{"id":1793,"date":"2025-01-26T23:06:06","date_gmt":"2025-01-26T23:06:06","guid":{"rendered":"https:\/\/sbia.org.br\/lnlm\/?page_id=1793"},"modified":"2025-01-26T23:06:06","modified_gmt":"2025-01-26T23:06:06","slug":"vol23-no1-art2","status":"publish","type":"page","link":"https:\/\/sbia.org.br\/lnlm\/publicacoes\/vol23-no1\/vol23-no1-art2\/","title":{"rendered":"Symmetry Feature Estimation Over STFT Transform to Improve Radar Classification Based on the Wisard Weightless Neural Network"},"content":{"rendered":"<p>Rodrigo Moreira <a href=\"https:\/\/orcid.org\/0000-0001-8041-2379\"><img loading=\"lazy\" decoding=\"async\" class=\"alignnone size-full wp-image-1167\" src=\"https:\/\/sbia.org.br\/lnlm\/wp-content\/uploads\/sites\/4\/2020\/09\/orcid.jpg\" alt=\"orcid\" width=\"20\" height=\"20\" \/><\/a>, Jorge Pires <a href=\"https:\/\/orcid.org\/0000-0003-4336-1466\"><img loading=\"lazy\" decoding=\"async\" class=\"alignnone size-full wp-image-1167\" src=\"https:\/\/sbia.org.br\/lnlm\/wp-content\/uploads\/sites\/4\/2020\/09\/orcid.jpg\" alt=\"orcid\" width=\"20\" height=\"20\" \/><\/a>, &amp; Aline de Oliveira <a href=\"https:\/\/orcid.org\/0000-0002-7795-1010\"><img loading=\"lazy\" decoding=\"async\" class=\"alignnone size-full wp-image-1167\" src=\"https:\/\/sbia.org.br\/lnlm\/wp-content\/uploads\/sites\/4\/2020\/09\/orcid.jpg\" alt=\"orcid\" width=\"20\" height=\"20\" \/><\/a><\/p>\n<p><strong>Abstract:<\/strong> Automated early recognition of enemy radar emissions are essential for the survival of a warship. Radar signals intercepted by a passive digital Electronic Support Measure (ESM) receiver can be classified based on the type of intrapulse modulation. The modulation classification is typically based on features extracted from the preprocessed radar\u2019s signal. Low Probability of Intercept (LPI) radars can use phase or frequency modulated signals to make radar emissions difficult for the enemy to detect. This paper proposes the use of a new feature, the symmetry measured in a Time-Frequency (TF) matrix, to improve intrapulse radar modulation classification. The analysis of the symmetry in a STFT matrix is characterized by an image processing problem, where the matrix is interpreted as a grayscale image. This paper also proposes the use of Weightless Neural Network WiSARD in identifying symmetry patterns in the Short Time Fourier Transform (STFT) matrix, a characteristic present in signals with Barker and Polytime phase modulations and which can be used by classifiers to discriminate them from signals with other types of modulations such as polyphase modulations (P1, P2, P3, P4 and Frank), linear frequency modulation (LFM), and Non Linear Frequency Modulation.<\/p>\n<p><strong>Keywords:<\/strong>  WiSARD, classification, artificial intelligence, feature, time-frequency transform.