{"id":"https://openalex.org/W2149673298","doi":"https://doi.org/10.1109/taes.2012.6178068","title":"Statistical Interpretation of a Data Adaptive Clutter Subspace Estimation Algorithm","display_name":"Statistical Interpretation of a Data Adaptive Clutter Subspace Estimation Algorithm","publication_year":2012,"publication_date":"2012-01-01","ids":{"openalex":"https://openalex.org/W2149673298","doi":"https://doi.org/10.1109/taes.2012.6178068","mag":"2149673298"},"language":"en","primary_location":{"id":"doi:10.1109/taes.2012.6178068","is_oa":false,"landing_page_url":"https://doi.org/10.1109/taes.2012.6178068","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/A5037857418","display_name":"R. S. Raghavan","orcid":"https://orcid.org/0000-0001-7355-6817"},"institutions":[{"id":"https://openalex.org/I1280414376","display_name":"United States Air Force Research Laboratory","ror":"https://ror.org/02e2egq70","country_code":"US","type":"facility","lineage":["https://openalex.org/I1280414376","https://openalex.org/I1330347796","https://openalex.org/I4210102105","https://openalex.org/I4389425425"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"R. S. Raghavan","raw_affiliation_strings":["AFRL, OH, USA"],"affiliations":[{"raw_affiliation_string":"AFRL, OH, USA","institution_ids":["https://openalex.org/I1280414376"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5037857418"],"corresponding_institution_ids":["https://openalex.org/I1280414376"],"apc_list":null,"apc_paid":null,"fwci":8.7463,"has_fulltext":false,"cited_by_count":30,"citation_normalized_percentile":{"value":0.97390581,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"48","issue":"2","first_page":"1370","last_page":"1384"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10891","display_name":"Radar Systems and Signal Processing","score":0.998199999332428,"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":0.998199999332428,"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/T10931","display_name":"Direction-of-Arrival Estimation Techniques","score":0.9975000023841858,"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/T11233","display_name":"Advanced Adaptive Filtering Techniques","score":0.9970999956130981,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/clutter","display_name":"Clutter","score":0.7977432012557983},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.672997772693634},{"id":"https://openalex.org/keywords/subspace-topology","display_name":"Subspace topology","score":0.621924638748169},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5744420886039734},{"id":"https://openalex.org/keywords/interpretation","display_name":"Interpretation (philosophy)","score":0.541396975517273},{"id":"https://openalex.org/keywords/estimation-theory","display_name":"Estimation theory","score":0.4722667932510376},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3713316321372986},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.36659950017929077},{"id":"https://openalex.org/keywords/radar","display_name":"Radar","score":0.21594226360321045},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.09847626090049744}],"concepts":[{"id":"https://openalex.org/C132094186","wikidata":"https://www.wikidata.org/wiki/Q641585","display_name":"Clutter","level":3,"score":0.7977432012557983},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.672997772693634},{"id":"https://openalex.org/C32834561","wikidata":"https://www.wikidata.org/wiki/Q660730","display_name":"Subspace topology","level":2,"score":0.621924638748169},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5744420886039734},{"id":"https://openalex.org/C527412718","wikidata":"https://www.wikidata.org/wiki/Q855395","display_name":"Interpretation (philosophy)","level":2,"score":0.541396975517273},{"id":"https://openalex.org/C167928553","wikidata":"https://www.wikidata.org/wiki/Q1376021","display_name":"Estimation theory","level":2,"score":0.4722667932510376},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3713316321372986},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.36659950017929077},{"id":"https://openalex.org/C554190296","wikidata":"https://www.wikidata.org/wiki/Q47528","display_name":"Radar","level":2,"score":0.21594226360321045},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.09847626090049744},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/taes.2012.6178068","is_oa":false,"landing_page_url":"https://doi.org/10.1109/taes.2012.6178068","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":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":42,"referenced_works":["https://openalex.org/W1492221128","https://openalex.org/W1578953027","https://openalex.org/W1667165204","https://openalex.org/W