{"id":"https://openalex.org/W2592057254","doi":"https://doi.org/10.1109/acssc.2016.7869553","title":"Canonical correlations for target detection in a passive radar network","display_name":"Canonical correlations for target detection in a passive radar network","publication_year":2016,"publication_date":"2016-11-01","ids":{"openalex":"https://openalex.org/W2592057254","doi":"https://doi.org/10.1109/acssc.2016.7869553","mag":"2592057254"},"language":"en","primary_location":{"id":"doi:10.1109/acssc.2016.7869553","is_oa":false,"landing_page_url":"https://doi.org/10.1109/acssc.2016.7869553","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 50th Asilomar Conference on Signals, Systems and Computers","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"http://hdl.handle.net/10902/11094","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100344848","display_name":"Yuan Wang","orcid":"https://orcid.org/0000-0002-4038-8797"},"institutions":[{"id":"https://openalex.org/I72951846","display_name":"Washington State University","ror":"https://ror.org/05dk0ce17","country_code":"US","type":"education","lineage":["https://openalex.org/I72951846"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yuan Wang","raw_affiliation_strings":["Department of Mathematics and Statistics, Washington State University, Pullman, WA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Mathematics and Statistics, Washington State University, Pullman, WA, USA","institution_ids":["https://openalex.org/I72951846"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5080469112","display_name":"Louis L. Scharf","orcid":"https://orcid.org/0000-0003-1764-9335"},"institutions":[{"id":"https://openalex.org/I92446798","display_name":"Colorado State University","ror":"https://ror.org/03k1gpj17","country_code":"US","type":"education","lineage":["https://openalex.org/I92446798"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Louis L. Scharf","raw_affiliation_strings":["Department of Mathematics, Colorado State University, Fort Collins, CO, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Mathematics, Colorado State University, Fort Collins, CO, USA","institution_ids":["https://openalex.org/I92446798"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5059078809","display_name":"Ignacio Santamar\u0131\u0301a","orcid":"https://orcid.org/0000-0003-0040-7436"},"institutions":[{"id":"https://openalex.org/I13134134","display_name":"Universidad de Cantabria","ror":"https://ror.org/046ffzj20","country_code":"ES","type":"education","lineage":["https://openalex.org/I13134134"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"Ignacio Santamaria","raw_affiliation_strings":["Department of Communications Engineering, University of Cantabria, Santander, Spain"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Communications Engineering, University of Cantabria, Santander, Spain","institution_ids":["https://openalex.org/I13134134"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100342606","display_name":"Haonan Wang","orcid":"https://orcid.org/0000-0002-7474-2096"},"institutions":[{"id":"https://openalex.org/I92446798","display_name":"Colorado State University","ror":"https://ror.org/03k1gpj17","country_code":"US","type":"education","lineage":["https://openalex.org/I92446798"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Haonan Wang","raw_affiliation_strings":["Department of Statistics, Colorado State University, Fort Collins, CO, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Statistics, Colorado State University, Fort Collins, CO, USA","institution_ids":["https://openalex.org/I92446798"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":16,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1159","last_page":"1163"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10891","display_name":"Radar Systems and Signal Processing","score":0.9994000196456909,"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":0.9994000196456909,"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/T12879","display_name":"Distributed Sensor Networks and Detection Algorithms","score":0.9923999905586243,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/T11720","display_name":"Probability and Risk Models","score":0.9879999756813049,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/subspace-topology","display_name":"Subspace topology","score":0.7107445597648621},{"id":"https://openalex.org/keywords/mimo","display_name":"MIMO","score":0.5793136954307556},{"id":"https://openalex.org/keywords/passive-radar","display_name":"Passive radar","score":0.5483501553535461},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5429851412773132},{"id":"https://openalex.org/keywords/channel","display_name":"Channel (broadcasting)","score":0.5067222714424133},{"id":"https://openalex.org/keywords/likelihood-ratio-test","display_name":"Likelihood-ratio test","score":0.4854586720466614},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.47517648339271545},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.47279995679855347},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.4468056261539459},{"id":"https://openalex.org/keywords/radar","display_name":"Radar","score":0.28378063440322876},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.27403897047042847},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.23689621686935425},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.21500852704048157},{"id":"https://openalex.org/keywords/bistatic-radar","display_name":"Bistatic radar","score":0.17155328392982483}],"concepts":[{"id":"https://openalex.org/C32834561","wikidata":"https://www.wikidata.org/wiki/Q660730","display_name":"Subspace