{"id":"https://openalex.org/W3008979300","doi":"https://doi.org/10.1109/tgrs.2020.2972060","title":"A Clutter Suppression Method Based on NSS-RPCA in Heterogeneous Environments for SAR-GMTI","display_name":"A Clutter Suppression Method Based on NSS-RPCA in Heterogeneous Environments for SAR-GMTI","publication_year":2020,"publication_date":"2020-02-21","ids":{"openalex":"https://openalex.org/W3008979300","doi":"https://doi.org/10.1109/tgrs.2020.2972060","mag":"3008979300"},"language":"en","primary_location":{"id":"doi:10.1109/tgrs.2020.2972060","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2020.2972060","pdf_url":null,"source":{"id":"https://openalex.org/S111326731","display_name":"IEEE Transactions on Geoscience and Remote Sensing","issn_l":"0196-2892","issn":["0196-2892","1558-0644"],"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 Transactions on Geoscience and Remote Sensing","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/A5016392085","display_name":"Yifan Guo","orcid":"https://orcid.org/0000-0003-4196-3244"},"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":"Yifan Guo","raw_affiliation_strings":["National Laboratory of Radar Signal Processing, Xidian University, Xi\u2019an, China","National Laboratory of Radar Signal Processing, Xidian University, Xi'an, China"],"affiliations":[{"raw_affiliation_string":"National Laboratory of Radar Signal Processing, Xidian University, Xi\u2019an, China","institution_ids":["https://openalex.org/I149594827"]},{"raw_affiliation_string":"National Laboratory of Radar Signal Processing, Xidian University, Xi'an, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5052210425","display_name":"Guisheng Liao","orcid":"https://orcid.org/0000-0002-5919-0713"},"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":"Guisheng Liao","raw_affiliation_strings":["National Laboratory of Radar Signal Processing, Xidian University, Xi\u2019an, China","National Laboratory of Radar Signal Processing, Xidian University, Xi'an, China"],"affiliations":[{"raw_affiliation_string":"National Laboratory of Radar Signal Processing, Xidian University, Xi\u2019an, China","institution_ids":["https://openalex.org/I149594827"]},{"raw_affiliation_string":"National Laboratory of Radar Signal Processing, Xidian University, Xi'an, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5108189755","display_name":"Jun Li","orcid":"https://orcid.org/0000-0001-6850-1555"},"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":"Jun Li","raw_affiliation_strings":["National Laboratory of Radar Signal Processing, Xidian University, Xi\u2019an, China","National Laboratory of Radar Signal Processing, Xidian University, Xi'an, China"],"affiliations":[{"raw_affiliation_string":"National Laboratory of Radar Signal Processing, Xidian University, Xi\u2019an, China","institution_ids":["https://openalex.org/I149594827"]},{"raw_affiliation_string":"National Laboratory of Radar Signal Processing, Xidian University, Xi'an, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5024106373","display_name":"Tong Gu","orcid":"https://orcid.org/0000-0003-1231-5766"},"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":"Tong Gu","raw_affiliation_strings":["National Laboratory of Radar Signal Processing, Xidian University, Xi\u2019an, China","National Laboratory of Radar Signal Processing, Xidian University, Xi'an, China"],"affiliations":[{"raw_affiliation_string":"National Laboratory of Radar Signal Processing, Xidian University, Xi\u2019an, China","institution_ids":["https://openalex.org/I149594827"]},{"raw_affiliation_string":"National Laboratory of Radar Signal Processing, Xidian University, Xi'an, China","institution_ids":["https://openalex.org/I149594827"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5016392085"],"corresponding_institution_ids":["https://openalex.org/I149594827"],"apc_list":null,"apc_paid":null,"fwci":6.558,"has_fulltext":false,"cited_by_count":28,"citation_normalized_percentile":{"value":0.96017732,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":99},"biblio":{"volume":"58","issue":"8","first_page":"5880","last_page":"5891"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11038","display_name":"Advanced