{"id":"https://openalex.org/W4292058999","doi":"https://doi.org/10.3390/rs14163931","title":"On the Efficient Implementation of Sparse Bayesian Learning-Based STAP Algorithms","display_name":"On the Efficient Implementation of Sparse Bayesian Learning-Based STAP Algorithms","publication_year":2022,"publication_date":"2022-08-13","ids":{"openalex":"https://openalex.org/W4292058999","doi":"https://doi.org/10.3390/rs14163931"},"language":"en","primary_location":{"id":"doi:10.3390/rs14163931","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs14163931","pdf_url":"https://www.mdpi.com/2072-4292/14/16/3931/pdf?version=1660790588","source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Remote Sensing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/2072-4292/14/16/3931/pdf?version=1660790588","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5045075979","display_name":"Kun Liu","orcid":"https://orcid.org/0000-0002-7349-8730"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kun Liu","raw_affiliation_strings":["National Lab of Radar Signal Processing, Xidian University, Xi\u2019an 710071, China","National Lab of Radar Signal Processing, Xidian University, Xi'an 710071, China"],"affiliations":[{"raw_affiliation_string":"National Lab of Radar Signal Processing, Xidian University, Xi\u2019an 710071, China","institution_ids":["https://openalex.org/I149594827"]},{"raw_affiliation_string":"National Lab of Radar Signal Processing, Xidian University, Xi'an 710071, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100450990","display_name":"Tong Wang","orcid":"https://orcid.org/0000-0002-2664-1354"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Tong Wang","raw_affiliation_strings":["National Lab of Radar Signal Processing, Xidian University, Xi\u2019an 710071, China","National Lab of Radar Signal Processing, Xidian University, Xi'an 710071, China"],"affiliations":[{"raw_affiliation_string":"National Lab of Radar Signal Processing, Xidian University, Xi\u2019an 710071, China","institution_ids":["https://openalex.org/I149594827"]},{"raw_affiliation_string":"National Lab of Radar Signal Processing, Xidian University, Xi'an 710071, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103278899","display_name":"Jianxin Wu","orcid":"https://orcid.org/0000-0001-6968-2861"},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jianxin Wu","raw_affiliation_strings":["School of Electronics and Communication Engineering, Sun Yat-sen University, Guangzhou 510275, China"],"affiliations":[{"raw_affiliation_string":"School of Electronics and Communication Engineering, Sun Yat-sen University, Guangzhou 510275, China","institution_ids":["https://openalex.org/I157773358"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5114803994","display_name":"Cheng Liu","orcid":"https://orcid.org/0000-0002-1369-6292"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Cheng Liu","raw_affiliation_strings":["National Lab of Radar Signal Processing, Xidian University, Xi\u2019an 710071, China","National Lab of Radar Signal Processing, Xidian University, Xi'an 710071, China"],"affiliations":[{"raw_affiliation_string":"National Lab of Radar Signal Processing, Xidian University, Xi\u2019an 710071, China","institution_ids":["https://openalex.org/I149594827"]},{"raw_affiliation_string":"National Lab of Radar Signal Processing, Xidian University, Xi'an 710071, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5080596450","display_name":"Weichen Cui","orcid":"https://orcid.org/0000-0003-4442-6858"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Weichen Cui","raw_affiliation_strings":["National Lab of Radar Signal Processing, Xidian University, Xi\u2019an 710071, China","National Lab of Radar Signal Processing, Xidian University, Xi'an 710071, China"],"affiliations":[{"raw_affiliation_string":"National Lab of Radar Signal Processing, Xidian University, Xi\u2019an 710071, China","institution_ids":["https://openalex.org/I149594827"]},{"raw_affiliation_string":"National Lab of Radar Signal Processing, Xidian University, Xi'an 710071, China","institution_ids":["https://openalex.org/I149594827"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5100450990"],"corresponding_institution_ids":["https://openalex.org/I149594827"],"apc_list":{"value":2500,"currency":"CHF","value_usd":2707},"apc_paid":{"value":2500,"currency":"CHF","value_usd":2707},"fwci":1.7227,"has_fulltext":true,"cited_by_count":3,"citation_normalized_percentile":{"value":0.89596936,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":95},"biblio":{"volume":"14","issue":"16","first_page":"3931","last_page":"3931"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10891","display_name":"Radar Systems and Signal Processing","score":1.0,"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":1.0,"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":0.9998000264167786,"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/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9995999932289124,"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/algorithm","display_name":"Algorithm","score":0.7291501760482788},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6272647380828857},{"id":"https://openalex.org/keywords/space-time-adaptive-processing","display_name":"Space-time