topology","level":2,"score":0.7107445597648621},{"id":"https://openalex.org/C207987634","wikidata":"https://www.wikidata.org/wiki/Q176862","display_name":"MIMO","level":3,"score":0.5793136954307556},{"id":"https://openalex.org/C151120012","wikidata":"https://www.wikidata.org/wiki/Q2143008","display_name":"Passive radar","level":5,"score":0.5483501553535461},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5429851412773132},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.5067222714424133},{"id":"https://openalex.org/C9483764","wikidata":"https://www.wikidata.org/wiki/Q585740","display_name":"Likelihood-ratio test","level":2,"score":0.4854586720466614},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.47517648339271545},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.47279995679855347},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.4468056261539459},{"id":"https://openalex.org/C554190296","wikidata":"https://www.wikidata.org/wiki/Q47528","display_name":"Radar","level":2,"score":0.28378063440322876},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.27403897047042847},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.23689621686935425},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.21500852704048157},{"id":"https://openalex.org/C100102862","wikidata":"https://www.wikidata.org/wiki/Q2625855","display_name":"Bistatic radar","level":4,"score":0.17155328392982483},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0},{"id":"https://openalex.org/C10929652","wikidata":"https://www.wikidata.org/wiki/Q7279985","display_name":"Radar imaging","level":3,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/acssc.2016.7869553","is_oa":false,"landing_page_url":"https://doi.org/10.1109/acssc.2016.7869553","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 50th Asilomar Conference on Signals, Systems and Computers","raw_type":"proceedings-article"},{"id":"pmh:oai:repositorio.unican.es:10902/11094","is_oa":true,"landing_page_url":"http://hdl.handle.net/10902/11094","pdf_url":null,"source":{"id":"https://openalex.org/S4306400398","display_name":"UCrea (University of Cantabria)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I13134134","host_organization_name":"Universidad de Cantabria","host_organization_lineage":["https://openalex.org/I13134134"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"50th Asilomar Conference on Signals, Systems and Computers, Pacific Grove, California, 2016, 1159-1163","raw_type":"info:eu-repo/semantics/conferenceObject"}],"best_oa_location":{"id":"pmh:oai:repositorio.unican.es:10902/11094","is_oa":true,"landing_page_url":"http://hdl.handle.net/10902/11094","pdf_url":null,"source":{"id":"https://openalex.org/S4306400398","display_name":"UCrea (University of Cantabria)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I13134134","host_organization_name":"Universidad de Cantabria","host_organization_lineage":["https://openalex.org/I13134134"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"50th Asilomar Conference on Signals, Systems and Computers, Pacific Grove, California, 2016, 1159-1163","raw_type":"info:eu-repo/semantics/conferenceObject"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":11,"referenced_works":["https://openalex.org/W1487062216","https://openalex.org/W1836036400","https://openalex.org/W1971589750","https://openalex.org/W1979601639","https://openalex.org/W2101478599","https://openalex.org/W2106033317","https://openalex.org/W2114148673","https://openalex.org/W2118880464","https://openalex.org/W2163852636","https://openalex.org/W2565979243","https://openalex.org/W4251809989"],"related_works":["https://openalex.org/W1980381208","https://openalex.org/W2364594919","https://openalex.org/W2219338811","https://openalex.org/W2167092671","https://openalex.org/W1861706286","https://openalex.org/W2149583853","https://openalex.org/W1120847856","https://openalex.org/W2151840477","https://openalex.org/W2127095042","https://openalex.org/W2098393088"],"abstract_inverted_index":{"In":[0],"this":[1],"work,":[2],"we":[3],"consider":[4,80],"a":[5,17,21,31,38,55,62,81,143],"two-channel":[6],"multiple-input":[7],"multiple-output":[8],"(MIMO)":[9],"passive":[10],"detection":[11,83],"problem,":[12],"in":[13,75,123],"which":[14,68],"there":[15],"is":[16,27,49,69,142],"surveillance":[18,52,153],"array":[19,26],"and":[20,37,61,106,139,152],"reference":[22,25,77,151],"array.":[23],"The":[24,47,121],"known":[28,42],"to":[29],"carry":[30],"linear":[32,56],"combination":[33,57],"of":[34,41,58,65,99,104,117,146],"broadband":[35,59],"noise":[36,60],"subspace":[39,63,73,87],"signal":[40,64,74],"dimension":[43],"but":[44,94],"unknown":[45,66,110],"basis.":[46],"question":[48],"whether":[50],"the":[51,72,76,118,132,150],"channel":[53,125],"carries":[54],"basis,":[67],"correlated":[70],"with":[71],"channel.":[78],"We":[79,130],"second-order":[82],"problem":[84],"where":[85],"these":[86],"signals":[88],"are":[89],"structured":[90],"by":[91],"an":[92],"unknown,":[93],"common,":[95],"p-dimensional":[96],"random":[97],"vector":[98],"symbols":[100],"transmitted":[101],"from":[102],"sources":[103],"opportunity,":[105],"then":[107],"received":[108],"through":[109],"M":[111],"\u00d7":[112],"p":[113],"matrices":[114],"at":[115],"each":[116,124],"M-element":[119],"arrays.":[120],"noises":[122],"have":[126],"arbitrary":[127],"spatial":[128],"correlation.":[129],"derive":[131],"generalized":[133],"likelihood":[134],"ratio":[135],"test":[136],"(GLRT)":[137],"statistic":[138],"show":[140],"it":[141],"monotone":[144],"function":[145],"canonical":[147],"correlations":[148],"between":[149],"channels.":[154]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":3},{"year":2019,"cited_by_count":2},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":3}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}