{"id":296,"date":"2026-08-08T21:19:30","date_gmt":"2026-08-09T02:19:30","guid":{"rendered":"https:\/\/research.ece.ncsu.edu\/impress\/?page_id=296"},"modified":"2026-08-08T21:19:30","modified_gmt":"2026-08-09T02:19:30","slug":"rf-shield","status":"publish","type":"page","link":"https:\/\/research.ece.ncsu.edu\/impress\/research\/rf-shield\/","title":{"rendered":"RF-SHIELD: AI-Driven RF Sensemaking"},"content":{"rendered":"\n<div class=\"wp-block-group has-background\" style=\"border-left-color:#CC0000;border-left-width:4px;background-color:#f7f8f9;margin-top:0px;margin-bottom:26px;padding-top:16px;padding-right:20px;padding-bottom:16px;padding-left:20px\"><div class=\"wp-block-group__inner-container is-layout-flow wp-block-group-is-layout-flow\">\n<p class=\"wp-block-paragraph\" style=\"font-size:15px\"><strong>Sponsor:<\/strong> Laboratory for Analytic Sciences (LAS), NC State University<\/p>\n\n\n\n<p class=\"wp-block-paragraph\" style=\"font-size:15px\"><strong>Role:<\/strong> Principal Investigator<\/p>\n\n\n\n<p class=\"wp-block-paragraph\" style=\"font-size:15px\"><strong>Period:<\/strong> January 2026 \u2013 December 2026<\/p>\n\n\n\n<p class=\"wp-block-paragraph\" style=\"font-size:15px\"><strong>Team:<\/strong> IMPRESS Lab researchers and Ph.D. students<\/p>\n<\/div><\/div>\n\n<h3 class=\"wp-block-heading has-text-color\" style=\"color:#CC0000\">Motivation<\/h3>\n\n<p class=\"wp-block-paragraph\">The RF environment is increasingly congested and increasingly difficult to interpret: many emitters, overlapping bands, short transmissions, and waveforms that were never catalogued. Analysts need systems that turn raw wideband RF observations into an understandable picture of what is present, what is unusual, and what deserves attention \u2014 with reasoning that a human can follow.<\/p>\n\n<h3 class=\"wp-block-heading has-text-color\" style=\"color:#CC0000\">Approach<\/h3>\n\n<p class=\"wp-block-paragraph\">RF-SHIELD develops an AI-driven RF sensemaking framework built on interpretable learning architectures and software-defined radio experimentation:<\/p>\n\n<ul class=\"wp-block-list\">\n<li><strong>Wideband detection and classification<\/strong> \u2014 detecting emissions and recognizing waveform and modulation types directly from complex-valued RF data.<\/li>\n\n<li><strong>Interpretable architectures<\/strong> \u2014 parameterized learnable filters (SincNet- and PLFNet-style) whose learned filters correspond to physically meaningful frequency responses, so classification decisions can be inspected rather than taken on trust.<\/li>\n\n<li><strong>Anomaly and threat detection<\/strong> \u2014 identifying emissions that do not match known classes, and characterizing them for further analysis.<\/li>\n\n<li><strong>SDR implementation<\/strong> \u2014 evaluation on recorded and live over-the-air data rather than synthetic signals alone.<\/li>\n<\/ul>\n\n<figure class=\"wp-block-image size-large\"><img loading=\"lazy\" decoding=\"async\" width=\"400\" height=\"249\" src=\"https:\/\/research.ece.ncsu.edu\/impress\/wp-content\/uploads\/sites\/43\/2026\/08\/lab-thrust3.jpg\" alt=\"Spectrum sensing and RF waveform classification\" class=\"wp-image-291\" srcset=\"https:\/\/research.ece.ncsu.edu\/impress\/wp-content\/uploads\/sites\/43\/2026\/08\/lab-thrust3.jpg 400w, https:\/\/research.ece.ncsu.edu\/impress\/wp-content\/uploads\/sites\/43\/2026\/08\/lab-thrust3-300x187.jpg 300w\" sizes=\"auto, (max-width: 400px) 100vw, 400px\" \/><\/figure>\n\n<h3 class=\"wp-block-heading has-text-color\" style=\"color:#CC0000\">Related work<\/h3>\n\n<ul class=\"wp-block-list\">\n<li><em>PLFNets: Interpretable Complex-Valued Parameterized Learnable Filters for Computationally Efficient RF Classification<\/em>, IEEE Transactions on Radar Systems, 2024.<\/li>\n\n<li><em>Learnable Gaussian Filter-Based Automatic RF Waveform Modulation Recognition<\/em>, IEEE Radar Conference, 2025.<\/li>\n\n<li><em>Automatic classification of radar and communication waveforms through interpretable deep learning<\/em>, SPIE, 2025.<\/li>\n<\/ul>\n","protected":false},"excerpt":{"rendered":"<p>Sponsor: Laboratory for Analytic Sciences (LAS), NC State University Role: Principal Investigator Period: January 2026 \u2013 December 2026 Team: IMPRESS Lab researchers and Ph.D. students&#8230;<\/p>\n","protected":false},"author":152,"featured_media":0,"parent":7,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"_acf_changed":false,"footnotes":""},"class_list":["post-296","page","type-page","status-publish","hentry"],"acf":[],"_links":{"self":[{"href":"https:\/\/research.ece.ncsu.edu\/impress\/wp-json\/wp\/v2\/pages\/296","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/research.ece.ncsu.edu\/impress\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/research.ece.ncsu.edu\/impress\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/research.ece.ncsu.edu\/impress\/wp-json\/wp\/v2\/users\/152"}],"replies":[{"embeddable":true,"href":"https:\/\/research.ece.ncsu.edu\/impress\/wp-json\/wp\/v2\/comments?post=296"}],"version-history":[{"count":1,"href":"https:\/\/research.ece.ncsu.edu\/impress\/wp-json\/wp\/v2\/pages\/296\/revisions"}],"predecessor-version":[{"id":357,"href":"https:\/\/research.ece.ncsu.edu\/impress\/wp-json\/wp\/v2\/pages\/296\/revisions\/357"}],"up":[{"embeddable":true,"href":"https:\/\/research.ece.ncsu.edu\/impress\/wp-json\/wp\/v2\/pages\/7"}],"wp:attachment":[{"href":"https:\/\/research.ece.ncsu.edu\/impress\/wp-json\/wp\/v2\/media?parent=296"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}