adaptive processing","score":0.5444714426994324},{"id":"https://openalex.org/keywords/fast-fourier-transform","display_name":"Fast Fourier transform","score":0.5393810868263245},{"id":"https://openalex.org/keywords/clutter","display_name":"Clutter","score":0.5358717441558838},{"id":"https://openalex.org/keywords/covariance-matrix","display_name":"Covariance matrix","score":0.5319443345069885},{"id":"https://openalex.org/keywords/cholesky-decomposition","display_name":"Cholesky decomposition","score":0.5261951088905334},{"id":"https://openalex.org/keywords/sample-matrix-inversion","display_name":"Sample matrix inversion","score":0.4708024263381958},{"id":"https://openalex.org/keywords/toeplitz-matrix","display_name":"Toeplitz matrix","score":0.440105676651001},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2575015127658844},{"id":"https://openalex.org/keywords/radar","display_name":"Radar","score":0.24528181552886963},{"id":"https://openalex.org/keywords/eigenvalues-and-eigenvectors","display_name":"Eigenvalues and eigenvectors","score":0.19461417198181152},{"id":"https://openalex.org/keywords/radar-imaging","display_name":"Radar imaging","score":0.08095049858093262},{"id":"https://openalex.org/keywords/radar-engineering-details","display_name":"Radar engineering details","score":0.07611900568008423}],"concepts":[{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.7291501760482788},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6272647380828857},{"id":"https://openalex.org/C190203512","wikidata":"https://www.wikidata.org/wiki/Q7572182","display_name":"Space-time adaptive processing","level":5,"score":0.5444714426994324},{"id":"https://openalex.org/C75172450","wikidata":"https://www.wikidata.org/wiki/Q623950","display_name":"Fast Fourier transform","level":2,"score":0.5393810868263245},{"id":"https://openalex.org/C132094186","wikidata":"https://www.wikidata.org/wiki/Q641585","display_name":"Clutter","level":3,"score":0.5358717441558838},{"id":"https://openalex.org/C185142706","wikidata":"https://www.wikidata.org/wiki/Q1134404","display_name":"Covariance matrix","level":2,"score":0.5319443345069885},{"id":"https://openalex.org/C34727166","wikidata":"https://www.wikidata.org/wiki/Q515375","display_name":"Cholesky decomposition","level":3,"score":0.5261951088905334},{"id":"https://openalex.org/C62403268","wikidata":"https://www.wikidata.org/wiki/Q7410141","display_name":"Sample matrix inversion","level":3,"score":0.4708024263381958},{"id":"https://openalex.org/C147710293","wikidata":"https://www.wikidata.org/wiki/Q849428","display_name":"Toeplitz matrix","level":2,"score":0.440105676651001},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2575015127658844},{"id":"https://openalex.org/C554190296","wikidata":"https://www.wikidata.org/wiki/Q47528","display_name":"Radar","level":2,"score":0.24528181552886963},{"id":"https://openalex.org/C158693339","wikidata":"https://www.wikidata.org/wiki/Q190524","display_name":"Eigenvalues and eigenvectors","level":2,"score":0.19461417198181152},{"id":"https://openalex.org/C10929652","wikidata":"https://www.wikidata.org/wiki/Q7279985","display_name":"Radar imaging","level":3,"score":0.08095049858093262},{"id":"https://openalex.org/C134406370","wikidata":"https://www.wikidata.org/wiki/Q832005","display_name":"Radar engineering details","level":4,"score":0.07611900568008423},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"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/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.3390/rs14163931","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs14163931","pdf_url":"https://www.mdpi.com/2072-4292/14/16/3931/pdf?version=1660790588","source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Remote Sensing","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:aca3125da86c4aaba81e21c824111f9b","is_oa":true,"landing_page_url":"https://doaj.org/article/aca3125da86c4aaba81e21c824111f9b","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Remote Sensing, Vol 14, Iss 16, p 3931 (2022)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/2072-4292/14/16/3931/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/rs14163931","pdf_url":null,"source":{"id":"https://openalex.org/S4306400947","display_name":"MDPI (MDPI AG)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210097602","host_organization_name":"Multidisciplinary Digital Publishing Institute (Switzerland)","host_organization_lineage":["https://openalex.org/I4210097602"],"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":"Remote Sensing","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/rs14163931","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs14163931","pdf_url":"https://www.mdpi.com/2072-4292/14/16/3931/pdf?version=1660790588","source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Remote