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A Two-Step Deep Learning Approach for Denoising RF-Transmitted Images Under Jamming

Semester: Spring 2025


Presentation description

Our senior design clinic developed a system to reconstruct jammed RF signals using a two-step RF and image denoising approach. At the physical layer, we used signal processing techniques like carrier frequency offset correction and chirp-based synchronization to maintain integrity under jamming. Using Ettus B200 radios, we transmitted and received jammed images, denoising them with Wavenet and UNet Transformer models on an Orin Jetson, followed by a UNet CNN for full recovery

Presenter Name: Xiaowen Yuan
Presenter Name: John Cimmarusti, Connor Nuibe, Alfred Farias
Presentation Type: Oral
Presentation Format: In Person
College: Engineering
School / Department: Electrical and Computer Engineering
Research Mentor: Rong-Rong Chen
Time: 1:00 PM
Physical Location or Zoom link:

Room 323