1973176871","https://openalex.org/W1984614739","https://openalex.org/W1999542175","https://openalex.org/W2008662406","https://openalex.org/W2028034811","https://openalex.org/W2036488048","https://openalex.org/W2038085771","https://openalex.org/W2049633694","https://openalex.org/W2063996237","https://openalex.org/W2097417130","https://openalex.org/W2097977627","https://openalex.org/W2099135042","https://openalex.org/W2099444990","https://openalex.org/W2103870658","https://openalex.org/W2104076888","https://openalex.org/W2107820823","https://openalex.org/W2109363365","https://openalex.org/W2110045631","https://openalex.org/W2112708316","https://openalex.org/W2113007636","https://openalex.org/W2114785525","https://openalex.org/W2115458638","https://openalex.org/W2119959491","https://openalex.org/W2123200950","https://openalex.org/W2124759694","https://openalex.org/W2125341398","https://openalex.org/W2125412367","https://openalex.org/W2138320657","https://openalex.org/W2142485381","https://openalex.org/W2142495747","https://openalex.org/W2145118533","https://openalex.org/W2152071579","https://openalex.org/W2152516315","https://openalex.org/W2170481245","https://openalex.org/W3147705998","https://openalex.org/W6629420886","https://openalex.org/W6634728565","https://openalex.org/W6680941772","https://openalex.org/W7024001005"],"related_works":["https://openalex.org/W2130674020","https://openalex.org/W2093748878","https://openalex.org/W2333771223","https://openalex.org/W2120056845","https://openalex.org/W1981531423","https://openalex.org/W2035264131","https://openalex.org/W1679012645","https://openalex.org/W3036468168","https://openalex.org/W2070318884","https://openalex.org/W2011939812"],"abstract_inverted_index":{"Detection":[0],"algorithms":[1],"in":[2,81],"a":[3,117,142,163,187,211],"nonhomogeneous":[4],"clutter":[5,20,49,70,76,113,123],"environment":[6],"have":[7,116],"to":[8,26,67,83,98,128,157,161,185,220,227],"contend":[9],"with":[10,233,261],"the":[11,19,36,44,48,52,57,61,69,72,75,84,87,96,105,110,155,169,174,180,194,200,216,234,239,243,248,256],"problem":[12,181],"of":[13,43,47,56,60,74,86,119,150,168,173,199,238,247,255],"excessive":[14],"false":[15],"alarm":[16],"rates":[17],"when":[18,71,95],"is":[21,79,101,258],"not":[22,102],"sufficiently":[23],"suppressed.":[24],"Prior":[25],"signal":[27,97],"detection,":[28],"adaptive":[29],"receivers":[30],"must":[31,207],"either":[32],"\"null\"":[33],"or":[34],"\"whiten\"":[35],"clutter.":[37,62],"The":[38,223],"former":[39],"approach":[40,189],"requires":[41,54],"estimates":[42,55],"basis":[45,171],"vectors":[46,172],"subspace":[50,77,221,235],"while":[51],"latter":[53],"covariance":[58],"matrix":[59],"It":[63],"may":[64,115],"be":[65,99,183,208],"preferable":[66],"null":[68],"dimensionality":[73],"(M)":[78],"small":[80],"comparison":[82],"length":[85],"data":[88,114,125],"vector":[89,206,230],"coherently":[90],"processed":[91],"(N)":[92],"and":[93,136,153,245],"also":[94],"detected":[100],"substantially":[103],"within":[104],"clutter-plus-noise":[106,175,236],"subspace.":[107,176],"Depending":[108],"on":[109,193],"scenario,":[111],"radar":[112],"variety":[118],"effects":[120,152],"such":[121],"as":[122],"discretes,":[124],"dropouts":[126],"due":[127],"terrain":[129],"masking":[130],"that":[131,179,203],"cause":[132],"shadowing,":[133],"multipath":[134],"effects,":[135],"non-Gaussian":[137],"amplitude":[138],"statistics.":[139],"We":[140,177],"consider":[141],"statistical":[143,253],"model":[144,156],"which":[145],"can":[146,182],"account":[147],"for":[148,190,242],"some":[149],"these":[151],"apply":[154],"design":[158],"an":[159],"algorithm":[160],"obtain":[162],"maximum":[164],"likelihood":[165],"estimate":[166],"(MLE)":[167],"orthonormal":[170],"show":[178,202],"reformulated":[184],"develop":[186],"recursive":[188],"MLE":[191],"based":[192],"expectation-maximization":[195],"(EM)":[196],"algorithm.":[197],"Results":[198],"analysis":[201],"each":[204,228],"training":[205,229],"scaled":[209],"by":[210],"nonnegative":[212],"scale":[213,224],"factor":[214,225],"from":[215],"interval":[217],"[0,1]":[218],"prior":[219],"estimation.":[222],"applied":[226],"increases":[231],"monotonically":[232],"power":[237],"vector.":[240],"Conditions":[241],"existence":[244],"uniqueness":[246],"solution":[249,257],"are":[250],"considered.":[251],"A":[252],"interpretation":[254],"provided":[259],"along":[260],"sample":[262],"simulation":[263],"results.":[264]},"counts_by_year":[{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":3},{"year":2017,"cited_by_count":1},{"year":2016,"cited_by_count":8},{"year":2015,"cited_by_count":6},{"year":2014,"cited_by_count":4},{"year":2013,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}