SAR Imaging Techniques","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/T11038","display_name":"Advanced SAR Imaging Techniques","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/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9984999895095825,"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/T10801","display_name":"Synthetic Aperture Radar (SAR) Applications and Techniques","score":0.9972000122070312,"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":0.8545068502426147},{"id":"https://openalex.org/keywords/robust-principal-component-analysis","display_name":"Robust principal component analysis","score":0.8073408007621765},{"id":"https://openalex.org/keywords/residual","display_name":"Residual","score":0.6686288118362427},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6529989838600159},{"id":"https://openalex.org/keywords/synthetic-aperture-radar","display_name":"Synthetic aperture radar","score":0.6445428729057312},{"id":"https://openalex.org/keywords/covariance-matrix","display_name":"Covariance matrix","score":0.5538022518157959},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.527326762676239},{"id":"https://openalex.org/keywords/tensor","display_name":"Tensor (intrinsic definition)","score":0.5104300379753113},{"id":"https://openalex.org/keywords/principal-component-analysis","display_name":"Principal component analysis","score":0.48146000504493713},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.46703478693962097},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4626733958721161},{"id":"https://openalex.org/keywords/constant-false-alarm-rate","display_name":"Constant false alarm rate","score":0.4307596981525421},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.41770100593566895},{"id":"https://openalex.org/keywords/radar","display_name":"Radar","score":0.37509623169898987},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.210150808095932}],"concepts":[{"id":"https://openalex.org/C132094186","wikidata":"https://www.wikidata.org/wiki/Q641585","display_name":"Clutter","level":3,"score":0.8545068502426147},{"id":"https://openalex.org/C2777749129","wikidata":"https://www.wikidata.org/wiki/Q17148469","display_name":"Robust principal component analysis","level":3,"score":0.8073408007621765},{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.6686288118362427},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6529989838600159},{"id":"https://openalex.org/C87360688","wikidata":"https://www.wikidata.org/wiki/Q740686","display_name":"Synthetic aperture radar","level":2,"score":0.6445428729057312},{"id":"https://openalex.org/C185142706","wikidata":"https://www.wikidata.org/wiki/Q1134404","display_name":"Covariance matrix","level":2,"score":0.5538022518157959},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.527326762676239},{"id":"https://openalex.org/C155281189","wikidata":"https://www.wikidata.org/wiki/Q3518150","display_name":"Tensor (intrinsic definition)","level":2,"score":0.5104300379753113},{"id":"https://openalex.org/C27438332","wikidata":"https://www.wikidata.org/wiki/Q2873","display_name":"Principal component analysis","level":2,"score":0.48146000504493713},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.46703478693962097},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4626733958721161},{"id":"https://openalex.org/C77052588","wikidata":"https://www.wikidata.org/wiki/Q644307","display_name":"Constant false alarm rate","level":2,"score":0.4307596981525421},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.41770100593566895},{"id":"https://openalex.org/C554190296","wikidata":"https://www.wikidata.org/wiki/Q47528","display_name":"Radar","level":2,"score":0.37509623169898987},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.210150808095932},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tgrs.2020.2972060","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2020.2972060","pdf_url":null,"source":{"id":"https://openalex.org/S111326731","display_name":"IEEE Transactions on Geoscience and Remote Sensing","issn_l":"0196-2892","issn":["0196-2892","1558-0644"],"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 Transactions on