Sensing","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions","score":0.7799999713897705}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4292058999.pdf","grobid_xml":"https://content.openalex.org/works/W4292058999.grobid-xml"},"referenced_works_count":56,"referenced_works":["https://openalex.org/W565312106","https://openalex.org/W1770500012","https://openalex.org/W1986676404","https://openalex.org/W1988946738","https://openalex.org/W1992172678","https://openalex.org/W2009040648","https://openalex.org/W2013438974","https://openalex.org/W2021070329","https://openalex.org/W2021302824","https://openalex.org/W2033419225","https://openalex.org/W2034619772","https://openalex.org/W2046658845","https://openalex.org/W2071284784","https://openalex.org/W2076495042","https://openalex.org/W2097323375","https://openalex.org/W2098012923","https://openalex.org/W2101042764","https://openalex.org/W2104266187","https://openalex.org/W2106515821","https://openalex.org/W2111067490","https://openalex.org/W2111825923","https://openalex.org/W2112258609","https://openalex.org/W2112855412","https://openalex.org/W2113604609","https://openalex.org/W2115706991","https://openalex.org/W2122315118","https://openalex.org/W2125680629","https://openalex.org/W2126607811","https://openalex.org/W2127271355","https://openalex.org/W2134397831","https://openalex.org/W2144158572","https://openalex.org/W2147656689","https://openalex.org/W2148154358","https://openalex.org/W2151693816","https://openalex.org/W2152279006","https://openalex.org/W2159359905","https://openalex.org/W2162409952","https://openalex.org/W2166732227","https://openalex.org/W2250039352","https://openalex.org/W2460384451","https://openalex.org/W2510706873","https://openalex.org/W2580533102","https://openalex.org/W2626738463","https://openalex.org/W2895489867","https://openalex.org/W2900854126","https://openalex.org/W2906161054","https://openalex.org/W2949462039","https://openalex.org/W3004727024","https://openalex.org/W3104426778","https://openalex.org/W3185546052","https://openalex.org/W4200344880","https://openalex.org/W4220757480","https://openalex.org/W4280571332","https://openalex.org/W4300029251","https://openalex.org/W6725542545","https://openalex.org/W6876089446"],"related_works":["https://openalex.org/W1666266471","https://openalex.org/W3016581522","https://openalex.org/W1830551853","https://openalex.org/W2028279303","https://openalex.org/W2130932512","https://openalex.org/W2170243420","https://openalex.org/W4206580878","https://openalex.org/W1990764752","https://openalex.org/W772091534","https://openalex.org/W1985188219"],"abstract_inverted_index":{"Sparse":[0],"Bayesian":[1],"learning-based":[2],"space\u2013time":[3],"adaptive":[4],"processing":[5],"(SBL-STAP)":[6],"algorithms":[7,37,98,157,177],"can":[8,114,149,178],"achieve":[9],"superior":[10],"clutter":[11,24],"suppression":[12],"performance":[13,192],"with":[14,105,165],"limited":[15],"training":[16],"sample":[17],"support":[18],"in":[19,58,91,117,154],"practical":[20],"heterogeneous":[21],"and":[22,48,140],"non-stationary":[23],"environments.":[25],"However,":[26],"when":[27],"the":[28,44,49,59,80,83,92,96,106,110,126,132,136,141,144,155,166,175,181,198,201],"system":[29],"has":[30],"high":[31,40],"degrees":[32],"of":[33,52,95,125,135,143,188,200],"freedom":[34],"(DOFs),":[35],"SBL-STAP":[36,72,97,156,168],"suffer":[38],"from":[39],"computational":[41,182],"complexity,":[42],"since":[43],"large-scale":[45,53],"matrix":[46,113,139],"calculations":[47],"inversion":[50],"operations":[51,153],"covariance":[54,84,112,138],"matrices":[55,85],"are":[56],"involved":[57],"iterative":[60,93],"process.":[61],"In":[62],"this":[63],"article,":[64],"we":[65,148],"consider":[66],"a":[67,100,122,162],"computationally":[68],"efficient":[69,75],"implementation":[70,76],"for":[71,171],"algorithms.":[73,203],"The":[74],"is":[77],"based":[78],"on":[79,131],"fact":[81],"that":[82,86,109],"need":[87],"to":[88],"be":[89,115],"updated":[90],"process":[94],"have":[99],"Hermitian":[101],"Toplitz-block-Toeplitz":[102],"(HTBT)":[103],"structure,":[104],"result":[107],"being":[108],"inverse":[111,137],"expressed":[116],"closed":[118],"form":[119],"by":[120,158,184],"using":[121],"special":[123],"case":[124],"Gohberg\u2013Semencul":[127],"(G-S)":[128],"formula.":[129],"Based":[130],"G-S-type":[133],"factorization":[134],"structure":[142],"used":[145],"dictionary":[146],"matrix,":[147],"perform":[150],"almost":[151],"all":[152],"2-D":[159],"FFT/IFFT.":[160],"As":[161],"result,":[163],"compared":[164],"original":[167],"algorithms,":[169],"even":[170],"moderate":[172],"data":[173],"sizes,":[174],"proposed":[176,202],"directly":[179],"reduce":[180],"load":[183],"about":[185],"two":[186],"orders":[187],"magnitudes":[189],"without":[190],"any":[191],"loss.":[193],"Finally,":[194],"simulation":[195],"results":[196],"validate":[197],"effectiveness":[199]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2022,"cited_by_count":1}],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2025-10-10T00:00:00"}