{"id":"https://openalex.org/W2559445141","doi":"https://doi.org/10.1186/s13634-016-0425-0","title":"Robust group compressive sensing for DOA estimation with partially distorted observations","display_name":"Robust group compressive sensing for DOA estimation with partially distorted observations","publication_year":2016,"publication_date":"2016-12-01","ids":{"openalex":"https://openalex.org/W2559445141","doi":"https://doi.org/10.1186/s13634-016-0425-0","mag":"2559445141"},"language":"en","primary_location":{"id":"doi:10.1186/s13634-016-0425-0","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s13634-016-0425-0","pdf_url":"https://asp-eurasipjournals.springeropen.com/track/pdf/10.1186/s13634-016-0425-0","source":{"id":"https://openalex.org/S35920007","display_name":"EURASIP Journal on Advances in Signal Processing","issn_l":"1687-6172","issn":["1687-6172","1687-6180"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"EURASIP Journal on Advances in Signal Processing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://asp-eurasipjournals.springeropen.com/track/pdf/10.1186/s13634-016-0425-0","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100341640","display_name":"Ben Wang","orcid":"https://orcid.org/0000-0003-1604-8108"},"institutions":[{"id":"https://openalex.org/I151727225","display_name":"Harbin Engineering University","ror":"https://ror.org/03x80pn82","country_code":"CN","type":"education","lineage":["https://openalex.org/I151727225"]},{"id":"https://openalex.org/I84392919","display_name":"Temple University","ror":"https://ror.org/00kx1jb78","country_code":"US","type":"education","lineage":["https://openalex.org/I84392919"]}],"countries":["CN","US"],"is_corresponding":true,"raw_author_name":"Ben Wang","raw_affiliation_strings":["College of Automation, Harbin Engineering University, Harbin, Heilongjiang, 150001, China","Department of Electrical and Computer Engineering, Temple University, Philadelphia, 19122, PA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Automation, Harbin Engineering University, Harbin, Heilongjiang, 150001, China","institution_ids":["https://openalex.org/I151727225"]},{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Temple University, Philadelphia, 19122, PA, USA","institution_ids":["https://openalex.org/I84392919"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5074195801","display_name":"Yimin D. Zhang","orcid":"https://orcid.org/0000-0002-4625-209X"},"institutions":[{"id":"https://openalex.org/I84392919","display_name":"Temple University","ror":"https://ror.org/00kx1jb78","country_code":"US","type":"education","lineage":["https://openalex.org/I84392919"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yimin D. Zhang","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Temple University, Philadelphia, 19122, PA, USA"],"raw_orcid":"https://orcid.org/0000-0002-4625-209X","affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Temple University, Philadelphia, 19122, PA, USA","institution_ids":["https://openalex.org/I84392919"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100391971","display_name":"Wei Wang","orcid":"https://orcid.org/0000-0002-4392-1884"},"institutions":[{"id":"https://openalex.org/I151727225","display_name":"Harbin Engineering University","ror":"https://ror.org/03x80pn82","country_code":"CN","type":"education","lineage":["https://openalex.org/I151727225"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wei Wang","raw_affiliation_strings":["College of Automation, Harbin Engineering University, Harbin, Heilongjiang, 150001, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Automation, Harbin Engineering University, Harbin, Heilongjiang, 150001, China","institution_ids":["https://openalex.org/I151727225"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5100341640"],"corresponding_institution_ids":["https://openalex.org/I151727225","https://openalex.org/I84392919"],"apc_list":{"value":1140,"currency":"GBP","value_usd":1398},"apc_paid":{"value":1140,"currency":"GBP","value_usd":1398},"fwci":4.0122,"has_fulltext":true,"cited_by_count":15,"citation_normalized_percentile":{"value":0.93661278,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":"2016","issue":"1","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9998000264167786,"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"}},"topics":[{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9998000264167786,"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"}},{"id":"https://openalex.org/T10931","display_name":"Direction-of-Arrival Estimation Techniques","score":0.9998000264167786,"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":0.9998000264167786,"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/compressed-sensing","display_name":"Compressed