Dissertation Defense Announcement for John T. Rogers II on 10/120/2023 at 3:30 PM

October 19, 2023

Dissertation Title: Neural Networks for Improved Signal Source Enumeration and Localization with Unsteered Antenna Arrays

When: 20 Oct 2023, 15:30

Where: Simrall 228
or Webex: https://msstate.webex.com/meet/jeb234

Candidate: John T. Rogers II

Degree: Doctor of Philosophy in Electrical and Computer Engineering

Committee Members: Dr. John Ball, Dr. Ali Gurbuz, Dr. Chaomin Luo, Dr. Mehmet Kurum

Abstract: Direction of Arrival estimation using unsteered antenna arrays, unlike mechanically scanned or phased arrays, requires complex algorithms which perform poorly with small arrays or without a large number of observations. These algorithms commonly compute the direction of arrival from the sample covariance matrix and require a prior estimate of the number of signal sources. Herein, artificial neural networks are proposed which demonstrate improved estimation of the number of signal sources, the true signal covariance matrix, and the direction of arrival. The proposed number of source estimation network demonstrates robust performance in the case of coherent signals where conventional methods fail. For covariance matrix estimation, four network architectures are assessed and the best performing architecture achieves a $20$ times improvement in performance over the sample covariance matrix. Additionally, this network can achieve comparable performance to the sample covariance matrix with $1/8th$ the amount of snapshots. For direction of arrival estimation, preliminary results are provided comparing six architectures which all demonstrate high levels of accuracy and demonstrate the benefits of progressively training artificial neural networks by training on a sequence of sub-problems and extending to the network to encapsulate the entire process.