{"id":"https://openalex.org/W3135310702","doi":"https://doi.org/10.1109/access.2021.3064362","title":"Target Recognition of SAR Image Based on CN-GAN and CNN in Complex Environment","display_name":"Target Recognition of SAR Image Based on CN-GAN and CNN in Complex Environment","publication_year":2021,"publication_date":"2021-01-01","ids":{"openalex":"https://openalex.org/W3135310702","doi":"https://doi.org/10.1109/access.2021.3064362","mag":"3135310702"},"language":"en","primary_location":{"id":"doi:10.1109/access.2021.3064362","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2021.3064362","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.2021.3064362","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5077983641","display_name":"Cong Mao","orcid":"https://orcid.org/0000-0002-2446-3216"},"institutions":[{"id":"https://openalex.org/I927504317","display_name":"Nanchang Hangkong University","ror":"https://ror.org/0369pvp92","country_code":"CN","type":"education","lineage":["https://openalex.org/I927504317"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Cong Mao","raw_affiliation_strings":["School of Information Engineering, Nanchang Hangkong University, Nanchang, China","ORCiD"],"affiliations":[{"raw_affiliation_string":"School of Information Engineering, Nanchang Hangkong University, Nanchang, China","institution_ids":["https://openalex.org/I927504317"]},{"raw_affiliation_string":"ORCiD","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101667572","display_name":"Lizhen Huang","orcid":"https://orcid.org/0000-0003-2148-2902"},"institutions":[{"id":"https://openalex.org/I927504317","display_name":"Nanchang Hangkong University","ror":"https://ror.org/0369pvp92","country_code":"CN","type":"education","lineage":["https://openalex.org/I927504317"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lizhen Huang","raw_affiliation_strings":["School of Information Engineering, Nanchang Hangkong University, Nanchang, China"],"affiliations":[{"raw_affiliation_string":"School of Information Engineering, Nanchang Hangkong University, Nanchang, China","institution_ids":["https://openalex.org/I927504317"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5034634350","display_name":"Yongsheng Xiao","orcid":"https://orcid.org/0000-0001-7815-9431"},"institutions":[{"id":"https://openalex.org/I927504317","display_name":"Nanchang Hangkong University","ror":"https://ror.org/0369pvp92","country_code":"CN","type":"education","lineage":["https://openalex.org/I927504317"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yongsheng Xiao","raw_affiliation_strings":["School of Information Engineering, Nanchang Hangkong University, Nanchang, China","ORCiD"],"affiliations":[{"raw_affiliation_string":"School of Information Engineering, Nanchang Hangkong University, Nanchang, China","institution_ids":["https://openalex.org/I927504317"]},{"raw_affiliation_string":"ORCiD","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100554567","display_name":"Fengshou He","orcid":null},"institutions":[{"id":"https://openalex.org/I11838497","display_name":"Aviation Industry Corporation of China (China)","ror":"https://ror.org/02wq41p38","country_code":"CN","type":"company","lineage":["https://openalex.org/I11838497"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Fengshou He","raw_affiliation_strings":["Leihua Electronic Technology Research Institute, Aviation Industries of China, Wuxi, China"],"affiliations":[{"raw_affiliation_string":"Leihua Electronic Technology Research Institute, Aviation Industries of China, Wuxi, China","institution_ids":["https://openalex.org/I11838497"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101868150","display_name":"Yufan Liu","orcid":"https://orcid.org/0000-0002-7144-7665"},"institutions":[{"id":"https://openalex.org/I927504317","display_name":"Nanchang Hangkong University","ror":"https://ror.org/0369pvp92","country_code":"CN","type":"education","lineage":["https://openalex.org/I927504317"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yufan Liu","raw_affiliation_strings":["School of Information Engineering, Nanchang Hangkong University, Nanchang, China","ORCiD"],"affiliations":[{"raw_affiliation_string":"School of Information Engineering, Nanchang Hangkong University, Nanchang, China","institution_ids":["https://openalex.org/I927504317"]},{"raw_affiliation_string":"ORCiD","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5077983641"],"corresponding_institution_ids":["https://openalex.org/I927504317"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":38.303,"has_fulltext":false,"cited_by_count":44,"citation_normalized_percentile":{"value":0.99577561,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":99},"biblio":{"volume":"9","issue":null,"first_page":"39608","last_page":"39617"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11038","display_name":"Advanced