{"id":"https://openalex.org/W3035353796","doi":"https://doi.org/10.1109/sam48682.2020.9104339","title":"Underdetermined DOA Estimation of Quasi-Stationary Signals in the Presence of Malfunctioning Sensors","display_name":"Underdetermined DOA Estimation of Quasi-Stationary Signals in the Presence of Malfunctioning Sensors","publication_year":2020,"publication_date":"2020-06-01","ids":{"openalex":"https://openalex.org/W3035353796","doi":"https://doi.org/10.1109/sam48682.2020.9104339","mag":"3035353796"},"language":"en","primary_location":{"id":"doi:10.1109/sam48682.2020.9104339","is_oa":false,"landing_page_url":"https://doi.org/10.1109/sam48682.2020.9104339","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE 11th Sensor Array and Multichannel Signal Processing Workshop (SAM)","raw_type":"proceedings-article"},"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":"https://openalex.org/A5056061849","display_name":"Weize Sun","orcid":"https://orcid.org/0000-0002-8658-7775"},"institutions":[{"id":"https://openalex.org/I180726961","display_name":"Shenzhen University","ror":"https://ror.org/01vy4gh70","country_code":"CN","type":"education","lineage":["https://openalex.org/I180726961"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Weize Sun","raw_affiliation_strings":["Guangdong Laboratory of Artificial Intelligence and Cyber-Economics(SZ), nShenzhen University, ShenZhen, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Guangdong Laboratory of Artificial Intelligence and Cyber-Economics(SZ), nShenzhen University, ShenZhen, China","institution_ids":["https://openalex.org/I180726961"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5089319597","display_name":"Chuangxiang XU","orcid":null},"institutions":[{"id":"https://openalex.org/I180726961","display_name":"Shenzhen University","ror":"https://ror.org/01vy4gh70","country_code":"CN","type":"education","lineage":["https://openalex.org/I180726961"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chuangxiang XU","raw_affiliation_strings":["Guangdong Laboratory of Artificial Intelligence and Cyber-Economics(SZ), Shenzhen University, ShenZhen, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Guangdong Laboratory of Artificial Intelligence and Cyber-Economics(SZ), Shenzhen University, ShenZhen, China","institution_ids":["https://openalex.org/I180726961"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5013499211","display_name":"Yingying Huang","orcid":"https://orcid.org/0000-0001-9868-9747"},"institutions":[{"id":"https://openalex.org/I180726961","display_name":"Shenzhen University","ror":"https://ror.org/01vy4gh70","country_code":"CN","type":"education","lineage":["https://openalex.org/I180726961"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yingying Huang","raw_affiliation_strings":["Guangdong Laboratory of Artificial Intelligence and Cyber-Economics(SZ), Shenzhen University, ShenZhen, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Guangdong Laboratory of Artificial Intelligence and Cyber-Economics(SZ), Shenzhen University, ShenZhen, China","institution_ids":["https://openalex.org/I180726961"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5108051851","display_name":"Lei Huang","orcid":"https://orcid.org/0000-0002-2024-1130"},"institutions":[{"id":"https://openalex.org/I180726961","display_name":"Shenzhen University","ror":"https://ror.org/01vy4gh70","country_code":"CN","type":"education","lineage":["https://openalex.org/I180726961"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lei Huang","raw_affiliation_strings":["Guangdong Laboratory of Artificial Intelligence and Cyber-Economics(SZ), Shenzhen University, ShenZhen, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Guangdong Laboratory of Artificial Intelligence and Cyber-Economics(SZ), Shenzhen University, ShenZhen, China","institution_ids":["https://openalex.org/I180726961"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I180726961"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.05472637,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"63","issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10931","display_name":"Direction-of-Arrival Estimation Techniques","score":0.9998999834060669,"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"}},"topics":[{"id":"https://openalex.org/T10931","display_name":"Direction-of-Arrival Estimation Techniques","score":0.9998999834060669,"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/T10860","display_name":"Speech and Audio Processing","score":0.998199999332428,"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/T10891","display_name":"Radar Systems and Signal Processing","score":0.9957000017166138,"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/underdetermined-system","display_name":"Underdetermined system","score":0.8299288749694824},{"id":"https://openalex.org/keywords/subspace-topology","display_name":"Subspace topology","score":0.7485666871070862},{"id":"https://openalex.org/keywords/direction-of-arrival","display_name":"Direction of arrival","score":0.7289859652519226},{"id":"https://openalex.org/keywords/coprime-integers","display_name":"Coprime integers","score":0.6929693818092346},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6073218584060669},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5773101449012756},{"id":"https://openalex.org/keywords/covariance-matrix","display_name":"Covariance matrix","score":0.513020932674408},{"id":"https://openalex.org/keywords/covariance","display_name":"Covariance","score":0.48988574743270874},{"id":"https://openalex.org/keywords/state","display_name":"State (computer science)","score":0.4378345310688019},{"id":"https://openalex.org/keywords/sensor-array","display_name":"Sensor