{"id":"https://openalex.org/W2781731889","doi":"https://doi.org/10.1109/access.2017.2788942","title":"Automatic LPI Radar Waveform Recognition Using CNN","display_name":"Automatic LPI Radar Waveform Recognition Using CNN","publication_year":2018,"publication_date":"2018-01-01","ids":{"openalex":"https://openalex.org/W2781731889","doi":"https://doi.org/10.1109/access.2017.2788942","mag":"2781731889"},"language":"en","primary_location":{"id":"doi:10.1109/access.2017.2788942","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2017.2788942","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":null,"license_id":null,"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.2017.2788942","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5073091471","display_name":"Seung-Hyun Kong","orcid":"https://orcid.org/0000-0002-4753-1998"},"institutions":[{"id":"https://openalex.org/I157485424","display_name":"Korea Advanced Institute of Science and Technology","ror":"https://ror.org/05apxxy63","country_code":"KR","type":"education","lineage":["https://openalex.org/I157485424"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"Seung-Hyun Kong","raw_affiliation_strings":["The CCS Graduate School of Green Transportation, Korea Advanced Institute of Science and Technology, Daejeon, South Korea"],"affiliations":[{"raw_affiliation_string":"The CCS Graduate School of Green Transportation, Korea Advanced Institute of Science and Technology, Daejeon, South Korea","institution_ids":["https://openalex.org/I157485424"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100406602","display_name":"Min-Jun Kim","orcid":"https://orcid.org/0000-0002-7345-0358"},"institutions":[{"id":"https://openalex.org/I157485424","display_name":"Korea Advanced Institute of Science and Technology","ror":"https://ror.org/05apxxy63","country_code":"KR","type":"education","lineage":["https://openalex.org/I157485424"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Minjun Kim","raw_affiliation_strings":["The CCS Graduate School of Green Transportation, Korea Advanced Institute of Science and Technology, Daejeon, South Korea"],"affiliations":[{"raw_affiliation_string":"The CCS Graduate School of Green Transportation, Korea Advanced Institute of Science and Technology, Daejeon, South Korea","institution_ids":["https://openalex.org/I157485424"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5039170333","display_name":"Linh Hoang","orcid":"https://orcid.org/0000-0003-3930-4522"},"institutions":[{"id":"https://openalex.org/I157485424","display_name":"Korea Advanced Institute of Science and Technology","ror":"https://ror.org/05apxxy63","country_code":"KR","type":"education","lineage":["https://openalex.org/I157485424"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Linh Manh Hoang","raw_affiliation_strings":["The CCS Graduate School of Green Transportation, Korea Advanced Institute of Science and Technology, Daejeon, South Korea"],"affiliations":[{"raw_affiliation_string":"The CCS Graduate School of Green Transportation, Korea Advanced Institute of Science and Technology, Daejeon, South Korea","institution_ids":["https://openalex.org/I157485424"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5110270969","display_name":"Eunhui Kim","orcid":null},"institutions":[{"id":"https://openalex.org/I157485424","display_name":"Korea Advanced Institute of Science and Technology","ror":"https://ror.org/05apxxy63","country_code":"KR","type":"education","lineage":["https://openalex.org/I157485424"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Eunhui Kim","raw_affiliation_strings":["The CCS Graduate School of Green Transportation, Korea Advanced Institute of Science and Technology, Daejeon, South Korea"],"affiliations":[{"raw_affiliation_string":"The CCS Graduate School of Green Transportation, Korea Advanced Institute of Science and Technology, Daejeon, South Korea","institution_ids":["https://openalex.org/I157485424"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5073091471"],"corresponding_institution_ids":["https://openalex.org/I157485424"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":11.8458,"has_fulltext":false,"cited_by_count":167,"citation_normalized_percentile":{"value":0.98697977,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":100},"biblio":{"volume":"6","issue":null,"first_page":"4207","last_page":"4219"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12131","display_name":"Wireless Signal Modulation Classification","score":0.9998000264167786,"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/T12131","display_name":"Wireless Signal Modulation Classification","score":0.9998000264167786,"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/T10891","display_name":"Radar Systems and Signal