{"id":"https://openalex.org/W3012021401","doi":"https://doi.org/10.1109/camsap45676.2019.9022525","title":"Radar Waveform Recognition Using Fourier-Based Synchrosqueezing Transform and CNN","display_name":"Radar Waveform Recognition Using Fourier-Based Synchrosqueezing Transform and CNN","publication_year":2019,"publication_date":"2019-12-01","ids":{"openalex":"https://openalex.org/W3012021401","doi":"https://doi.org/10.1109/camsap45676.2019.9022525","mag":"3012021401"},"language":"en","primary_location":{"id":"doi:10.1109/camsap45676.2019.9022525","is_oa":false,"landing_page_url":"https://doi.org/10.1109/camsap45676.2019.9022525","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE 8th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP)","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://research.aalto.fi/en/publications/68b00776-9cc1-45c7-967f-4317406081c0","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5065104133","display_name":"Gyuyeol Kong","orcid":"https://orcid.org/0000-0002-6490-0281"},"institutions":[{"id":"https://openalex.org/I9927081","display_name":"Aalto University","ror":"https://ror.org/020hwjq30","country_code":"FI","type":"education","lineage":["https://openalex.org/I9927081"]}],"countries":["FI"],"is_corresponding":false,"raw_author_name":"Gyuyeol Kong","raw_affiliation_strings":["Department of Signal Processing and Acoustics, Aalto University, Finland"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Signal Processing and Acoustics, Aalto University, Finland","institution_ids":["https://openalex.org/I9927081"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5105267090","display_name":"Visa Koivunen","orcid":"https://orcid.org/0000-0003-1454-5928"},"institutions":[{"id":"https://openalex.org/I9927081","display_name":"Aalto University","ror":"https://ror.org/020hwjq30","country_code":"FI","type":"education","lineage":["https://openalex.org/I9927081"]}],"countries":["FI"],"is_corresponding":false,"raw_author_name":"Visa Koivunen","raw_affiliation_strings":["Department of Signal Processing and Acoustics, Aalto University, Finland"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Signal Processing and Acoustics, Aalto University, Finland","institution_ids":["https://openalex.org/I9927081"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I9927081"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":15,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"664","last_page":"668"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12131","display_name":"Wireless Signal Modulation Classification","score":0.9994000196456909,"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":0.9994000196456909,"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":0.9948999881744385,"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/T10220","display_name":"Machine Fault Diagnosis Techniques","score":0.992900013923645,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems 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/waveform","display_name":"Waveform","score":0.830574631690979},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.697677493095398},{"id":"https://openalex.org/keywords/radar","display_name":"Radar","score":0.6308621168136597},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5998427271842957},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5162539482116699},{"id":"https://openalex.org/keywords/time\u2013frequency-analysis","display_name":"Time\u2013frequency analysis","score":0.5134497880935669},{"id":"https://openalex.org/keywords/fourier-transform","display_name":"Fourier transform","score":0.49111005663871765},{"id":"https://openalex.org/keywords/automatic-target-recognition","display_name":"Automatic target recognition","score":0.46927610039711},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.46527573466300964},{"id":"https://openalex.org/keywords/signal","display_name":"SIGNAL (programming language)","score":0.46357256174087524},{"id":"https://openalex.org/keywords/polyphase-system","display_name":"Polyphase system","score":0.44408726692199707},{"id":"https://openalex.org/keywords/frequency-domain","display_name":"Frequency domain","score":0.42938053607940674},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.39662104845046997},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.2531506419181824},{"id":"https://openalex.org/keywords/electronic-engineering","display_name":"Electronic engineering","score":0.2098829448223114},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.20095935463905334},{"id":"https://openalex.org/keywords/synthetic-aperture-radar","display_name":"Synthetic aperture radar","score":0.19667217135429382},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.18086537718772888},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.14657220244407654}],"concepts":[{"id":"https://openalex.org/C197424946","wikidata":"https://www.wikidata.org/wiki/Q1165717","display_name":"Waveform","level":3,"score":0.830574631690979},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.697677493095398},{"id":"https://openalex.org/C554190296","wikidata":"https://www.wikidata.org/wiki/Q47528","display_name":"Radar","level":2,"score":0.6308621168136597},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5998427271842957},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5162539482116699},{"id":"https://openalex.org/C142433447","wikidata":"https://www.wikidata.org/wiki/Q7806653","display_name":"Time\u2013frequency analysis","level":3,"score":0.5134497880935669},{"id":"https://openalex.org/C102519508","wikidata":"https://www.wikidata.org/wiki/Q6520159","display_name":"Fourier