{"id":"https://openalex.org/W2969217465","doi":"https://doi.org/10.1109/lsp.2019.2936101","title":"Interference Covariance Matrix Structure Classification in Heterogeneous Environment","display_name":"Interference Covariance Matrix Structure Classification in Heterogeneous Environment","publication_year":2019,"publication_date":"2019-08-22","ids":{"openalex":"https://openalex.org/W2969217465","doi":"https://doi.org/10.1109/lsp.2019.2936101","mag":"2969217465"},"language":"en","primary_location":{"id":"doi:10.1109/lsp.2019.2936101","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lsp.2019.2936101","pdf_url":null,"source":{"id":"https://openalex.org/S120629676","display_name":"IEEE Signal Processing Letters","issn_l":"1070-9908","issn":["1070-9908","1558-2361"],"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 Signal Processing Letters","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/A5002391817","display_name":"Vincenzo Carotenuto","orcid":"https://orcid.org/0000-0002-2659-1959"},"institutions":[{"id":"https://openalex.org/I71267560","display_name":"University of Naples Federico II","ror":"https://ror.org/05290cv24","country_code":"IT","type":"education","lineage":["https://openalex.org/I71267560"]}],"countries":["IT"],"is_corresponding":true,"raw_author_name":"Vincenzo Carotenuto","raw_affiliation_strings":["CNIT, udr Universit\u00e0 degli Studi di Napoli \u201cFederico II\u201d, Napoli, Italy"],"raw_orcid":"https://orcid.org/0000-0002-2659-1959","affiliations":[{"raw_affiliation_string":"CNIT, udr Universit\u00e0 degli Studi di Napoli \u201cFederico II\u201d, Napoli, Italy","institution_ids":["https://openalex.org/I71267560"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5044520390","display_name":"Danilo Orlando","orcid":"https://orcid.org/0000-0001-8630-8505"},"institutions":[{"id":"https://openalex.org/I4210124295","display_name":"University Niccol\u00f2 Cusano","ror":"https://ror.org/032c3ae16","country_code":"IT","type":"education","lineage":["https://openalex.org/I4210124295"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Danilo Orlando","raw_affiliation_strings":["Universit\u00e0 degli Studi \u201cNiccol\u00f2 Cusano\u201d, Roma, Italy"],"raw_orcid":"https://orcid.org/0000-0001-8630-8505","affiliations":[{"raw_affiliation_string":"Universit\u00e0 degli Studi \u201cNiccol\u00f2 Cusano\u201d, Roma, Italy","institution_ids":["https://openalex.org/I4210124295"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5045179998","display_name":"Alfonso Farina","orcid":"https://orcid.org/0000-0003-3247-2427"},"institutions":[{"id":"https://openalex.org/I76806421","display_name":"SELEX Sistemi Integrati","ror":"https://ror.org/02sj0zy88","country_code":"IT","type":"company","lineage":["https://openalex.org/I76806421"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Alfonso Farina","raw_affiliation_strings":["Selex ES (retired), Roma, Italy"],"raw_orcid":"https://orcid.org/0000-0003-3247-2427","affiliations":[{"raw_affiliation_string":"Selex ES (retired), Roma, Italy","institution_ids":["https://openalex.org/I76806421"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5002391817"],"corresponding_institution_ids":["https://openalex.org/I71267560"],"apc_list":null,"apc_paid":null,"fwci":11.0284,"has_fulltext":false,"cited_by_count":8,"citation_normalized_percentile":{"value":0.97827194,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":97},"biblio":{"volume":"26","issue":"10","first_page":"1491","last_page":"1495"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10891","display_name":"Radar Systems and Signal Processing","score":0.9998000264167786,"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":0.9998000264167786,"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":0.9976999759674072,"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/T12131","display_name":"Wireless Signal Modulation Classification","score":0.9932000041007996,"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/covariance-matrix","display_name":"Covariance matrix","score":0.845043957233429},{"id":"https://openalex.org/keywords/covariance","display_name":"Covariance","score":0.7073099613189697},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5960575342178345},{"id":"https://openalex.org/keywords/interference","display_name":"Interference (communication)","score":0.5459548234939575},{"id":"https://openalex.org/keywords/estimation-of-covariance-matrices","display_name":"Estimation of covariance matrices","score":0.5390782356262207},{"id":"https://openalex.org/keywords/radar","display_name":"Radar","score":0.5354362726211548},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.510700523853302},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.48616549372673035},{"id":"https://openalex.org/keywords/test-statistic","display_name":"Test statistic","score":0.47775998711586},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4474772810935974},{"id":"https://openalex.org/keywords/scatter-matrix","display_name":"Scatter matrix","score":0.4238853454589844},{"id":"https://openalex.org/keywords/matrix","display_name":"Matrix (chemical analysis)","score":0.41135311126708984},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.39798274636268616},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3581165075302124},{"id":"https://openalex.org/keywords/statistical-hypothesis-testing","display_name":"Statistical hypothesis testing","score":0.2701535224914551},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.23385345935821533},{"id":"https://openalex.org/keywords/channel","display_name":"Channel (broadcasting)","score":0.08092102408409119}],"concepts":[{"id":"https://openalex.org/C185142706","wikidata":"https://www.wikidata.org/wiki/Q1134404","display_name":"Covariance matrix","level":2,"score":0.845043957233429},{"id":"https://openalex.org/C178650346","wikidata":"https://www.wikidata.org/wiki/Q201984","display_name":"Covariance","level":2,"score":0.7073099613189697},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5960575342178345},{"id":"https://openalex.org/C32022120","wikidata":"https://www.wikidata.org/wiki/Q797225","display_name":"Interference (communication)","level":3,"score":0.5459548234939575},{"id":"https://openalex.org/C180877172","wikidata":"https://www.wikidata.org/wiki/Q5401390","display_name":"Estimation of covariance matrices","level":3,"score":0.5390782356262207},{"id":"https://openalex.org/C554190296","wikidata":"https://www.wikidata.org/wiki/Q47528","display_name":"Radar","level":2,"score":0.5354362726211548},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.510700523853302},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.48616549372673035},{"id":"https://openalex.org/C169857963","wikidata":"https://www.wikidata.org/wiki/Q1461038","display_name":"Test statistic","level":3,"score":0.47775998711586},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4474772810935974},{"id":"https://openalex.org/C176917957","wikidata":"https://www.wikidata.org/wiki/Q7430596","display_name":"Scatter matrix","level":4,"score":0.4238853454589844},{"id":"https://openalex.org/C106487976","wikidata":"https://www.wikidata.org/wiki/Q685816","display_name":"Matrix (chemical analysis)","level":2,"score":0.41135311126708984},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.39798274636268616},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3581165075302124},{"id":"https://openalex.org/C87007009","wikidata":"https://www.wikidata.org/wiki/Q210832","display_name":"Statistical hypothesis testing","level":2,"score":0.2701535224914551},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.23385345935821533},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.08092102408409119},{"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/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"score":0.0},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/lsp.2019.2936101","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lsp.2019.2936101","pdf_url":null,"source":{"id":"https://openalex.org/S120629676","display_name":"IEEE Signal Processing Letters","issn_l":"1070-9908","issn":["1070-9908","1558-2361"],"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 Signal Processing Letters","raw_type":"journal-article"},{"id":"pmh:oai:arpi.unipi.it:11568/1270477","is_oa":false,"landing_page_url":"https://hdl.handle.net/11568/1270477","pdf_url":null,"source":{"id":"https://openalex.org/S4377196265","display_name":"CINECA IRIS Institutial research information system (University of Pisa)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I108290504","host_organization_name":"University of Pisa","host_organization_lineage":["https://openalex.org/I108290504"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"info:eu-repo/semantics/article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/15","display_name":"Life in Land","score":0.5099999904632568}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":33,"referenced_works":["https://openalex.org/W1594866568","https://openalex.org/W1814500939","https://openalex.org/W1966397731","https://openalex.org/W1978971170","https://openalex.org/W1986921156","https://openalex.org/W1992511687","https://openalex.org/W2016538497","https://openalex.org/W2063677402","https://openalex.org/W2066762715","https://openalex.org/W2069215735","https://openalex.org/W2076660936","https://openalex.org/W2087527144","https://openalex.org/W2100274697","https://openalex.org/W2103148898","https://openalex.org/W2114217214","https://openalex.org/W2117454350","https://openalex.org/W2123776775","https://openalex.org/W2137102213","https://openalex.org/W2141330891","https://openalex.org/W2157148515","https://openalex.org/W2159376318","https://openalex.org/W2168703653","https://openalex.org/W2241013740","https://openalex.org/W2247519849","https://openalex.org/W2247802672","https://openalex.org/W2326234545","https://openalex.org/W2512311144","https://openalex.org/W2593316319","https://openalex.org/W2608585694","https://openalex.org/W2610765350","https://openalex.org/W2883435103","https://openalex.org/W2907765828","https://openalex.org/W4210572675"],"related_works":["https://openalex.org/W2257909921","https://openalex.org/W4313491988","https://openalex.org/W1978719164","https://openalex.org/W2887132723","https://openalex.org/W2921280830","https://openalex.org/W1670628120","https://openalex.org/W2886934452","https://openalex.org/W2024369332","https://openalex.org/W2088760192","https://openalex.org/W2048445012"],"abstract_inverted_index":{"In":[0,47],"this":[1],"letter,":[2],"an":[3],"adaptive":[4],"approach":[5],"to":[6,24,34,69,92],"classify":[7],"the":[8,11,20,25,29,36,39,49,63,82,98,101,104],"structure":[9,42],"of":[10,22,57,65,81,103],"Interference":[12],"Covariance":[13],"Matrix":[14],"(ICM)":[15],"is":[16,53,67,79,108],"proposed.":[17],"It":[18],"extends":[19],"framework":[21],"[1]":[23],"heterogeneous":[26],"environment":[27],"where":[28],"secondary":[30],"radar":[31,116],"data":[32,72,112],"used":[33],"estimate":[35],"ICM":[37],"share":[38],"same":[40],"covariance":[41],"but":[43],"different":[44],"power":[45,83],"levels.":[46],"particular,":[48],"considered":[50],"classification":[51,87],"problem":[52],"formulated":[54],"in":[55],"terms":[56],"a":[58,74],"multiple":[59],"hypothesis":[60],"test":[61],"and":[62],"Principle":[64],"Invariance":[66],"exploited":[68],"replace":[70],"original":[71],"with":[73],"suitable":[75],"statistic":[76],"whose":[77],"distribution":[78],"independent":[80],"scaling":[84],"factors.":[85],"Then,":[86],"schemes":[88],"are":[89],"devised":[90,106],"resorting":[91],"model":[93],"order":[94],"selection":[95],"rules.":[96],"At":[97],"analysis":[99],"stage,":[100],"effectiveness":[102],"newly":[105],"classifiers":[107],"illustrated":[109],"over":[110],"simulated":[111],"as":[113,115],"well":[114],"measured":[117],"data.":[118]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":2},{"year":2019,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