<\/p>\n<p><strong>DOI code:<\/strong> <a href=\"http:\/\/dx.doi.org\/10.21528\/lnlm-vol23-no1-art2\">10.21528\/lnlm-vol23-no1-art2<\/a><\/p>\n<p><strong>PDF file:<\/strong> <a href=\"https:\/\/sbia.org.br\/lnlm\/wp-content\/uploads\/2025\/12\/vol23-no1-art2.pdf\">vol23-no1-art2.pdf<\/a><\/p>\n<p><strong>BibTex file:<\/strong> <a href=\"https:\/\/sbia.org.br\/lnlm\/wp-content\/uploads\/2025\/12\/vol23-no1-art2.bib\">vol23-no1-art2.bib<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Rodrigo Moreira , Jorge Pires , &amp; Aline de Oliveira Abstract: Automated early recognition of enemy radar emissions are essential for the survival of a warship. Radar signals intercepted by a passive digital Electronic Support Measure (ESM) receiver can be <a href=\"https:\/\/sbia.org.br\/lnlm\/publicacoes\/vol23-no1\/vol23-no1-art2\/\" class=\"read-more\">Read More &#8230;<\/a><\/p>\n","protected":false},"author":1,"featured_media":0,"parent":1784,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"class_list":["post-1793","page","type-page","status-publish","hentry"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v26.9 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>Symmetry Feature Estimation Over STFT Transform to Improve Radar Classification Based on the Wisard Weightless Neural Network - Learning and NonLinear Models<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/sbia.org.br\/lnlm\/publicacoes\/vol23-no1\/vol23-no1-art2\/\" \/>\n<meta property=\"og:locale\" content=\"pt_BR\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Symmetry Feature Estimation Over STFT Transform to Improve Radar Classification Based on the Wisard Weightless Neural Network - Learning and NonLinear Models\" \/>\n<meta property=\"og:description\" content=\"Rodrigo Moreira , Jorge Pires , &amp; Aline de Oliveira Abstract: Automated early recognition of enemy radar emissions are essential for the survival of a warship. Radar signals intercepted by a passive digital Electronic Support Measure (ESM) receiver can be Read More ...\" \/>\n<meta property=\"og:url\" content=\"https:\/\/sbia.org.br\/lnlm\/publicacoes\/vol23-no1\/vol23-no1-art2\/\" \/>\n<meta property=\"og:site_name\" content=\"Learning and NonLinear Models\" \/>\n<meta property=\"og:image\" content=\"https:\/\/sbia.org.br\/lnlm\/wp-content\/uploads\/sites\/4\/2020\/09\/orcid.jpg\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\/\/schema.org\",\"@graph\":[{\"@type\":\"WebPage\",\"@id\":\"https:\/\/sbia.org.br\/lnlm\/publicacoes\/vol23-no1\/vol23-no1-art2\/\",\"url\":\"https:\/\/sbia.org.br\/lnlm\/publicacoes\/vol23-no1\/vol23-no1-art2\/\",\"name\":\"Symmetry Feature Estimation Over STFT Transform to Improve Radar Classification Based on the Wisard Weightless Neural Network - Learning and NonLinear Models\",\"isPartOf\":{\"@id\":\"https:\/\/sbia.org.br\/lnlm\/#website\"},\"primaryImageOfPage\":{\"@id\":\"https:\/\/sbia.org.br\/lnlm\/publicacoes\/vol23-no1\/vol23-no1-art2\/#primaryimage\"},\"image\":{\"@id\":\"https:\/\/sbia.org.br\/lnlm\/publicacoes\/vol23-no1\/vol23-no1-art2\/#primaryimage\"},\"thumbnailUrl\":\"https:\/\/sbia.org.br\/lnlm\/wp-content\/uploads\/sites\/4\/2020\/09\/orcid.jpg\",\"datePublished\":\"2025-01-26T23:06:06+00:00\",\"breadcrumb\":{\"@id\":\"https:\/\/sbia.org.br\/lnlm\/publicacoes\/vol23-no1\/vol23-no1-art2\/#breadcrumb\"},\"inLanguage\":\"pt-BR\",\"potentialAction\":[{\"@type\":\"ReadAction\",\"target\":[\"https:\/\/sbia.org.br\/lnlm\/publicacoes\/vol23-no1\/vol23-no1-art2\/\"]}]},{\"@type\":\"ImageObject\",\"inLanguage\":\"pt-BR\",\"@id\":\"https:\/\/sbia.org.br\/lnlm\/publicacoes\/vol23-no1\/vol23-no1-art2\/#primaryimage\",\"url\":\"https:\/\/sbia.org.br\/lnlm\/wp-content\/uploads\/sites\/4\/2020\/09\/orcid.jpg\",\"contentUrl\":\"https:\/\/sbia.org.br\/lnlm\/wp-content\/uploads\/sites\/4\/2020\/09\/orcid.jpg\"},{\"@type\":\"BreadcrumbList\",\"@id\":\"https:\/\/sbia.org.br\/lnlm\/publicacoes\/vol23-no1\/vol23-no1-art2\/#breadcrumb\",\"itemListElement\":[{\"@type\":\"ListItem\",\"position\":1,\"name\":\"Browse issues\",\"item\":\"https:\/\/sbia.org.br\/lnlm\/publicacoes\/\"},{\"@type\":\"ListItem\",\"position\":2,\"name\":\"Learning &#038; Nonlinear Models &#8211; L&#038;NLM &#8211; Volume 23 &#8211; N\u00famero 1\",\"item\":\"https:\/\/sbia.org.br\/lnlm\/publicacoes\/vol23-no1\/\"},{\"@type\":\"ListItem\",\"position\":3,\"name\":\"Symmetry Feature Estimation Over STFT Transform to Improve Radar Classification Based on the Wisard Weightless Neural Network\"}]},{\"@type\":\"WebSite\",\"@id\":\"https:\/\/sbia.org.br\/lnlm\/#website\",\"url\":\"https:\/\/sbia.org.br\/lnlm\/\",\"name\":\"Learning and NonLinear Models\",\"description\":\"\",\"publisher\":{\"@id\":\"https:\/\/sbia.org.br\/lnlm\/#organization\"},\"potentialAction\":[{\"@type\":\"SearchAction\",\"target\":{\"@type\":\"EntryPoint\",\"urlTemplate\":\"https:\/\/sbia.org.br\/lnlm\/?s={search_term_string}\"},\"query-input\":{\"@type\":\"PropertyValueSpecification\",\"valueRequired\":true,\"valueName\":\"search_term_string\"}}],\"inLanguage\":\"pt-BR\"},{\"@type\":\"Organization\",\"@id\":\"https:\/\/sbia.org.br\/lnlm\/#organization\",\"name\":\"Learning and NonLinear Models\",\"url\":\"https:\/\/sbia.org.br\/lnlm\/\",\"logo\":{\"@type\":\"ImageObject\",\"inLanguage\":\"pt-BR\",\"@id\":\"https:\/\/sbia.org.br\/lnlm\/#\/schema\/logo\/image\/\",\"url\":\"https:\/\/sbia.org.br\/lnlm\/wp-content\/uploads\/2021\/07\/logo-lnlm.png\",\"contentUrl\":\"https:\/\/sbia.org.br\/lnlm\/wp-content\/uploads\/2021\/07\/logo-lnlm.png\",\"width\":398,\"height\":94,\"caption\":\"Learning and NonLinear Models\"},\"image\":{\"@id\":\"https:\/\/sbia.org.br\/lnlm\/#\/schema\/logo\/image\/\"}}]}<\/script>\n<!-- \/ Yoast SEO plugin. -->","yoast_head_json":{"title":"Symmetry Feature Estimation Over STFT Transform to Improve Radar Classification Based on the Wisard Weightless Neural Network - Learning and NonLinear Models","robots":{"index":"index","follow":"follow","max-snippet":"max-snippet:-1","max-image-preview":"max-image-preview:large","max-video-preview":"max-video-preview:-1"},"canonical":"https:\/\/sbia.org.br\/lnlm\/publicacoes\/vol23-no1\/vol23-no1-art2\/","og_locale":"pt_BR","og_type":"article","og_title":"Symmetry Feature Estimation Over STFT Transform to Improve Radar Classification Based on the Wisard Weightless Neural Network - Learning and NonLinear Models","og_description":"Rodrigo Moreira , Jorge Pires , &amp; Aline de Oliveira Abstract: Automated early recognition of enemy radar emissions are essential for the survival of a warship. 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