transform","level":2,"score":0.49111005663871765},{"id":"https://openalex.org/C117623542","wikidata":"https://www.wikidata.org/wiki/Q621974","display_name":"Automatic target recognition","level":3,"score":0.46927610039711},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.46527573466300964},{"id":"https://openalex.org/C2779843651","wikidata":"https://www.wikidata.org/wiki/Q7390335","display_name":"SIGNAL (programming language)","level":2,"score":0.46357256174087524},{"id":"https://openalex.org/C96157337","wikidata":"https://www.wikidata.org/wiki/Q391639","display_name":"Polyphase system","level":2,"score":0.44408726692199707},{"id":"https://openalex.org/C19118579","wikidata":"https://www.wikidata.org/wiki/Q786423","display_name":"Frequency domain","level":2,"score":0.42938053607940674},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.39662104845046997},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.2531506419181824},{"id":"https://openalex.org/C24326235","wikidata":"https://www.wikidata.org/wiki/Q126095","display_name":"Electronic engineering","level":1,"score":0.2098829448223114},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.20095935463905334},{"id":"https://openalex.org/C87360688","wikidata":"https://www.wikidata.org/wiki/Q740686","display_name":"Synthetic aperture radar","level":2,"score":0.19667217135429382},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.18086537718772888},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.14657220244407654},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/camsap45676.2019.9022525","is_oa":false,"landing_page_url":"https://doi.org/10.1109/camsap45676.2019.9022525","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE 8th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP)","raw_type":"proceedings-article"},{"id":"pmh:oai:aaltodoc.aalto.fi:123456789/43875","is_oa":true,"landing_page_url":"https://research.aalto.fi/en/publications/68b00776-9cc1-45c7-967f-4317406081c0","pdf_url":null,"source":{"id":"https://openalex.org/S4306401662","display_name":"Aaltodoc (Aalto University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I9927081","host_organization_name":"Aalto University","host_organization_lineage":["https://openalex.org/I9927081"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"acceptedVersion"}],"best_oa_location":{"id":"pmh:oai:aaltodoc.aalto.fi:123456789/43875","is_oa":true,"landing_page_url":"https://research.aalto.fi/en/publications/68b00776-9cc1-45c7-967f-4317406081c0","pdf_url":null,"source":{"id":"https://openalex.org/S4306401662","display_name":"Aaltodoc (Aalto University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I9927081","host_organization_name":"Aalto University","host_organization_lineage":["https://openalex.org/I9927081"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"acceptedVersion"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":22,"referenced_works":["https://openalex.org/W1522301498","https://openalex.org/W1598868193","https://openalex.org/W1836465849","https://openalex.org/W2054878302","https://openalex.org/W2088869937","https://openalex.org/W2108948681","https://openalex.org/W2125312588","https://openalex.org/W2153816607","https://openalex.org/W2163630665","https://openalex.org/W2176412452","https://openalex.org/W2531162019","https://openalex.org/W2555378055","https://openalex.org/W2624887404","https://openalex.org/W2781731889","https://openalex.org/W2949117887","https://openalex.org/W2951488730","https://openalex.org/W2963285578","https://openalex.org/W2964121744","https://openalex.org/W4244753254","https://openalex.org/W6631190155","https://openalex.org/W6675995183","https://openalex.org/W6685562342"],"related_works":["https://openalex.org/W4243016812","https://openalex.org/W2792461516","https://openalex.org/W2363918075","https://openalex.org/W2025377125","https://openalex.org/W2128153108","https://openalex.org/W2024367938","https://openalex.org/W1947057263","https://openalex.org/W2355447608","https://openalex.org/W1980067354","https://openalex.org/W2033324903"],"abstract_inverted_index":{"In":[0],"this":[1],"paper":[2],"the":[3,97,100,107],"problem":[4],"of":[5,66],"recognizing":[6],"radar":[7,27],"waveforms":[8,28,109],"is":[9,13,47,76,83],"addressed.":[10],"Waveform":[11],"classification":[12],"needed":[14],"in":[15,32,57,69,105],"spectrum":[16],"sharing":[17],"and":[18,23,64],"radar-communications":[19],"coexistence,":[20],"cognitive":[21],"radars":[22],"signal":[24,46],"intelligence.":[25],"Different":[26],"exhibit":[29],"different":[30],"properties":[31,56],"time-frequency":[33,74],"domain.":[34],"We":[35],"propose":[36],"a":[37,79,86],"deep":[38],"learning":[39],"method":[40,92,104],"for":[41],"waveform":[42],"classification.":[43],"The":[44,72,90],"received":[45,70],"processed":[48],"with":[49],"Fourier":[50],"synchrosqueezing":[51],"transform":[52],"that":[53,82],"has":[54,93],"excellent":[55],"revealing":[58],"time-varying":[59],"behavior,":[60],"rate":[61],"of,":[62],"strength":[63],"number":[65],"oscillatory":[67],"components":[68],"signals.":[71],"resulting":[73],"description":[75],"represented":[77],"as":[78],"bivariate":[80],"image":[81],"fed":[84],"into":[85],"convolutional":[87],"neural":[88],"network.":[89],"proposed":[91],"superior":[94],"performance":[95],"over":[96],"widely":[98],"used":[99],"Choi-Williams":[101],"distribution":[102],"(CWD)":[103],"distinguishing":[106],"polyphase":[108],"even":[110],"at":[111],"low":[112],"signal-to-noise":[113],"ratio":[114],"regime.":[115]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":2}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}