array","score":0.4371236562728882},{"id":"https://openalex.org/keywords/signal-subspace","display_name":"Signal subspace","score":0.42561036348342896},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.32111644744873047},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.19254809617996216},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.14068925380706787},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.13283908367156982},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.1146664023399353}],"concepts":[{"id":"https://openalex.org/C179690561","wikidata":"https://www.wikidata.org/wiki/Q4316110","display_name":"Underdetermined system","level":2,"score":0.8299288749694824},{"id":"https://openalex.org/C32834561","wikidata":"https://www.wikidata.org/wiki/Q660730","display_name":"Subspace topology","level":2,"score":0.7485666871070862},{"id":"https://openalex.org/C172051844","wikidata":"https://www.wikidata.org/wiki/Q5280438","display_name":"Direction of arrival","level":3,"score":0.7289859652519226},{"id":"https://openalex.org/C23230895","wikidata":"https://www.wikidata.org/wiki/Q104752","display_name":"Coprime integers","level":2,"score":0.6929693818092346},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6073218584060669},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5773101449012756},{"id":"https://openalex.org/C185142706","wikidata":"https://www.wikidata.org/wiki/Q1134404","display_name":"Covariance matrix","level":2,"score":0.513020932674408},{"id":"https://openalex.org/C178650346","wikidata":"https://www.wikidata.org/wiki/Q201984","display_name":"Covariance","level":2,"score":0.48988574743270874},{"id":"https://openalex.org/C48103436","wikidata":"https://www.wikidata.org/wiki/Q599031","display_name":"State (computer science)","level":2,"score":0.4378345310688019},{"id":"https://openalex.org/C66251956","wikidata":"https://www.wikidata.org/wiki/Q7451086","display_name":"Sensor array","level":2,"score":0.4371236562728882},{"id":"https://openalex.org/C2777121530","wikidata":"https://www.wikidata.org/wiki/Q7512739","display_name":"Signal subspace","level":4,"score":0.42561036348342896},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.32111644744873047},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.19254809617996216},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.14068925380706787},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.13283908367156982},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.1146664023399353},{"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/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","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:10.1109/sam48682.2020.9104339","is_oa":false,"landing_page_url":"https://doi.org/10.1109/sam48682.2020.9104339","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE 11th Sensor Array and Multichannel Signal Processing Workshop (SAM)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":29,"referenced_works":["https://openalex.org/W1963068807","https://openalex.org/W1973489105","https://openalex.org/W1998301743","https://openalex.org/W2018419043","https://openalex.org/W2033691878","https://openalex.org/W2042291830","https://openalex.org/W2045740791","https://openalex.org/W2046855287","https://openalex.org/W2074853220","https://openalex.org/W2085156437","https://openalex.org/W2099085385","https://openalex.org/W2101658087","https://openalex.org/W2107244205","https://openalex.org/W2113638573","https://openalex.org/W2115309662","https://openalex.org/W2129013763","https://openalex.org/W2133507081","https://openalex.org/W2158169606","https://openalex.org/W2224644547","https://openalex.org/W2263854549","https://openalex.org/W2541625224","https://openalex.org/W2559682492","https://openalex.org/W2606284533","https://openalex.org/W2794361188","https://openalex.org/W2914623695","https://openalex.org/W2943802243","https://openalex.org/W2978208636","https://openalex.org/W6643320455","https://openalex.org/W6658892764"],"related_works":["https://openalex.org/W2372042310","https://openalex.org/W2011972562","https://openalex.org/W2009153891","https://openalex.org/W2042828345","https://openalex.org/W4388819947","https://openalex.org/W2849843506","https://openalex.org/W4317795331","https://openalex.org/W3205335469","https://openalex.org/W2462138637","https://openalex.org/W334600925"],"abstract_inverted_index":{"This":[0],"paper":[1],"address":[2],"the":[3,22,26,43,48,72,81,89,93,106,109],"problem":[4],"of":[5,9,25,30,47,88,108],"direction-of-arrival":[6],"(DOA)":[7],"estimation":[8],"quasi-stationary":[10,31],"signals":[11,50],"based":[12],"on":[13],"uniform":[14],"linear":[15,59],"array":[16,60],"with":[17],"malfunctioning":[18],"sensors.":[19],"By":[20],"utilizing":[21],"subspace":[23,35],"structures":[24],"local":[27,44],"second-order":[28],"statistics":[29],"signals,":[32],"a":[33,56,85],"Khatri-Rao":[34],"approach":[36],"is":[37,77,84],"developed.":[38],"Our":[39],"scheme":[40],"first":[41],"collects":[42],"covariance":[45],"matrices":[46],"source":[49],"and":[51,112],"then":[52],"transfers":[53],"them":[54],"into":[55],"new":[57],"virtual":[58],"which":[61],"can":[62,96],"identify":[63],"at":[64],"least":[65],"twice":[66],"as":[67,70],"much":[68],"DOAs":[69],"to":[71],"original":[73],"physical":[74],"one.":[75],"It":[76],"also":[78,102],"shown":[79],"that":[80],"coprime":[82],"configuration":[83],"special":[86],"case":[87],"proposed":[90,110],"model":[91],"therefore":[92],"same":[94],"techniques":[95],"be":[97],"applied":[98],"directly.":[99],"Simulations":[100],"are":[101],"carried":[103],"out":[104],"for":[105],"comparison":[107],"algorithm":[111],"state-of-the-art":[113],"approaches.":[114]},"counts_by_year":[],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
