{"id":"https://openalex.org/W2972666617","doi":"https://doi.org/10.23919/acc.2019.8815143","title":"A Window-based Tensor Decomposition Approach to Data-Association for Multi Target Tracking","display_name":"A Window-based Tensor Decomposition Approach to Data-Association for Multi Target Tracking","publication_year":2019,"publication_date":"2019-07-01","ids":{"openalex":"https://openalex.org/W2972666617","doi":"https://doi.org/10.23919/acc.2019.8815143","mag":"2972666617"},"language":"en","primary_location":{"id":"doi:10.23919/acc.2019.8815143","is_oa":false,"landing_page_url":"https://doi.org/10.23919/acc.2019.8815143","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 American Control Conference (ACC)","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/A5008100892","display_name":"Sriram Krishnaswamy","orcid":null},"institutions":[{"id":"https://openalex.org/I52357470","display_name":"The Ohio State University","ror":"https://ror.org/00rs6vg23","country_code":"US","type":"education","lineage":["https://openalex.org/I52357470"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Sriram Krishnaswamy","raw_affiliation_strings":["Ohio State University, Columbus, OH, 43210, USA","Department of Mechanical and Aerospace Engineering, Ohio State University, Columbus, OH, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Ohio State University, Columbus, OH, 43210, USA","institution_ids":["https://openalex.org/I52357470"]},{"raw_affiliation_string":"Department of Mechanical and Aerospace Engineering, Ohio State University, Columbus, OH, USA","institution_ids":["https://openalex.org/I52357470"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5073597636","display_name":"Mrinal Kumar","orcid":"https://orcid.org/0000-0001-9747-9449"},"institutions":[{"id":"https://openalex.org/I52357470","display_name":"The Ohio State University","ror":"https://ror.org/00rs6vg23","country_code":"US","type":"education","lineage":["https://openalex.org/I52357470"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Mrinal Kumar","raw_affiliation_strings":["Aerospace University, The Ohio State University, Columbus, OH, 45434, USA","Department of Mechanical, The Ohio State University, Columbus, OH, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Aerospace University, The Ohio State University, Columbus, OH, 45434, USA","institution_ids":["https://openalex.org/I52357470"]},{"raw_affiliation_string":"Department of Mechanical, The Ohio State University, Columbus, OH, USA","institution_ids":["https://openalex.org/I52357470"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.2944,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.4497549,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"5148","last_page":"5153"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12303","display_name":"Tensor decomposition and applications","score":0.9925000071525574,"subfield":{"id":"https://openalex.org/subfields/2605","display_name":"Computational Mathematics"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T12303","display_name":"Tensor decomposition and applications","score":0.9925000071525574,"subfield":{"id":"https://openalex.org/subfields/2605","display_name":"Computational Mathematics"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11447","display_name":"Blind Source Separation Techniques","score":0.9909999966621399,"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"}},{"id":"https://openalex.org/T10711","display_name":"Target Tracking and Data Fusion in Sensor Networks","score":0.989799976348877,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/tensor","display_name":"Tensor (intrinsic definition)","score":0.7104715704917908},{"id":"https://openalex.org/keywords/computational-complexity-theory","display_name":"Computational complexity theory","score":0.6167606711387634},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5870426893234253},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5205129981040955},{"id":"https://openalex.org/keywords/tucker-decomposition","display_name":"Tucker decomposition","score":0.49107909202575684},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.4739035665988922},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.4285348951816559},{"id":"https://openalex.org/keywords/dimensionality-reduction","display_name":"Dimensionality reduction","score":0.41397935152053833},{"id":"https://openalex.org/keywords/tensor-decomposition","display_name":"Tensor decomposition","score":0.3917556405067444},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.316125750541687},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2744501233100891}],"concepts":[{"id":"https://openalex.org/C155281189","wikidata":"https://www.wikidata.org/wiki/Q3518150","display_name":"Tensor (intrinsic definition)","level":2,"score":0.7104715704917908},{"id":"https://openalex.org/C179799912","wikidata":"https://www.wikidata.org/wiki/Q205084","display_name":"Computational complexity theory","level":2,"score":0.6167606711387634},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5870426893234253},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5205129981040955},{"id":"https://openalex.org/C42704193","wikidata":"https://www.wikidata.org/wiki/Q7851097","display_name":"Tucker decomposition","level":4,"score":0.49107909202575684},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.4739035665988922},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.4285348951816559},{"id":"https://openalex.org/C70518039","wikidata":"https://www.wikidata.org/wiki/Q16000077","display_name":"Dimensionality reduction","level":2,"score":0.41397935152053833},{"id":"https://openalex.org/C2986737658","wikidata":"https://www.wikidata.org/wiki/Q30103009","display_name":"Tensor decomposition","level":3,"score":0.3917556405067444},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.316125750541687},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2744501233100891},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.23919/acc.2019.8815143","is_oa":false,"landing_page_url":"https://doi.org/10.23919/acc.2019.8815143","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 American Control Conference (ACC)","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":15,"referenced_works":["https://openalex.org/W34992941","https://openalex.org/W1501075844","https://openalex.org/W1981908713","https://openalex.org/W1993589664","https://openalex.org/W2024165284","https://openalex.org/W2066705949","https://openalex.org/W2090476902","https://openalex.org/W2097009900","https://openalex.org/W2127021804","https://openalex.org/W2151757185","https://openalex.org/W2158726805","https://openalex.org/W2258054274","https://openalex.org/W2782422899","https://openalex.org/W3023058184","https://openalex.org/W4285719527"],"related_works":["https://openalex.org/W2891735857","https://openalex.org/W4214526161","https://openalex.org/W3127610061","https://openalex.org/W47805180","https://openalex.org/W2093953080","https://openalex.org/W2891277085","https://openalex.org/W2347172331","https://openalex.org/W3216281372","https://openalex.org/W4226375746","https://openalex.org/W4281643854"],"abstract_inverted_index":{"Traditional":[0],"observation-to-track":[1],"data":[2,55],"association":[3,56,95],"algorithms,":[4],"such":[5,136],"as":[6],"Bayesian":[7],"methods,":[8],"suffer":[9],"from":[10,88,147,157],"exponential":[11],"growth":[12],"in":[13,18,24,45,54,125,154],"computational":[14,85,130,155],"complexity":[15,53],"with":[16,27],"increase":[17],"a":[19,36,65,108,110,122,174,178],"number":[20,101],"of":[21,43,78,92,102,114,118,177],"targets,":[22],"especially":[23],"dense":[25],"environments":[26],"low":[28],"signal-to-noise":[29],"ratio.":[30],"This":[31,152],"paper":[32],"utilizes":[33],"tensor":[34,80,112,144,160],"decomposition,":[35,134],"commonly":[37],"used":[38],"technique":[39],"to":[40,49,72,82,128,166],"tackle":[41],"\u201ccurse":[42],"dimensionality\u201d":[44],"high":[46],"dimensional":[47],"applications,":[48],"reduce":[50,83,129],"the":[51,76,90,115,158,167],"aforementioned":[52],"problems.":[57],"The":[58,100,142],"Joint":[59],"Probabilistic":[60],"Data":[61],"Association":[62],"(JPDA)":[63],"is":[64,105,145,171],"pseudo-Bayesian":[66],"sub-optimal":[67],"filter":[68],"that":[69],"lends":[70],"itself":[71],"be":[73],"modified":[74],"within":[75],"framework":[77],"incremental":[79],"decomposition":[81],"its":[84],"burden":[86,156],"resulting":[87],"computing":[89],"probabilities":[91],"noncompeting":[93],"join":[94],"events":[96,104],"or":[97],"\u201cfeasible":[98],"events\u201d.":[99],"feasible":[103],"reduced":[106],"by":[107],"using":[109],"\u201ccore\u201d":[111,143],"instead":[113],"complete":[116],"set":[117],"measurements":[119,137],"received":[120],"at":[121],"specified":[123],"instance":[124],"time.":[126],"Furthermore,":[127],"overhead":[131],"while":[132],"performing":[133],"many":[135],"are":[138],"combined":[139],"into":[140],"\u201cbatches\u201d.":[141],"obtained":[146],"Dynamic":[148],"Tensor":[149],"Analysis":[150],"(DTA).":[151],"reduction":[153],"new":[159],"based":[161],"JPDA":[162,169],"method":[163,170],"when":[164],"compared":[165],"traditional":[168],"demonstrated":[172],"via":[173],"numerical":[175],"example":[176],"Space":[179],"Situational":[180],"Awareness":[181],"Problem":[182],"(SSA).":[183]},"counts_by_year":[{"year":2020,"cited_by_count":2}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}