SAR Imaging Techniques","score":0.9990000128746033,"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":0.9990000128746033,"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/T10688","display_name":"Image and Signal Denoising Methods","score":0.9886000156402588,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T13114","display_name":"Image Processing Techniques and Applications","score":0.9843999743461609,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"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/computer-science","display_name":"Computer science","score":0.778995931148529},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6942267417907715},{"id":"https://openalex.org/keywords/overfitting","display_name":"Overfitting","score":0.653844952583313},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5777198672294617},{"id":"https://openalex.org/keywords/synthetic-aperture-radar","display_name":"Synthetic aperture radar","score":0.5643566250801086},{"id":"https://openalex.org/keywords/clutter","display_name":"Clutter","score":0.5432054996490479},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5428156852722168},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5404935479164124},{"id":"https://openalex.org/keywords/data-set","display_name":"Data set","score":0.5300882458686829},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.4250290095806122},{"id":"https://openalex.org/keywords/speckle-noise","display_name":"Speckle noise","score":0.4114196002483368},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.3958943486213684},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.3775967061519623},{"id":"https://openalex.org/keywords/radar","display_name":"Radar","score":0.3020624816417694}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.778995931148529},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6942267417907715},{"id":"https://openalex.org/C22019652","wikidata":"https://www.wikidata.org/wiki/Q331309","display_name":"Overfitting","level":3,"score":0.653844952583313},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5777198672294617},{"id":"https://openalex.org/C87360688","wikidata":"https://www.wikidata.org/wiki/Q740686","display_name":"Synthetic aperture radar","level":2,"score":0.5643566250801086},{"id":"https://openalex.org/C132094186","wikidata":"https://www.wikidata.org/wiki/Q641585","display_name":"Clutter","level":3,"score":0.5432054996490479},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5428156852722168},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5404935479164124},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.5300882458686829},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.4250290095806122},{"id":"https://openalex.org/C180940675","wikidata":"https://www.wikidata.org/wiki/Q7575045","display_name":"Speckle noise","level":3,"score":0.4114196002483368},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.3958943486213684},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.3775967061519623},{"id":"https://openalex.org/C554190296","wikidata":"https://www.wikidata.org/wiki/Q47528","display_name":"Radar","level":2,"score":0.3020624816417694},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2021.3064362","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2021.3064362","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"},{"id":"pmh:oai:doaj.org/article:db6e3b6356824f498553a44ff6dc1424","is_oa":true,"landing_page_url":"https://doaj.org/article/db6e3b6356824f498553a44ff6dc1424","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-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 9, Pp 39608-39617 (2021)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2021.3064362","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2021.3064362","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":[{"display_name":"Peace, Justice and strong institutions","score":0.800000011920929,"id":"https://metadata.un.org/sdg/16"}],"awards":[{"id":"https://openalex.org/G2091460002","display_name":null,"funder_award_id":"61661035","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G2747130447","display_name":null,"funder_award_id":"20192BAB207001","funder_id":"https://openalex.org/F4320322665","funder_display_name":"Natural Science Foundation of Jiangxi Province"},{"id":"https://openalex.org/G3034438011","display_name":null,"funder_award_id":"201920056001","funder_id":"https://openalex.org/F4320329330","funder_display_name":"Aviation Science