{"id":"https://openalex.org/W1591669475","doi":"https://doi.org/10.1117/12.2181907","title":"Knowledge-aided GMTI in a Bayesian framework","display_name":"Knowledge-aided GMTI in a Bayesian framework","publication_year":2015,"publication_date":"2015-05-13","ids":{"openalex":"https://openalex.org/W1591669475","doi":"https://doi.org/10.1117/12.2181907","mag":"1591669475"},"language":"en","primary_location":{"id":"doi:10.1117/12.2181907","doi":"https://doi.org/10.1117/12.2181907","is_oa":false,"landing_page_url":"https://doi.org/10.1117/12.2181907","pdf_url":null,"source":{"id":"https://openalex.org/S183492911","display_name":"Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE","issn_l":"0277-786X","issn":["0277-786X","1996-756X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["cwts-core","norway-1"],"host_organization":"https://openalex.org/P4310315543","host_organization_name":"SPIE","host_organization_lineage":["https://openalex.org/P4310315543"],"host_organization_lineage_names":["SPIE"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"SPIE Proceedings","raw_type":"proceedings-article"},"volume":null,"type":"conference-paper","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":null,"display_name":"Michael Riedl","orcid":null,"observed_orcids":[]},"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":"Michael Riedl","raw_affiliation_strings":["The Ohio State Univ. (United States)","Department of Electrical and Computer Engineering, the Ohio State University, Columbus, 43210, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The Ohio State Univ. (United States)","institution_ids":["https://openalex.org/I52357470"]},{"raw_affiliation_string":"Department of Electrical and Computer Engineering, the Ohio State University, Columbus, 43210, USA","institution_ids":["https://openalex.org/I52357470"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5079352035","display_name":"Lee C. Potter","orcid":"https://orcid.org/0000-0002-1537-1627","observed_orcids":["https://orcid.org/0000-0002-1537-1627"]},"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":"Lee C. Potter","raw_affiliation_strings":["The Ohio State Univ. (United States)","Department of Electrical and Computer Engineering, the Ohio State University, Columbus, 43210, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The Ohio State Univ. (United States)","institution_ids":["https://openalex.org/I52357470"]},{"raw_affiliation_string":"Department of Electrical and Computer Engineering, the Ohio State University, Columbus, 43210, USA","institution_ids":["https://openalex.org/I52357470"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I52357470"],"apc_list":null,"apc_paid":null,"fwci":1.1558,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.72410139,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":"9475","issue":null,"first_page":"947506","last_page":"947506"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10891","display_name":"Radar Systems and Signal Processing","score":0.7699999809265137,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace Engineering"},"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/T10891","display_name":"Radar Systems and Signal Processing","score":0.7699999809265137,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace Engineering"},"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/T11038","display_name":"Advanced SAR Imaging Techniques","score":0.19249999523162842,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace Engineering"},"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/T10688","display_name":"Image and Signal Denoising Methods","score":0.004800000227987766,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/ground-moving-target-indication","display_name":"ground moving target indication","score":0.8970000147819519},{"id":"https://openalex.org/keywords/bayesian-estimation","display_name":"Bayesian estimation","score":0.3930000066757202},{"id":"https://openalex.org/keywords/digital-elevation-maps","display_name":"digital elevation maps","score":0.7749999761581421},{"id":"https://openalex.org/keywords/linear-mixture-model","display_name":"linear mixing model","score":0.9309999942779541},{"id":"https://openalex.org/keywords/space-time-adaptive-processing","display_name":"space-time adaptive processing","score":0.7940000295639038}],"concepts":[{"id":"https://openalex.org/C132094186","wikidata":"https://www.wikidata.org/wiki/Q641585","display_name":"Clutter","level":3,"score":0.8157519102096558},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6900075674057007},{"id":"https://openalex.org/C185142706","wikidata":"https://www.wikidata.org/wiki/Q1134404","display_name":"Covariance matrix","level":2,"score":0.6500354409217834},{"id":"https://openalex.org/C162416716","wikidata":"https://www.wikidata.org/wiki/Q446180","display_name":"Moving target indication","level":5,"score":0.5885515213012695},{"id":"https://openalex.org/C190203512","wikidata":"https://www.wikidata.org/wiki/Q7572182","display_name":"Space-time adaptive processing","level":5,"score":0.5833370685577393},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.48548606038093567},{"id":"https://openalex.org/C178650346","wikidata":"https://www.wikidata.org/wiki/Q201984","display_name":"Covariance","level":2,"score":0.4622476100921631},{"id":"https://openalex.org/C32022120","wikidata":"https://www.wikidata.org/wiki/Q797225","display_name":"Interference (communication)","level":3,"score":0.458906352519989},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.43544384837150574},{"id":"https://openalex.org/C160234255","wikidata":"https://www.wikidata.org/wiki/Q812535","display_name":"Bayesian inference","level":3,"score":0.4344770014286041},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.41954505443573},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.4128757417201996},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3870570957660675},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.19818884134292603},{"id":"https://openalex.org/C554190296","wikidata":"https://www.wikidata.org/wiki/Q47528","display_name":"Radar","level":2,"score":0.16933852434158325},{"id":"https://openalex.org/C139931591","wikidata":"https://www.wikidata.org/wiki/Q1029151","display_name":"Pulse-Doppler radar","level":4,"score":0.1321585476398468},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.12368673086166382},{"id":"https://openalex.org/C10929652","wikidata":"https://www.wikidata.org/wiki/Q7279985","display_name":"Radar imaging","level":3,"score":0.1197553277015686},{"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/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.0},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1117/12.2181907","doi":"https://doi.org/10.1117/12.2181907","is_oa":false,"landing_page_url":"https://doi.org/10.1117/12.2181907","pdf_url":null,"source":{"id":"https://openalex.org/S183492911","display_name":"Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE","issn_l":"0277-786X","issn":["0277-786X","1996-756X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["cwts-core","norway-1"],"host_organization":"https://openalex.org/P4310315543","host_organization_name":"SPIE","host_organization_lineage":["https://openalex.org/P4310315543"],"host_organization_lineage_names":["SPIE"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"SPIE Proceedings","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.5378999710083008,"display_name":"Industry, innovation and infrastructure","id":"https://metadata.un.org/sdg/9"}],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":17,"referenced_works":["https://openalex.org/W1620525164","https://openalex.org/W1976529258","https://openalex.org/W1988922258","https://openalex.org/W1994747941","https://openalex.org/W2006982313","https://openalex.org/W2008294191","https://openalex.org/W2008595386","https://openalex.org/W2012385823","https://openalex.org/W2026933032","https://openalex.org/W2074434407","https://openalex.org/W2098394824","https://openalex.org/W2166307990","https://openalex.org/W2166670884","https://openalex.org/W2951090971","https://openalex.org/W3023218716","https://openalex.org/W6652643762","https://openalex.org/W6684391177"],"related_works":["https://openalex.org/W2792624376","https://openalex.org/W7110504856","https://openalex.org/W2126589201","https://openalex.org/W1784076785","https://openalex.org/W4287877599","https://openalex.org/W2151462182","https://openalex.org/W7110548175","https://openalex.org/W2947489513","https://openalex.org/W2168060129","https://openalex.org/W1595443323"],"abstract_inverted_index":{"Traditional":[0],"ground":[1],"moving":[2,10],"target":[3],"indicator":[4],"(GMTI)":[5],"processing":[6,23,172],"attempts":[7],"to":[8,89,189],"separate":[9],"objects":[11],"in":[12,146],"the":[13,26,34,46,58,91,110,121,140,147,181,187],"scene":[14],"from":[15,45],"stationary":[16],"clutter.":[17],"Techniques":[18],"such":[19],"as":[20],"space-time":[21],"adaptive":[22],"(STAP)":[24],"require":[25],"use":[27],"of":[28,33,81,86,113,123],"an":[29,75,114,124],"unknown":[30],"covariance":[31,60,77,116],"matrix":[32,78],"interference":[35,59,76,115],"(clutter,":[36],"jamming,":[37],"and":[38,102,136,139,170,185],"thermal":[39],"noise)":[40],"that":[41,98,142],"must":[42],"be":[43],"estimated":[44],"remaining":[47],"data":[48],"not":[49],"currently":[50],"under":[51],"test.":[52],"Many":[53],"problems":[54],"exist":[55],"with":[56],"estimating":[57],"including:":[61],"heterogeneous,":[62],"contaminated,":[63],"and/or":[64],"limited":[65],"training":[66],"data.":[67],"There":[68],"are":[69,144,174],"many":[70],"existing":[71],"techniques":[72],"for":[73,160],"obtaining":[74],"estimate,":[79],"most":[80],"which":[82],"incorporate":[83],"some":[84],"kind":[85],"prior":[87],"knowledge":[88,122],"improve":[90],"estimate.":[92],"We":[93,176],"propose":[94],"a":[95,105],"Bayesian":[96,152],"framework":[97],"estimates":[99],"both":[100],"clutter":[101],"movers":[103,143],"on":[104,163],"range-by-":[106],"range":[107],"basis":[108],"without":[109],"explicit":[111],"estimation":[112],"matrix.":[117],"The":[118,167],"approach":[119,179],"incorporates":[120],"approximate":[125],"digital":[126],"elevation":[127],"map":[128],"(DEM),":[129],"platform":[130],"kinematics":[131],"(platform":[132],"velocity,":[133],"crab":[134],"angle,":[135],"antenna":[137],"spacings),":[138],"belief":[141],"sparse":[145],"scene.":[148],"Computation":[149],"using":[150,180],"this":[151],"model":[153,169],"is":[154],"enabled":[155],"by":[156],"recent":[157],"algorithm":[158],"developments":[159],"fast":[161],"inference":[162],"linear":[164],"mixing":[165],"models.":[166],"signal":[168],"required":[171],"steps":[173],"detailed.":[175],"test":[177],"our":[178],"KASSPER":[182],"I":[183],"dataset":[184],"compare":[186],"results":[188],"other":[190],"current":[191],"approaches.":[192]},"counts_by_year":[{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":2}],"updated_date":"2026-10-16T09:59:22.235173","created_date":"2016-06-24T00:00:00"}