Title:
Signal Detection with a Digital Antenna Array using Machine Learning: Image Recognition Methods Applied for Joint Detection and Signal Parameter Estimation
Overview
- Date:Starts 5 June 2023, 11:00Ends 5 June 2023, 12:00
- Location:ZOOM, Password: 329033
- Language:Swedish and English
Examiner: Rob Maaskant
Supervisors: Eric Norgren, Alexander Karlsson
Opponent: Karl Hammar
Abstract:
Radars and radar warning receiver systems engage in a perpetual battle for superiority. Constant evolution drives the development of new methods, and recent advancements in machine learning and image recognition may serve as sources of inspiration. In this thesis, a ``You Only Look Once''-style neural network is designed to detect pulsed radar signals and estimate their angle of arrival, frequency, time of arrival, and pulse width. Employing a digital multi-channel uniform linear antenna array, a short-time Fourier transform is applied to the output from each antenna element. Afterward, beamforming is performed for various angles combining the spectrograms, producing a 3D image upon which image recognition is applied. We find that using simulated data this method works for detecting two sinusoidal signals, even in noisy environments.
Welcome!
Elin and Rob
- Professor, Communication, Antennas and Optical Networks, Electrical Engineering