{"id":"https://openalex.org/W4285105135","doi":"https://doi.org/10.1109/tifs.2022.3170275","title":"A Practical Deceptive Jamming Method Based on Vulnerable Location Awareness Adversarial Attack for Radar HRRP Target Recognition","display_name":"A Practical Deceptive Jamming Method Based on Vulnerable Location Awareness Adversarial Attack for Radar HRRP Target Recognition","publication_year":2022,"publication_date":"2022-01-01","ids":{"openalex":"https://openalex.org/W4285105135","doi":"https://doi.org/10.1109/tifs.2022.3170275"},"language":"en","primary_location":{"id":"doi:10.1109/tifs.2022.3170275","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tifs.2022.3170275","pdf_url":null,"source":{"id":"https://openalex.org/S61310614","display_name":"IEEE Transactions on Information Forensics and Security","issn_l":"1556-6013","issn":["1556-6013","1556-6021"],"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 Information Forensics and Security","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/A5070576173","display_name":"Chuan Du","orcid":"https://orcid.org/0000-0003-4511-4653"},"institutions":[{"id":"https://openalex.org/I200845125","display_name":"Nanjing University of Information Science and Technology","ror":"https://ror.org/02y0rxk19","country_code":"CN","type":"education","lineage":["https://openalex.org/I200845125"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Chuan Du","raw_affiliation_strings":["School of Electronics and Information Engineering, Nanjing University of Information Science and Technology, Nanjing, China"],"affiliations":[{"raw_affiliation_string":"School of Electronics and Information Engineering, Nanjing University of Information Science and Technology, Nanjing, China","institution_ids":["https://openalex.org/I200845125"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100622056","display_name":"Yulai Cong","orcid":"https://orcid.org/0000-0003-2413-1163"},"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":"Yulai Cong","raw_affiliation_strings":["School of Electronics and Communication Engineering, Sun Yat-sen University, Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"School of Electronics and Communication Engineering, Sun Yat-sen University, Shenzhen, China","institution_ids":["https://openalex.org/I157773358"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100731331","display_name":"Lei Zhang","orcid":"https://orcid.org/0000-0003-1907-3640"},"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":"Lei Zhang","raw_affiliation_strings":["School of Electronics and Communication Engineering, Sun Yat-sen University, Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"School of Electronics and Communication Engineering, Sun Yat-sen University, Shenzhen, China","institution_ids":["https://openalex.org/I157773358"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5060633993","display_name":"Dandan Guo","orcid":"https://orcid.org/0000-0002-1329-8403"},"institutions":[{"id":"https://openalex.org/I4210116924","display_name":"Chinese University of Hong Kong, Shenzhen","ror":"https://ror.org/02d5ks197","country_code":"CN","type":"education","lineage":["https://openalex.org/I177725633","https://openalex.org/I180726961","https://openalex.org/I4210116924"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dandan Guo","raw_affiliation_strings":["Institute of Robotics and Intelligent Manufacturing, The Chinese University of Hong Kong, Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"Institute of Robotics and Intelligent Manufacturing, The Chinese University of Hong Kong, Shenzhen, China","institution_ids":["https://openalex.org/I4210116924"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5028340453","display_name":"Song Wei","orcid":"https://orcid.org/0000-0002-1335-1446"},"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":"Song Wei","raw_affiliation_strings":["School of Electronics and Communication Engineering, Sun Yat-sen University, Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"School of Electronics and Communication Engineering, Sun Yat-sen University, Shenzhen, China","institution_ids":["https://openalex.org/I157773358"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5070576173"],"corresponding_institution_ids":["https://openalex.org/I200845125"],"apc_list":null,"apc_paid":null,"fwci":2.7599,"has_fulltext":false,"cited_by_count":22,"citation_normalized_percentile":{"value":0.91525725,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":99},"biblio":{"volume":"17","issue":null,"first_page":"2410","last_page":"2424"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9987999796867371,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9987999796867371,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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":0.9961000084877014,"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/T10891","display_name":"Radar