Geoscience and Remote Sensing","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1725003993","display_name":null,"funder_award_id":"61621005","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8291095538","display_name":null,"funder_award_id":"61431016","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":35,"referenced_works":["https://openalex.org/W1504174073","https://openalex.org/W1511391727","https://openalex.org/W1513956161","https://openalex.org/W1560772759","https://openalex.org/W1562101002","https://openalex.org/W1924878616","https://openalex.org/W1978749115","https://openalex.org/W1982303641","https://openalex.org/W1999204714","https://openalex.org/W2024165284","https://openalex.org/W2055796721","https://openalex.org/W2085889589","https://openalex.org/W2097417130","https://openalex.org/W2099991189","https://openalex.org/W2103972604","https://openalex.org/W2118809607","https://openalex.org/W2122956087","https://openalex.org/W2126209902","https://openalex.org/W2132102860","https://openalex.org/W2134332047","https://openalex.org/W2143057771","https://openalex.org/W2145962650","https://openalex.org/W2149246019","https://openalex.org/W2156643866","https://openalex.org/W2156650489","https://openalex.org/W2170588123","https://openalex.org/W2171428861","https://openalex.org/W2195771339","https://openalex.org/W2550763917","https://openalex.org/W3099180803","https://openalex.org/W3099453716","https://openalex.org/W4229903650","https://openalex.org/W4292363360","https://openalex.org/W6630549410","https://openalex.org/W6675020458"],"related_works":["https://openalex.org/W2357365693","https://openalex.org/W2097772921","https://openalex.org/W2762654808","https://openalex.org/W2150496749","https://openalex.org/W2097746176","https://openalex.org/W2042378457","https://openalex.org/W3173283069","https://openalex.org/W2098454995","https://openalex.org/W4200549931","https://openalex.org/W1486190487"],"abstract_inverted_index":{"Clutter":[0],"background":[1,74],"suppression":[2],"is":[3,23,47,56,105,130,138],"a":[4,17,37,108],"critical":[5],"problem":[6,33],"in":[7,27,87],"synthetic":[8],"aperture":[9,168],"radar-ground":[10],"moving":[11],"target":[12,136],"indication":[13],"(SAR-GMTI).":[14],"In":[15,152],"general,":[16],"great":[18],"quantity":[19],"of":[20,34,71,131,157,185],"secondary":[21],"data":[22,61,181],"not":[24],"easily":[25],"acquired":[26],"heterogeneous":[28],"environments.":[29],"To":[30],"solve":[31],"the":[32,59,72,79,84,88,98,102,111,119,127,135,141,148,155,171,179,183,186],"clutter":[35,55,143],"suppression,":[36],"method":[38,86],"based":[39,177],"on":[40,178],"nonlocal":[41],"self-similarity-robust":[42],"principal":[43],"component":[44],"analysis":[45,176],"(NSS-RPCA)":[46],"proposed":[48,172,187],"for":[49],"airborne":[50],"SAR":[51],"systems.":[52],"First,":[53],"discrete":[54],"separated":[57],"from":[58,118],"echo":[60],"by":[62,97,124,147,170],"RPCA":[63],"after":[64],"range":[65],"pulse":[66],"compression.":[67],"Second,":[68],"similar":[69,99],"blocks":[70],"residual-clutter":[73,128],"are":[75,95],"extracted":[76],"to":[77],"overcome":[78],"training":[80],"sample":[81],"limitation":[82],"using":[83],"NSS":[85],"2-D":[89],"time":[90],"domain.":[91],"Third,":[92],"subcovariance":[93,103,121],"matrices":[94],"structured":[96],"blocks,":[100],"and":[101,134,175],"matrix":[104,114,122],"stacked":[106,120],"into":[107],"tensor.":[109],"Then,":[110],"subclutter":[112,149],"covariance":[113,150],"can":[115,144],"be":[116,145,164],"obtained":[117],"tensor":[123,129,137],"RPCA,":[125],"where":[126],"low":[132],"rank":[133],"sparse.":[139],"Finally,":[140],"residual":[142],"suppressed":[146],"matrix.":[151],"this":[153],"manner,":[154],"source":[156],"independent":[158],"identically":[159],"distributed":[160],"(IID)":[161],"samples":[162],"will":[163],"increased":[165],"significantly":[166],"without":[167],"loss":[169],"method.":[173,188],"Simulation":[174],"experimental":[180],"illustrate":[182],"effectiveness":[184]},"counts_by_year":[{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":7},{"year":2022,"cited_by_count":7},{"year":2021,"cited_by_count":5}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}