enhance":[98],"distinction":[100],"between":[101],"targets":[102],"clutter.":[104],"Subsequently,":[105],"information,":[109],"we":[110],"label":[113,119,124],"matching":[114,125,130],"quality":[115],"model":[116],"combine":[118],"historical":[120],"data":[121],"among":[126],"multiple":[127],"nodes.":[128],"enables":[132],"effective":[133],"fusion":[134],"of":[135],"multi-sensor":[136],"data,":[137],"improving":[139],"overall":[140],"accuracy.":[142],"Simulation":[143],"experiment":[144],"results":[145],"demonstrate":[146],"that":[147],"proposed":[149],"exhibits":[151],"strong":[152],"effectiveness":[153],"robustness":[155],"in":[156],"dense":[157],"clutter":[158],"environments":[159],"under":[161],"low":[162],"detection":[163],"probability":[164],"conditions.":[165]},"counts_by_year":[],"updated_date":"2026-04-17T05:58:53.018234","created_date":"2026-03-04T00:00:00"}