Systems and Signal Processing","score":0.9772999882698059,"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/jamming","display_name":"Jamming","score":0.8724838495254517},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8382151126861572},{"id":"https://openalex.org/keywords/radar-jamming-and-deception","display_name":"Radar jamming and deception","score":0.6761149168014526},{"id":"https://openalex.org/keywords/radar","display_name":"Radar","score":0.6438028812408447},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6080434918403625},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.47603774070739746},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.44686853885650635},{"id":"https://openalex.org/keywords/electronic-countermeasure","display_name":"Electronic countermeasure","score":0.4337451159954071},{"id":"https://openalex.org/keywords/adversarial-system","display_name":"Adversarial system","score":0.42549917101860046},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.42182719707489014},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.401614248752594},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3607128858566284},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.15307354927062988},{"id":"https://openalex.org/keywords/pulse-doppler-radar","display_name":"Pulse-Doppler radar","score":0.13022133708000183},{"id":"https://openalex.org/keywords/radar-imaging","display_name":"Radar imaging","score":0.12409773468971252}],"concepts":[{"id":"https://openalex.org/C2779079576","wikidata":"https://www.wikidata.org/wiki/Q17092823","display_name":"Jamming","level":2,"score":0.8724838495254517},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8382151126861572},{"id":"https://openalex.org/C176381164","wikidata":"https://www.wikidata.org/wiki/Q1486507","display_name":"Radar jamming and deception","level":5,"score":0.6761149168014526},{"id":"https://openalex.org/C554190296","wikidata":"https://www.wikidata.org/wiki/Q47528","display_name":"Radar","level":2,"score":0.6438028812408447},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6080434918403625},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.47603774070739746},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.44686853885650635},{"id":"https://openalex.org/C131426668","wikidata":"https://www.wikidata.org/wiki/Q849203","display_name":"Electronic countermeasure","level":3,"score":0.4337451159954071},{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.42549917101860046},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.42182719707489014},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.401614248752594},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3607128858566284},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.15307354927062988},{"id":"https://openalex.org/C139931591","wikidata":"https://www.wikidata.org/wiki/Q1029151","display_name":"Pulse-Doppler radar","level":4,"score":0.13022133708000183},{"id":"https://openalex.org/C10929652","wikidata":"https://www.wikidata.org/wiki/Q7279985","display_name":"Radar imaging","level":3,"score":0.12409773468971252},{"id":"https://openalex.org/C97355855","wikidata":"https://www.wikidata.org/wiki/Q11473","display_name":"Thermodynamics","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:10.1109/tifs.2022.3170275","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tifs.2022.3170275","pdf_url":null,"source":{"id":"https://openalex.org/S61310614","display_name":"IEEE Transactions on Information Forensics and Security","issn_l":"1556-6013","issn":["1556-6013","1556-6021"],"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 Information Forensics and Security","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Reduced inequalities","score":0.4300000071525574,"id":"https://metadata.un.org/sdg/10"}],"awards":[{"id":"https://openalex.org/G1591395953","display_name":null,"funder_award_id":"61771372","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G2293978782","display_name":null,"funder_award_id":"KQTD20190929172704911","funder_id":"https://openalex.org/F4320336569","funder_display_name":"Shenzhen Science and Technology Innovation Program"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320336569","display_name":"Shenzhen Science and Technology Innovation