Available at: https://digitalcommons.calpoly.edu/theses/2907
Date of Award
6-2024
Degree Name
MS in Electrical Engineering
Department/Program
Electrical Engineering
College
College of Engineering
Advisor
Payam Nayeri
Advisor Department
Electrical Engineering
Advisor College
College of Engineering
Abstract
Direction of Arrival (DOA) estimation with digital arrays under unknown Gaussian distributed element location perturbation has detrimental effects to the performance of traditional DOA estimation techniques. This work proposes an artificial intelligence (AI) approach as a solution to this problem. A Deep Convolutional Neural Network (DCNN) is proposed and experimentation into network parameters, classification networks, and how the DCNN is applied to the DOA problem are studied. It is shown that this AI based approach is successful in estimating the DOA with perturbed arrays where traditional approaches fail.