{"id":"https://openalex.org/W4417284399","doi":"https://doi.org/10.1109/access.2025.3643750","title":"FDA-STAP by Shrinkage Algorithm Under Range Ambiguity for Limited Training Samples","display_name":"FDA-STAP by Shrinkage Algorithm Under Range Ambiguity for Limited Training Samples","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4417284399","doi":"https://doi.org/10.1109/access.2025.3643750"},"language":null,"primary_location":{"id":"doi:10.1109/access.2025.3643750","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2025.3643750","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1109/access.2025.3643750","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5000824035","display_name":"Di Song","orcid":null},"institutions":[{"id":"https://openalex.org/I4210110718","display_name":"Nanyang Normal University","ror":"https://ror.org/01f7yer47","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210110718"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Di Song","raw_affiliation_strings":["School of Physics and Electronic Engineering, Nanyang Normal University, Nanyang, China"],"raw_orcid":"https://orcid.org/0000-0002-6704-6471","affiliations":[{"raw_affiliation_string":"School of Physics and Electronic Engineering, Nanyang Normal University, Nanyang, China","institution_ids":["https://openalex.org/I4210110718"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5108718287","display_name":"Chunyu Song","orcid":null},"institutions":[{"id":"https://openalex.org/I4210110718","display_name":"Nanyang Normal University","ror":"https://ror.org/01f7yer47","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210110718"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chunyu Song","raw_affiliation_strings":["School of Physics and Electronic Engineering, Nanyang Normal University, Nanyang, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Physics and Electronic Engineering, Nanyang Normal University, Nanyang, China","institution_ids":["https://openalex.org/I4210110718"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100638487","display_name":"Dawei Liu","orcid":"https://orcid.org/0000-0002-2268-5632"},"institutions":[{"id":"https://openalex.org/I58995867","display_name":"Civil Aviation Flight University of China","ror":"https://ror.org/01xyb1v19","country_code":"CN","type":"education","lineage":["https://openalex.org/I58995867"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dawei Liu","raw_affiliation_strings":["Luoyang College, Civil Aviation Flight University of China, Luoyang, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Luoyang College, Civil Aviation Flight University of China, Luoyang, China","institution_ids":["https://openalex.org/I58995867"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5102969023","display_name":"Zhao Wang","orcid":"https://orcid.org/0000-0003-1860-8391"},"institutions":[{"id":"https://openalex.org/I58995867","display_name":"Civil Aviation Flight University of China","ror":"https://ror.org/01xyb1v19","country_code":"CN","type":"education","lineage":["https://openalex.org/I58995867"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhao Wang","raw_affiliation_strings":["Luoyang College, Civil Aviation Flight University of China, Luoyang, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Luoyang College, Civil Aviation Flight University of China, Luoyang, China","institution_ids":["https://openalex.org/I58995867"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5000824035"],"corresponding_institution_ids":["https://openalex.org/I4210110718"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.47021288,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"13","issue":null,"first_page":"213092","last_page":"213106"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10891","display_name":"Radar Systems and Signal Processing","score":0.8046000003814697,"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":0.8046000003814697,"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":0.16850000619888306,"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":0.015200000256299973,"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/clutter","display_name":"Clutter","score":0.9003999829292297},{"id":"https://openalex.org/keywords/covariance-matrix","display_name":"Covariance matrix","score":0.6460999846458435},{"id":"https://openalex.org/keywords/radar","display_name":"Radar","score":0.5534999966621399},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.515500009059906},{"id":"https://openalex.org/keywords/space-time-adaptive-processing","display_name":"Space-time