{"id":"https://openalex.org/W2992098955","doi":"https://doi.org/10.1109/wimob.2019.8923125","title":"GLRT Detection of Nonfluctuating Targets in Background Noise Using Phased Arrays","display_name":"GLRT Detection of Nonfluctuating Targets in Background Noise Using Phased Arrays","publication_year":2019,"publication_date":"2019-10-01","ids":{"openalex":"https://openalex.org/W2992098955","doi":"https://doi.org/10.1109/wimob.2019.8923125","mag":"2992098955"},"language":"en","primary_location":{"id":"doi:10.1109/wimob.2019.8923125","is_oa":false,"landing_page_url":"https://doi.org/10.1109/wimob.2019.8923125","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 International Conference on Wireless and Mobile Computing, Networking and Communications (WiMob)","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/A5087614736","display_name":"Fernando Dar\u00edo Almeida Garc\u00eda","orcid":"https://orcid.org/0000-0003-3747-1511"},"institutions":[{"id":"https://openalex.org/I181391015","display_name":"Universidade Estadual de Campinas (UNICAMP)","ror":"https://ror.org/04wffgt70","country_code":"BR","type":"education","lineage":["https://openalex.org/I181391015"]}],"countries":["BR"],"is_corresponding":true,"raw_author_name":"Fernando Dario Almeida Garcia","raw_affiliation_strings":["Department of Communications, State University of Campinas, S\u00e3o Paulo, Brazil"],"affiliations":[{"raw_affiliation_string":"Department of Communications, State University of Campinas, S\u00e3o Paulo, Brazil","institution_ids":["https://openalex.org/I181391015"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5079110081","display_name":"Henry Carvajal Mora","orcid":"https://orcid.org/0000-0003-0529-8224"},"institutions":[{"id":"https://openalex.org/I4210102282","display_name":"Universidad de Las Am\u00e9ricas","ror":"https://ror.org/0198j4566","country_code":"EC","type":"education","lineage":["https://openalex.org/I4210102282"]}],"countries":["EC"],"is_corresponding":false,"raw_author_name":"Henry Ramiro Carvajal Mora","raw_affiliation_strings":["Telecommunications Engineering, Faculty of Engineering and Applied Sciences, Universidad de las Am\u00e9ricas (UDLA), Quito, Ecuador"],"affiliations":[{"raw_affiliation_string":"Telecommunications Engineering, Faculty of Engineering and Applied Sciences, Universidad de las Am\u00e9ricas (UDLA), Quito, Ecuador","institution_ids":["https://openalex.org/I4210102282"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5007382966","display_name":"Nathaly Orozco Garz\u00f3n","orcid":"https://orcid.org/0000-0002-5232-7529"},"institutions":[{"id":"https://openalex.org/I4210102282","display_name":"Universidad de Las Am\u00e9ricas","ror":"https://ror.org/0198j4566","country_code":"EC","type":"education","lineage":["https://openalex.org/I4210102282"]}],"countries":["EC"],"is_corresponding":false,"raw_author_name":"Nathaly Veronica Orozco Garzon","raw_affiliation_strings":["Telecommunications Engineering, Faculty of Engineering and Applied Sciences, Universidad de las Am\u00e9ricas (UDLA), Quito, Ecuador"],"affiliations":[{"raw_affiliation_string":"Telecommunications Engineering, Faculty of Engineering and Applied Sciences, Universidad de las Am\u00e9ricas (UDLA), Quito, Ecuador","institution_ids":["https://openalex.org/I4210102282"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5087614736"],"corresponding_institution_ids":["https://openalex.org/I181391015"],"apc_list":null,"apc_paid":null,"fwci":0.3967,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.75744048,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":93},"biblio":{"volume":"3","issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10891","display_name":"Radar Systems and Signal Processing","score":0.9998999834060669,"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":0.9998999834060669,"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":0.9952999949455261,"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/T11038","display_name":"Advanced SAR Imaging Techniques","score":0.9890000224113464,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/detector","display_name":"Detector","score":0.6871383190155029},{"id":"https://openalex.org/keywords/statistical-power","display_name":"Statistical