Examenspresentation av Elin Ohlman

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