adaptive processing","score":0.499099999666214},{"id":"https://openalex.org/keywords/range","display_name":"Range (aeronautics)","score":0.47780001163482666},{"id":"https://openalex.org/keywords/eigenvalues-and-eigenvectors","display_name":"Eigenvalues and eigenvectors","score":0.4262000024318695},{"id":"https://openalex.org/keywords/constant-false-alarm-rate","display_name":"Constant false alarm rate","score":0.4171000123023987},{"id":"https://openalex.org/keywords/matrix","display_name":"Matrix (chemical analysis)","score":0.35740000009536743}],"concepts":[{"id":"https://openalex.org/C132094186","wikidata":"https://www.wikidata.org/wiki/Q641585","display_name":"Clutter","level":3,"score":0.9003999829292297},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.667900025844574},{"id":"https://openalex.org/C185142706","wikidata":"https://www.wikidata.org/wiki/Q1134404","display_name":"Covariance matrix","level":2,"score":0.6460999846458435},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.637499988079071},{"id":"https://openalex.org/C554190296","wikidata":"https://www.wikidata.org/wiki/Q47528","display_name":"Radar","level":2,"score":0.5534999966621399},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.515500009059906},{"id":"https://openalex.org/C190203512","wikidata":"https://www.wikidata.org/wiki/Q7572182","display_name":"Space-time adaptive processing","level":5,"score":0.499099999666214},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.47780001163482666},{"id":"https://openalex.org/C158693339","wikidata":"https://www.wikidata.org/wiki/Q190524","display_name":"Eigenvalues and eigenvectors","level":2,"score":0.4262000024318695},{"id":"https://openalex.org/C77052588","wikidata":"https://www.wikidata.org/wiki/Q644307","display_name":"Constant false alarm rate","level":2,"score":0.4171000123023987},{"id":"https://openalex.org/C106487976","wikidata":"https://www.wikidata.org/wiki/Q685816","display_name":"Matrix (chemical analysis)","level":2,"score":0.35740000009536743},{"id":"https://openalex.org/C207467116","wikidata":"https://www.wikidata.org/wiki/Q4385666","display_name":"Inverse","level":2,"score":0.35010001063346863},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3424000144004822},{"id":"https://openalex.org/C178650346","wikidata":"https://www.wikidata.org/wiki/Q201984","display_name":"Covariance","level":2,"score":0.34139999747276306},{"id":"https://openalex.org/C32283439","wikidata":"https://www.wikidata.org/wiki/Q1407014","display_name":"Radar tracker","level":3,"score":0.335099995136261},{"id":"https://openalex.org/C29265498","wikidata":"https://www.wikidata.org/wiki/Q7047719","display_name":"Noise measurement","level":3,"score":0.3271999955177307},{"id":"https://openalex.org/C13944312","wikidata":"https://www.wikidata.org/wiki/Q7512748","display_name":"Signal-to-noise ratio (imaging)","level":2,"score":0.3197000026702881},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.31859999895095825},{"id":"https://openalex.org/C203234222","wikidata":"https://www.wikidata.org/wiki/Q2133519","display_name":"Noise power","level":3,"score":0.31459999084472656},{"id":"https://openalex.org/C96608239","wikidata":"https://www.wikidata.org/wiki/Q1199823","display_name":"Statistical power","level":2,"score":0.30079999566078186},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3003999888896942},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2791999876499176},{"id":"https://openalex.org/C2778559676","wikidata":"https://www.wikidata.org/wiki/Q1334213","display_name":"Doppler radar","level":3,"score":0.27410000562667847},{"id":"https://openalex.org/C59584813","wikidata":"https://www.wikidata.org/wiki/Q1029234","display_name":"Continuous-wave radar","level":4,"score":0.265500009059906},{"id":"https://openalex.org/C2780522230","wikidata":"https://www.wikidata.org/wiki/Q1140419","display_name":"Ambiguity","level":2,"score":0.2612999975681305},{"id":"https://openalex.org/C167928553","wikidata":"https://www.wikidata.org/wiki/Q1376021","display_name":"Estimation theory","level":2,"score":0.2556000053882599},{"id":"https://openalex.org/C100102862","wikidata":"https://www.wikidata.org/wiki/Q2625855","display_name":"Bistatic