sensing","score":0.7168144583702087},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.6851194500923157},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6204221844673157},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.6118375658988953},{"id":"https://openalex.org/keywords/weighting","display_name":"Weighting","score":0.554898738861084},{"id":"https://openalex.org/keywords/narrowband","display_name":"Narrowband","score":0.5303871035575867},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.5295392274856567},{"id":"https://openalex.org/keywords/signal-reconstruction","display_name":"Signal reconstruction","score":0.48306944966316223},{"id":"https://openalex.org/keywords/direction-of-arrival","display_name":"Direction of arrival","score":0.43928971886634827},{"id":"https://openalex.org/keywords/residual","display_name":"Residual","score":0.4340604245662689},{"id":"https://openalex.org/keywords/mean-squared-error","display_name":"Mean squared error","score":0.4155062437057495},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.30429357290267944},{"id":"https://openalex.org/keywords/signal-processing","display_name":"Signal processing","score":0.23322966694831848},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.11542749404907227},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.10988098382949829}],"concepts":[{"id":"https://openalex.org/C124851039","wikidata":"https://www.wikidata.org/wiki/Q2665459","display_name":"Compressed sensing","level":2,"score":0.7168144583702087},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.6851194500923157},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6204221844673157},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.6118375658988953},{"id":"https://openalex.org/C183115368","wikidata":"https://www.wikidata.org/wiki/Q856577","display_name":"Weighting","level":2,"score":0.554898738861084},{"id":"https://openalex.org/C2776096036","wikidata":"https://www.wikidata.org/wiki/Q1140483","display_name":"Narrowband","level":2,"score":0.5303871035575867},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.5295392274856567},{"id":"https://openalex.org/C70958404","wikidata":"https://www.wikidata.org/wiki/Q7512728","display_name":"Signal reconstruction","level":4,"score":0.48306944966316223},{"id":"https://openalex.org/C172051844","wikidata":"https://www.wikidata.org/wiki/Q5280438","display_name":"Direction of arrival","level":3,"score":0.43928971886634827},{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.4340604245662689},{"id":"https://openalex.org/C139945424","wikidata":"https://www.wikidata.org/wiki/Q1940696","display_name":"Mean squared error","level":2,"score":0.4155062437057495},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.30429357290267944},{"id":"https://openalex.org/C104267543","wikidata":"https://www.wikidata.org/wiki/Q208163","display_name":"Signal processing","level":3,"score":0.23322966694831848},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.11542749404907227},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.10988098382949829},{"id":"https://openalex.org/C554190296","wikidata":"https://www.wikidata.org/wiki/Q47528","display_name":"Radar","level":2,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"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/C126838900","wikidata":"https://www.wikidata.org/wiki/Q77604","display_name":"Radiology","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1186/s13634-016-0425-0","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s13634-016-0425-0","pdf_url":"https://asp-eurasipjournals.springeropen.com/track/pdf/10.1186/s13634-016-0425-0","source":{"id":"https://openalex.org/S35920007","display_name":"EURASIP Journal on Advances in Signal Processing","issn_l":"1687-6172","issn":["1687-6172","1687-6180"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"EURASIP Journal on Advances in Signal Processing","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1186/s13634-016-0425-0","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s13634-016-0425-0","pdf_url":"https://asp-eurasipjournals.springeropen.com/track/pdf/10.1186/s13634-016-0425-0","source":{"id":"https://openalex.org/S35920007","display_name":"EURASIP Journal on Advances in Signal Processing","issn_l":"1687-6172","issn":["1687-6172","1687-6180"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"EURASIP Journal on Advances in Signal Processing","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G3985473536","display_name":null,"funder_award_id":"1547420","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G3997724014","display_name":null,"funder_award_id":"2014M550182","funder_id":"https://openalex.org/F4320322725","funder_display_name":"China Scholarship