Fund"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320322665","display_name":"Natural Science Foundation of Jiangxi Province","ror":null},{"id":"https://openalex.org/F4320329330","display_name":"Aviation Science Fund","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":39,"referenced_works":["https://openalex.org/W127697324","https://openalex.org/W142575998","https://openalex.org/W1530224848","https://openalex.org/W1566144858","https://openalex.org/W1602107991","https://openalex.org/W2063870433","https://openalex.org/W2090563002","https://openalex.org/W2099471712","https://openalex.org/W2160815625","https://openalex.org/W2292481059","https://openalex.org/W2410591237","https://openalex.org/W2588453093","https://openalex.org/W2593414223","https://openalex.org/W2604403460","https://openalex.org/W2614504311","https://openalex.org/W2615263668","https://openalex.org/W2621042270","https://openalex.org/W2757678917","https://openalex.org/W2767966434","https://openalex.org/W2786355301","https://openalex.org/W2798737368","https://openalex.org/W2806263990","https://openalex.org/W2883863016","https://openalex.org/W2895222021","https://openalex.org/W2901459322","https://openalex.org/W2905439256","https://openalex.org/W2918405464","https://openalex.org/W2919115771","https://openalex.org/W2931068004","https://openalex.org/W2959574828","https://openalex.org/W2963073614","https://openalex.org/W2963583038","https://openalex.org/W2972724712","https://openalex.org/W2999775558","https://openalex.org/W3122003316","https://openalex.org/W4320013936","https://openalex.org/W6605120661","https://openalex.org/W6605852207","https://openalex.org/W6760037434"],"related_works":["https://openalex.org/W4362597605","https://openalex.org/W1574414179","https://openalex.org/W4297676672","https://openalex.org/W3009056573","https://openalex.org/W2100498883","https://openalex.org/W1974266560","https://openalex.org/W3171448127","https://openalex.org/W2601459726","https://openalex.org/W4386025691","https://openalex.org/W19246820"],"abstract_inverted_index":{"In":[0],"recent":[1],"years,":[2],"with":[3],"the":[4,10,26,40,51,57,106,111,134,138,142,158,164,172,185,190,197,202],"rapid":[5],"development":[6],"of":[7,12,25,42,66,98,110,137,144,166,183,205,215],"deep":[8],"learning,":[9],"research":[11],"radar":[13],"image":[14,37,68],"automatic":[15],"target":[16,52,63],"recognition":[17,53,64,186,203],"(ATR)":[18],"has":[19,156],"made":[20],"great":[21],"progress.":[22],"However,":[23],"because":[24],"complex":[27],"environments":[28],"and":[29,45,77,89,105,140,161,176,201],"special":[30],"imaging":[31],"principles,":[32],"Synthetic":[33],"Aperture":[34],"Radar":[35],"(SAR)":[36],"still":[38],"have":[39],"problems":[41,97],"sample":[43],"scarcity":[44],"strong":[46],"speckle":[47],"noise,":[48],"which":[49,113,130],"affects":[50],"performance.":[54],"To":[55],"solve":[56],"above":[58],"problems,":[59],"we":[60,121],"proposed":[61],"a":[62,123],"method":[65],"SAR":[67],"based":[69,188],"on":[70,189],"Constrained":[71],"Naive":[72],"Generative":[73,85],"Adversarial":[74,86],"Networks":[75,87],"(CN-GAN)":[76],"Convolutional":[78],"Neural":[79],"Network":[80],"(CNN).":[81],"Combining":[82],"Least":[83],"Squares":[84],"(LSGAN)":[88],"Image-to-Image":[90],"Translation":[91],"(Pix2Pix),":[92],"CN-GAN":[93,155,210],"can":[94,131],"overcome":[95],"these":[96],"low":[99],"Signal-to-Clutter-Noise":[100],"Ratio":[101],"(SCNR),":[102],"model":[103,139,145],"instability":[104],"excessive":[107],"freedom":[108],"degree":[109],"output,":[112],"are":[114],"produced":[115],"by":[116,180,209],"conventional":[117],"naive":[118],"GAN.":[119],"Besides,":[120],"adopted":[122],"shallow":[124],"network":[125],"structure":[126],"design":[127],"in":[128,150],"CNN,":[129],"effectively":[132],"improve":[133],"generalization":[135],"ability":[136],"avoid":[141],"problem":[143],"overfitting.":[146],"The":[147],"experimental":[148],"results":[149],"this":[151],"paper":[152],"demonstrate":[153],"that":[154,214],"achieved":[157],"data":[159,162,168,174,177,192,199,206,218],"generation":[160],"enhancement,":[163],"SCNR":[165],"generated":[167],"is":[169,194,211],"higher":[170,212],"than":[171,196,213],"origin":[173,198],"set":[175,193,207],"sets":[178],"gained":[179],"other":[181,216],"forms":[182],"GANs,":[184],"performance":[187],"extended":[191],"better":[195],"set,":[200],"rate":[204],"enhanced":[208],"common":[217],"enhancement":[219],"methods.":[220]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":6},{"year":2024,"cited_by_count":11},{"year":2023,"cited_by_count":15},{"year":2022,"cited_by_count":7},{"year":2021,"cited_by_count":4}],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2025-10-10T00:00:00"}