Program","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":46,"referenced_works":["https://openalex.org/W1595159159","https://openalex.org/W1673923490","https://openalex.org/W1974340448","https://openalex.org/W1991224261","https://openalex.org/W2021047654","https://openalex.org/W2118521282","https://openalex.org/W2133047848","https://openalex.org/W2156194072","https://openalex.org/W2158672843","https://openalex.org/W2165698076","https://openalex.org/W2180612164","https://openalex.org/W2243397390","https://openalex.org/W2317194222","https://openalex.org/W2338657408","https://openalex.org/W2344848374","https://openalex.org/W2534211090","https://openalex.org/W2607464629","https://openalex.org/W2762279682","https://openalex.org/W2765424254","https://openalex.org/W2773828237","https://openalex.org/W2791444548","https://openalex.org/W2798302089","https://openalex.org/W2909390529","https://openalex.org/W2920313172","https://openalex.org/W2958109694","https://openalex.org/W2963229629","https://openalex.org/W2963542245","https://openalex.org/W2963857521","https://openalex.org/W3005128058","https://openalex.org/W3013256492","https://openalex.org/W3023942469","https://openalex.org/W3035821888","https://openalex.org/W3090384423","https://openalex.org/W3100144085","https://openalex.org/W3103557498","https://openalex.org/W3122775479","https://openalex.org/W3127159478","https://openalex.org/W3129895333","https://openalex.org/W3130760752","https://openalex.org/W3140214783","https://openalex.org/W3161293751","https://openalex.org/W3163842339","https://openalex.org/W4293846201","https://openalex.org/W6637162671","https://openalex.org/W6640425456","https://openalex.org/W6738884980"],"related_works":["https://openalex.org/W2042728352","https://openalex.org/W2373607998","https://openalex.org/W3167002625","https://openalex.org/W3115621866","https://openalex.org/W2006572611","https://openalex.org/W2350696335","https://openalex.org/W3126373676","https://openalex.org/W2132849939","https://openalex.org/W2389502827","https://openalex.org/W4376647199"],"abstract_inverted_index":{"In":[0,205],"recent":[1,21],"years,":[2],"deep":[3],"neural":[4,219],"networks":[5],"are":[6,66,123],"increasingly":[7],"popular":[8],"in":[9,54,104],"the":[10,38,59,100,130,139,149,152,159,168,176,186,193,198,202,206,210,216,234],"field":[11],"of":[12,68,151,170,201],"radar":[13,49,131],"high-resolution":[14],"range":[15,102,118,195],"profiles":[16],"(HRRPs)":[17],"target":[18,133,141],"recognition.":[19],"Unfortunately,":[20],"researches":[22],"have":[23],"revealed":[24],"that":[25,88,98,233],"a":[26,92,238,245],"deep-learning":[27],"classifier":[28],"can":[29,128],"be":[30],"easily":[31],"fooled":[32],"by":[33,62],"adding":[34],"small":[35],"perturbations":[36,60],"to":[37,80,125,137,166,184,191,214],"input,":[39],"named":[40],"adversarial":[41,64],"attack.":[42],"This":[43],"provides":[44],"us":[45],"an":[46,105,178],"inspiration":[47],"for":[48,78],"deceptive":[50,94,249],"jamming":[51,84,95,111,121,172,203,250],"signal":[52,173],"generation":[53,96,174,251],"electronic":[55],"countermeasures":[56],"(ECMs).":[57],"However,":[58],"generated":[61],"these":[63,117],"attacks":[65],"usually":[67],"complex":[69],"envelopes":[70],"and":[71,108,127,197,242,247],"quite":[72],"low":[73],"power,":[74],"making":[75],"it":[76],"challenging":[77],"jammers":[79],"generate":[81,126],"such":[82],"actual":[83],"signals.":[85],"To":[86,147],"solve":[87],"issue,":[89],"we":[90,157,208],"propose":[91],"practical":[93,246],"method":[97],"learns":[99],"vulnerable":[101,194],"cells":[103,196],"HRRP":[106,230],"sample":[107],"injects":[109],"several":[110],"pulses":[112],"with":[113,144],"specific":[114,199],"amplitudes":[115,200],"into":[116],"cells.":[119],"Such":[120],"signals":[122],"easy":[124],"deceive":[129],"automatic":[132],"recognition":[134,153],"(RATR)":[135],"model":[136],"output":[138],"wrong":[140],"category":[142],"prediction":[143],"high":[145],"confidence.":[146],"avoid":[148],"requirement":[150],"network":[154],"structure":[155],"information,":[156],"leverage":[158],"differential":[160],"evolution":[161],"optimization":[162],"algorithm":[163],"(non-gradientbased).":[164],"Further,":[165],"provide":[167],"potential":[169],"real-time":[171],"during":[175],"test,":[177],"encoder":[179],"is":[180],"constructed":[181],"not":[182],"only":[183],"learn":[185],"separable":[187],"features":[188],"but":[189],"also":[190],"find":[192],"pulses.":[204],"experiments,":[207],"apply":[209],"proposed":[211,235],"attack":[212,240],"algorithms":[213,236],"fool":[215],"one-dimensional":[217],"convolutional":[218],"network-based":[220],"HRRPRATR":[221],"models.":[222],"The":[223],"extensive":[224],"experimental":[225],"results":[226],"on":[227],"measured":[228],"aircraft":[229],"dataset":[231],"prove":[232],"achieve":[237],"promising":[239],"performance":[241],"serve":[243],"as":[244],"fast":[248],"method.":[252]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":8},{"year":2024,"cited_by_count":6},{"year":2023,"cited_by_count":6}],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2025-10-10T00:00:00"}