FPGA Hardware Implementation and Experimental Validation of Efficient DOA Estimation Algorithms

About this project

The aim of this research project is to develop efficient algorithms for direction of arrival (DOA) estimation of both non-coherent and coherent sources and implement these algorithms on a field programmable gate array (FPGA) target for real-time experimental validation.

Estimation of direction of arrival angles of impinging radio frequency (RF) signals is an active and important research area owing to immense practical applications in both civilian and military fields such as sonar and radar for localisation of source, multiple-input multiple-out (MIMO) systems, and beam steering/forming smart antenna arrays in mobile communication. The practical significance of the DOA estimation problem can be established only through real-time testing on actual hardware for validation of the estimation methods. While there are several algorithms reported in the literature for DOA estimation, only a few of these are suitable for hardware implementation due to higher complexity, resource requirements, and computation time. Singular value decomposition (SVD) or eigen value decomposition (EVD) based algorithms such as ESPRIT and MUSIC, are not suitable for hardware implementation. In contrast, algorithms such as those based on LU factorization, Cholesky and LDL decomposition, and QR decomposition have lower computational complexity, which makes them suitable for real-time hardware implementation.

Lead researcher

Professor Abdel-Hamid Soliman

Professor

Abdel-Hamid's expertise includes automation, including Smart Cities, Building automation, Energy management, Security, Safety and health applications.

Abdel-Hamid's profile

Collaborators

Wireless Communications & Signal Processing Research Lab, Prince Mohammad bin Fahd University, KSA.

Publications

UK University

StudentCrowd University Awards 2022

for Job Prospects

StudentCrowd University Awards 2022

for Student Satisfaction

Complete University Guide 2022

for Social Inclusion

The Times and The Sunday Times Good University Guide 2023

for Course Content

StudentCrowd University Awards 2022

of Research Impact is ‘Outstanding’ or ‘Very Considerable’

Research Excellence Framework 2021