radar","level":4,"score":0.2522999942302704}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/access.2025.3643750","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2025.3643750","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1109/access.2025.3643750","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2025.3643750","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G293748861","display_name":null,"funder_award_id":"6217011933","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5888105847","display_name":null,"funder_award_id":"251163","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":67,"referenced_works":["https://openalex.org/W615589970","https://openalex.org/W1584444527","https://openalex.org/W1603430629","https://openalex.org/W1968200270","https://openalex.org/W1970790521","https://openalex.org/W1986362571","https://openalex.org/W1988130218","https://openalex.org/W2013438974","https://openalex.org/W2062125287","https://openalex.org/W2066459155","https://openalex.org/W2082637600","https://openalex.org/W2098492730","https://openalex.org/W2105502962","https://openalex.org/W2106084579","https://openalex.org/W2106779652","https://openalex.org/W2107551105","https://openalex.org/W2112790040","https://openalex.org/W2118800758","https://openalex.org/W2119963163","https://openalex.org/W2132588596","https://openalex.org/W2149246019","https://openalex.org/W2159359905","https://openalex.org/W2165061660","https://openalex.org/W2165468651","https://openalex.org/W2165918462","https://openalex.org/W2169174365","https://openalex.org/W2195896080","https://openalex.org/W2405791786","https://openalex.org/W2528771714","https://openalex.org/W2560387686","https://openalex.org/W2615820837","https://openalex.org/W2626872000","https://openalex.org/W2790478857","https://openalex.org/W2807791318","https://openalex.org/W2888860102","https://openalex.org/W2891932229","https://openalex.org/W2900574948","https://openalex.org/W2913717565","https://openalex.org/W2945721566","https://openalex.org/W2950381474","https://openalex.org/W3012069045","https://openalex.org/W3016404565","https://openalex.org/W3017403157","https://openalex.org/W3048034530","https://openalex.org/W3089171931","https://openalex.org/W3092124059","https://openalex.org/W3092603992","https://openalex.org/W3123766383","https://openalex.org/W3160344654","https://openalex.org/W3188870776","https://openalex.org/W3200762376","https://openalex.org/W3204967532","https://openalex.org/W3208982697","https://openalex.org/W3215020108","https://openalex.org/W4286213799","https://openalex.org/W4294982779","https://openalex.org/W4312879161","https://openalex.org/W4318681842","https://openalex.org/W4319586054","https://openalex.org/W4322706749","https://openalex.org/W4324116477","https://openalex.org/W4360995453","https://openalex.org/W4388754419","https://openalex.org/W4390905633","https://openalex.org/W4399602345","https://openalex.org/W4411948600","https://openalex.org/W4412939489"],"related_works":[],"abstract_inverted_index":{"When":[0],"airborne":[1],"radar":[2,122],"detects":[3],"targets,":[4],"space-time":[5],"adaptive":[6],"processing":[7],"(STAP)":[8],"performs":[9,79],"a":[10,127],"vital":[11],"role":[12],"in":[13,151],"clutter":[14,19,63,116],"rejection.":[15],"As":[16,47],"is":[17,21,71,97,131],"known,":[18],"rejection":[20],"limited":[22],"by":[23],"range":[24],"ambiguity.":[25],"With":[26],"range-related":[27],"degrees-of-freedom,":[28],"frequency":[29],"diverse":[30],"array":[31],"(FDA)":[32],"has":[33],"been":[34],"validated":[35],"to":[36,40,56,73,99],"have":[37],"the":[38,48,58,77,90,95,106,115,121,135,144,148],"ability":[39],"address":[41],"this":[42,69,82,84],"issue,":[43],"and":[44,103,114,134],"FDA-STAP":[45],"flourishes.":[46],"DoFs":[49],"increase,":[50],"more":[51],"training":[52],"samples":[53],"are":[54,109,118],"necessitated":[55],"satisfy":[57,74],"RMB":[59],"rule":[60,70],"for":[61],"accurate":[62],"covariance":[64],"matrix":[65],"(CCM)":[66],"estimation.":[67],"Nonetheless,":[68],"hard":[72],"practically,":[75],"then":[76],"STAP":[78,136],"poorly.":[80],"To":[81],"end,":[83],"work":[85],"introduces":[86],"shrinkage":[87],"estimation":[88],"into":[89],"STAP,":[91],"developing":[92],"FDA-SA-STAP.":[93],"First,":[94],"eigen-decomposition":[96],"implemented":[98],"obtain":[100],"sample":[101],"eigenvalues":[102,108],"eigenvectors.":[104],"Then":[105],"noise":[107,112],"manipulated":[110],"as":[111],"power,":[113],"ones":[117],"adjusted":[119],"via":[120],"output":[123],"power":[124],"minimization.":[125],"Ultimately,":[126],"new":[128],"inverse":[129],"CCM":[130],"reliably":[132],"derived,":[133],"can":[137],"be":[138],"effectively":[139],"conducted.":[140],"Numerical":[141],"experiments":[142],"confirm":[143],"performance":[145],"advantages":[146],"of":[147],"proposed":[149],"method":[150],"different":[152],"circumstances.":[153]},"counts_by_year":[],"updated_date":"2025-12-23T23:11:35.936235","created_date":"2025-12-12T00:00:00"}