Processing","score":0.9962999820709229,"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/T11038","display_name":"Advanced SAR Imaging Techniques","score":0.9936000108718872,"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/computer-science","display_name":"Computer science","score":0.8311359882354736},{"id":"https://openalex.org/keywords/waveform","display_name":"Waveform","score":0.6611692905426025},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6077563762664795},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.600104808807373},{"id":"https://openalex.org/keywords/radar","display_name":"Radar","score":0.5928627252578735},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5320640206336975},{"id":"https://openalex.org/keywords/low-probability-of-intercept-radar","display_name":"Low probability of intercept radar","score":0.4607791006565094},{"id":"https://openalex.org/keywords/matched-filter","display_name":"Matched filter","score":0.44453179836273193},{"id":"https://openalex.org/keywords/automatic-target-recognition","display_name":"Automatic target recognition","score":0.4262782335281372},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4214211404323578},{"id":"https://openalex.org/keywords/sensitivity","display_name":"Sensitivity (control systems)","score":0.4122955799102783},{"id":"https://openalex.org/keywords/hyperparameter","display_name":"Hyperparameter","score":0.4116475582122803},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.3694257140159607},{"id":"https://openalex.org/keywords/radar-engineering-details","display_name":"Radar engineering details","score":0.24319756031036377},{"id":"https://openalex.org/keywords/electronic-engineering","display_name":"Electronic engineering","score":0.22857731580734253},{"id":"https://openalex.org/keywords/radar-imaging","display_name":"Radar imaging","score":0.20674294233322144},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.15724840760231018},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.15177026391029358},{"id":"https://openalex.org/keywords/synthetic-aperture-radar","display_name":"Synthetic aperture radar","score":0.10837781429290771},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.09878137707710266}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8311359882354736},{"id":"https://openalex.org/C197424946","wikidata":"https://www.wikidata.org/wiki/Q1165717","display_name":"Waveform","level":3,"score":0.6611692905426025},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6077563762664795},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.600104808807373},{"id":"https://openalex.org/C554190296","wikidata":"https://www.wikidata.org/wiki/Q47528","display_name":"Radar","level":2,"score":0.5928627252578735},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5320640206336975},{"id":"https://openalex.org/C147345108","wikidata":"https://www.wikidata.org/wiki/Q6693040","display_name":"Low probability of intercept radar","level":5,"score":0.4607791006565094},{"id":"https://openalex.org/C50151734","wikidata":"https://www.wikidata.org/wiki/Q1759577","display_name":"Matched filter","level":3,"score":0.44453179836273193},{"id":"https://openalex.org/C117623542","wikidata":"https://www.wikidata.org/wiki/Q621974","display_name":"Automatic target recognition","level":3,"score":0.4262782335281372},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4214211404323578},{"id":"https://openalex.org/C21200559","wikidata":"https://www.wikidata.org/wiki/Q7451068","display_name":"Sensitivity (control systems)","level":2,"score":0.4122955799102783},{"id":"https://openalex.org/C8642999","wikidata":"https://www.wikidata.org/wiki/Q4171168","display_name":"Hyperparameter","level":2,"score":0.4116475582122803},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.3694257140159607},{"id":"https://openalex.org/C134406370","wikidata":"https://www.wikidata.org/wiki/Q832005","display_name":"Radar engineering details","level":4,"score":0.24319756031036377},{"id":"https://openalex.org/C24326235","wikidata":"https://www.wikidata.org/wiki/Q126095","display_name":"Electronic engineering","level":1,"score":0.22857731580734253},{"id":"https://openalex.org/C10929652","wikidata":"https://www.wikidata.org/wiki/Q7279985","display_name":"Radar imaging","level":3,"score":0.20674294233322144},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.15724840760231018},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.15177026391029358},{"id":"https://openalex.org/C87360688","wikidata":"https://www.wikidata.org/wiki/Q740686","display_name":"Synthetic aperture