power","score":0.5556452870368958},{"id":"https://openalex.org/keywords/monte-carlo-method","display_name":"Monte Carlo method","score":0.541034460067749},{"id":"https://openalex.org/keywords/phased-array","display_name":"Phased array","score":0.539583146572113},{"id":"https://openalex.org/keywords/signal-to-noise-ratio","display_name":"Signal-to-noise ratio (imaging)","score":0.5308113098144531},{"id":"https://openalex.org/keywords/gaussian-noise","display_name":"Gaussian noise","score":0.5273890495300293},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5035507082939148},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.502617597579956},{"id":"https://openalex.org/keywords/detection-theory","display_name":"Detection theory","score":0.47466352581977844},{"id":"https://openalex.org/keywords/noise-power","display_name":"Noise power","score":0.473150372505188},{"id":"https://openalex.org/keywords/probability-density-function","display_name":"Probability density function","score":0.45568370819091797},{"id":"https://openalex.org/keywords/white-noise","display_name":"White noise","score":0.4548604190349579},{"id":"https://openalex.org/keywords/likelihood-ratio-test","display_name":"Likelihood-ratio test","score":0.42474400997161865},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4209873080253601},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.3849315643310547},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3510659635066986},{"id":"https://openalex.org/keywords/power","display_name":"Power (physics)","score":0.2597997784614563},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.20881852507591248},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.1680341362953186},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.11928513646125793}],"concepts":[{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.6871383190155029},{"id":"https://openalex.org/C96608239","wikidata":"https://www.wikidata.org/wiki/Q1199823","display_name":"Statistical power","level":2,"score":0.5556452870368958},{"id":"https://openalex.org/C19499675","wikidata":"https://www.wikidata.org/wiki/Q232207","display_name":"Monte Carlo method","level":2,"score":0.541034460067749},{"id":"https://openalex.org/C55494473","wikidata":"https://www.wikidata.org/wiki/Q727898","display_name":"Phased array","level":3,"score":0.539583146572113},{"id":"https://openalex.org/C13944312","wikidata":"https://www.wikidata.org/wiki/Q7512748","display_name":"Signal-to-noise ratio (imaging)","level":2,"score":0.5308113098144531},{"id":"https://openalex.org/C4199805","wikidata":"https://www.wikidata.org/wiki/Q2725903","display_name":"Gaussian noise","level":2,"score":0.5273890495300293},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5035507082939148},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.502617597579956},{"id":"https://openalex.org/C137270730","wikidata":"https://www.wikidata.org/wiki/Q120811","display_name":"Detection theory","level":3,"score":0.47466352581977844},{"id":"https://openalex.org/C203234222","wikidata":"https://www.wikidata.org/wiki/Q2133519","display_name":"Noise power","level":3,"score":0.473150372505188},{"id":"https://openalex.org/C197055811","wikidata":"https://www.wikidata.org/wiki/Q207522","display_name":"Probability density function","level":2,"score":0.45568370819091797},{"id":"https://openalex.org/C112633086","wikidata":"https://www.wikidata.org/wiki/Q381287","display_name":"White noise","level":2,"score":0.4548604190349579},{"id":"https://openalex.org/C9483764","wikidata":"https://www.wikidata.org/wiki/Q585740","display_name":"Likelihood-ratio test","level":2,"score":0.42474400997161865},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4209873080253601},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.3849315643310547},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3510659635066986},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.2597997784614563},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.20881852507591248},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.1680341362953186},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.11928513646125793},{"id":"https://openalex.org/C21822782","wikidata":"https://www.wikidata.org/wiki/Q131214","display_name":"Antenna (radio)","level":2,"score":0.0},{"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/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/wimob.2019.8923125","is_oa":false,"landing_page_url":"https://doi.org/10.1109/wimob.2019.8923125","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 International Conference on Wireless and Mobile Computing, Networking and Communications (WiMob)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":37,"referenced_works":["https://openalex.org/W65255600","https://openalex.org/W250076511","https://openalex.org/W595851582","https://openalex.org/W1488131479","https://openalex.org/W1526295091","https://openalex.org/W1538006934","https://openalex.org/W1965392255","https://openalex.org/W1986921156","https://openalex.org/W1989192631","https://openalex.org/W1990611835","https://openalex.org/W1996160600","https://openalex.org/W2045638068","https://openalex.org/W2046245205","https://openalex.org/W2061310904","https://openalex.org/W2102591969","https://openalex.org/W2107767668","https://openalex.org/W2124146532","https://openalex.org/W2125391037","https://openalex.org/W2137087144","https://openalex.org/W2312259339","https://openalex.org/W2316416340","https://openalex.org/W2466192277","https://openalex.org/W2475771804","https://openalex.org/W2485142046","https://openalex.org/W2558756740","https://openalex.org/W2611591252","https://openalex.org/W2902638206","https://openalex.org/W3142517368","https://openalex.org/W3191210297","https://openalex.org/W3215551622","https://openalex.org/W4210572675","https://openalex.org/W4230081446","https://openalex.org/W4253629380","https://openalex.org/W4299578957","https://openalex.org/W4300223101","https://openalex.org/W4300440207","https://openalex.org/W4301418813"],"related_works":["https://openalex.org/W2349411638","https://openalex.org/W2015465174","https://openalex.org/W2408444874","https://openalex.org/W2155293550","https://openalex.org/W1966599233","https://openalex.org/W2388242297","https://openalex.org/W2542257450","https://openalex.org/W3216095215","https://openalex.org/W2138552207","https://openalex.org/W2793053744"],"abstract_inverted_index":{"This":[0],"work":[1],"assesses":[2],"the":[3,19,34,37,41,52,66,76,83,95,122,130,137,144,150],"performance":[4,128],"of":[5,21,36,51,97,124,129,149],"a":[6,22,62,90,104,110],"phased":[7],"array":[8],"radar":[9],"working":[10],"in":[11,26,32,147],"background":[12],"noise.":[13],"To":[14],"do":[15],"so,":[16],"we":[17,58,88],"consider":[18],"presence":[20],"nonfluctuating":[23],"target":[24,38],"embedded":[25],"complex":[27],"white":[28],"Gaussian":[29],"noise":[30,42],"(CWGN),":[31],"which":[33],"amplitude":[35],"echo":[39],"and":[40,60,112,117],"power":[43],"are":[44],"assumed":[45],"to":[46,82,142],"be":[47],"unknown.":[48],"Making":[49],"use":[50],"generalized":[53],"likelihood":[54],"ratio":[55,152],"test":[56],"(GLRT),":[57],"design":[59],"analyze":[61],"detector":[63,132,141],"based":[64],"on":[65],"phased-array":[67],"front":[68],"end.":[69],"We":[70],"obtain":[71],"exact":[72],"closed-form":[73],"expressions":[74],"for":[75,94],"probability":[77,96],"density":[78],"functions":[79],"(PDFs)":[80],"corresponding":[81],"detection":[84,98],"statistics.":[85],"In":[86],"addition,":[87],"derive":[89],"fast":[91],"convergent":[92],"series":[93,102],"(PD).":[99],"The":[100,127],"derived":[101],"presents":[103],"low":[105],"computational":[106],"cost":[107],"while":[108],"maintaining":[109],"tractable":[111],"efficient":[113],"solution.":[114],"Numerical":[115],"results":[116],"Monte":[118],"Carlo":[119],"simulations":[120],"corroborate":[121],"validity":[123],"our":[125],"expressions.":[126],"proposed":[131],"is":[133],"also":[134],"compared":[135],"with":[136],"idealized":[138],"Neyman-Pearson":[139],"(NP)":[140],"quantify":[143],"practical":[145],"losses":[146],"terms":[148],"signal-to-noise":[151],"(SNR).":[153]},"counts_by_year":[{"year":2021,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