Council"},{"id":"https://openalex.org/G474170905","display_name":null,"funder_award_id":"AST-1547420","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G6690599635","display_name":null,"funder_award_id":"2014M550182","funder_id":"https://openalex.org/F4320321543","funder_display_name":"China Postdoctoral Science Foundation"},{"id":"https://openalex.org/G7339644141","display_name":null,"funder_award_id":"2015T80328","funder_id":"https://openalex.org/F4320321543","funder_display_name":"China Postdoctoral Science Foundation"},{"id":"https://openalex.org/G8250933972","display_name":null,"funder_award_id":"61571148","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320312387","display_name":"Temple University","ror":"https://ror.org/00kx1jb78"},{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320321543","display_name":"China Postdoctoral Science Foundation","ror":"https://ror.org/0426zh255"},{"id":"https://openalex.org/F4320322725","display_name":"China Scholarship Council","ror":"https://ror.org/04atp4p48"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2559445141.pdf","grobid_xml":"https://content.openalex.org/works/W2559445141.grobid-xml"},"referenced_works_count":27,"referenced_works":["https://openalex.org/W1578518384","https://openalex.org/W1964901096","https://openalex.org/W1987996612","https://openalex.org/W1991031161","https://openalex.org/W2003157621","https://openalex.org/W2033332370","https://openalex.org/W2046039020","https://openalex.org/W2066218102","https://openalex.org/W2071284784","https://openalex.org/W2085910483","https://openalex.org/W2109857912","https://openalex.org/W2113638573","https://openalex.org/W2127271355","https://openalex.org/W2128439740","https://openalex.org/W2129302642","https://openalex.org/W2135046866","https://openalex.org/W2135160607","https://openalex.org/W2135780853","https://openalex.org/W2138019504","https://openalex.org/W2140728947","https://openalex.org/W2145856765","https://openalex.org/W2148604588","https://openalex.org/W2166329520","https://openalex.org/W2187618798","https://openalex.org/W2473227930","https://openalex.org/W2511885285","https://openalex.org/W3013302814"],"related_works":["https://openalex.org/W2378166785","https://openalex.org/W2156466545","https://openalex.org/W2379468505","https://openalex.org/W3104324607","https://openalex.org/W4206981968","https://openalex.org/W2308961925","https://openalex.org/W2601968125","https://openalex.org/W2391187634","https://openalex.org/W4285251805","https://openalex.org/W2102910599"],"abstract_inverted_index":{"In":[0,65,85],"this":[1,86],"paper,":[2],"we":[3,53,67],"propose":[4,54],"a":[5,55,69,140,158,174],"robust":[6,56,175],"direction-of-arrival":[7],"(DOA)":[8],"estimation":[9,30,111,121],"algorithm":[10,16,40,58,136,194],"based":[11],"on":[12],"group":[13,24,44,176],"sparse":[14,25,45,134],"reconstruction":[15,26,57,135,142],"utilizing":[17],"signals":[18],"observed":[19,73],"at":[20],"multiple":[21],"frequencies.":[22],"The":[23,187],"scheme":[27],"for":[28],"DOA":[29,185],"is":[31,151,161,180],"solved":[32],"through":[33],"the":[34,43,48,60,72,88,93,100,105,110,116,120,125,132,146,155,166,169,192],"complex":[35],"multitask":[36],"Bayesian":[37],"compressive":[38,177],"sensing":[39,178],"by":[41],"exploiting":[42,145],"property":[46],"of":[47,62,99,109,119,168,191],"received":[49],"multi-frequency":[50],"signals.":[51,64],"Then,":[52],"in":[59,75,131],"presence":[61],"distorted":[63,79,170],"particular,":[66],"consider":[68],"problem":[70],"where":[71],"data":[74],"some":[76,108],"frequencies":[77],"are":[78,195],"due":[80,103],"to,":[81],"e.g.,":[82],"interference":[83],"contamination.":[84],"case,":[87],"residual":[89],"error":[90,122],"will":[91],"follow":[92],"impulsive":[94,156],"Gaussian":[95,101],"mixture":[96],"distribution":[97,102],"instead":[98],"to":[104,139,154,163,182],"fact":[106],"that":[107],"errors":[112],"significantly":[113],"depart":[114],"from":[115],"mean":[117],"value":[118],"distribution.":[123],"Thus,":[124],"minimum":[126],"least":[127],"square":[128],"restriction":[129],"used":[130],"conventional":[133],"may":[137],"lead":[138],"failed":[141],"result.":[143],"By":[144],"maximum":[147],"correntropy":[148],"criterion":[149],"which":[150],"inherently":[152],"insensitive":[153],"noise,":[157],"weighting":[159],"vector":[160],"derived":[162],"automatically":[164],"mitigate":[165],"effect":[167],"narrowband":[171],"signals,":[172],"and":[173,189],"approach":[179],"developed":[181],"achieve":[183],"reliable":[184],"estimation.":[186],"robustness":[188],"effectiveness":[190],"proposed":[193],"verified":[196],"using":[197],"simulation":[198],"results.":[199]},"counts_by_year":[{"year":2020,"cited_by_count":2},{"year":2018,"cited_by_count":3},{"year":2017,"cited_by_count":9},{"year":2016,"cited_by_count":1}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}