radar","level":2,"score":0.10837781429290771},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.09878137707710266},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2017.2788942","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2017.2788942","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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:ffbc39c5d72a4d7bbae4347867855846","is_oa":true,"landing_page_url":"https://doaj.org/article/ffbc39c5d72a4d7bbae4347867855846","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 6, Pp 4207-4219 (2018)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2017.2788942","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2017.2788942","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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320321317","display_name":"Gwangju Institute of Science and Technology","ror":"https://ror.org/024kbgz78"},{"id":"https://openalex.org/F4320323103","display_name":"Agency for Defense Development","ror":"https://ror.org/05fhe0r85"},{"id":"https://openalex.org/F4320334874","display_name":"Defense Acquisition Program Administration","ror":"https://ror.org/04bjg9m96"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":30,"referenced_works":["https://openalex.org/W2594692","https://openalex.org/W1598868193","https://openalex.org/W1925346143","https://openalex.org/W1952160361","https://openalex.org/W2015861736","https://openalex.org/W2077520601","https://openalex.org/W2088869937","https://openalex.org/W2095705004","https://openalex.org/W2112796928","https://openalex.org/W2113524221","https://openalex.org/W2125312588","https://openalex.org/W2137356002","https://openalex.org/W2141125852","https://openalex.org/W2141128974","https://openalex.org/W2144930206","https://openalex.org/W2150391795","https://openalex.org/W2153816607","https://openalex.org/W2156163116","https://openalex.org/W2163605009","https://openalex.org/W2163922914","https://openalex.org/W2172174689","https://openalex.org/W2531162019","https://openalex.org/W2586095846","https://openalex.org/W2591880439","https://openalex.org/W2624887404","https://openalex.org/W2919115771","https://openalex.org/W2997791733","https://openalex.org/W4244753254","https://openalex.org/W6674330103","https://openalex.org/W6684191040"],"related_works":["https://openalex.org/W2140186469","https://openalex.org/W4390421286","https://openalex.org/W2163171661","https://openalex.org/W2079273826","https://openalex.org/W293646134","https://openalex.org/W2464278922","https://openalex.org/W2055319567","https://openalex.org/W2055640545","https://openalex.org/W2058410072","https://openalex.org/W2065831797"],"abstract_inverted_index":{"Detecting":[0],"and":[1,58,73,166],"classifying":[2],"the":[3,7,27,56,61,65,86,101,107,121,126,129,139,144,149,155,170],"modulation":[4],"scheme":[5],"of":[6,12,60,69,75,116,128],"intercepted":[8],"noisy":[9],"low":[10],"probability":[11],"intercept":[13,108],"(LPI)":[14],"radar":[15,33],"signals":[16],"in":[17,26,143,148],"real":[18],"time":[19],"is":[20,152],"a":[21,49,94,113],"necessary":[22],"survival":[23],"technique":[24,36,97],"required":[25,105],"electronic":[28],"warfare":[29],"systems.":[30],"Therefore,":[31],"LPI":[32],"waveform":[34],"recognition":[35,167],"(LWRT)":[37],"has":[38],"gained":[39],"an":[40],"increasing":[41],"attention":[42],"recently.":[43],"In":[44,90],"this":[45],"paper,":[46],"we":[47,92],"propose":[48,93],"convolutional":[50],"neural":[51],"network":[52],"(CNN)-based":[53],"LWRT,":[54],"where":[55],"input":[57,66],"hyperparameters":[59],"CNN,":[62],"such":[63,161],"as":[64,162],"size,":[67,72],"number":[68,74],"filters,":[70],"filter":[71],"neurons":[76],"are":[77],"designed":[78],"based":[79,137],"on":[80,138],"various":[81],"signal":[82,117],"conditions":[83,141],"to":[84,98,111,119,164],"guarantee":[85],"maximum":[87],"classification":[88],"performance.":[89],"addition,":[91],"sample":[95],"averaging":[96],"efficiently":[99],"reduce":[100],"large":[102,114],"computational":[103],"cost":[104],"when":[106],"receiver":[109],"needs":[110],"process":[112],"amount":[115],"samples":[118],"improve":[120],"detection":[122],"sensitivity.":[123],"We":[124],"demonstrate":[125],"performance":[127],"proposed":[130,156],"LWRT":[131,157],"with":[132],"numerous":[133],"Monte":[134],"Carlo":[135],"simulations":[136],"simulation":[140],"used":[142],"recent":[145,171],"LWRTs":[146],"introduced":[147],"literature.":[150],"It":[151],"testified":[153],"that":[154],"offers":[158],"significant":[159],"improvement,":[160],"robustness":[163],"noise":[165],"accuracy,":[168],"over":[169],"LWRTs.":[172]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":16},{"year":2024,"cited_by_count":22},{"year":2023,"cited_by_count":27},{"year":2022,"cited_by_count":29},{"year":2021,"cited_by_count":26},{"year":2020,"cited_by_count":20},{"year":2019,"cited_by_count":20},{"year":2018,"cited_by_count":4}],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2025-10-10T00:00:00"}