FPGA Hardware Implementation of Computationally Efficient DOA Estimation of Coherent Signals

Hussain, Ahmed A., Tayem, Nizar and SOLIMAN, Abdel-Hamid (2021) FPGA Hardware Implementation of Computationally Efficient DOA Estimation of Coherent Signals. In: 2021 International Conference on Radar, Antenna, Microwave, Electronics, and Telecommunications (ICRAMET). IEEE, pp. 103-108. ISBN 9781665428170

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Abstract or description

DOA estimation of highly correlated or coherent signals involves some preprocessing steps to de-correlate the signals before DOA estimates are computed. This increases the computational complexity of the estimation algorithms further, rendering hardware implementation a challenging task. In this paper, we present the hardware implementation of a novel and computationally efficient DOA estimation algorithm for coherent sources based on applying forward/backward averaging to the signal space matrix to deal with the incident coherent signals. The proposed algorithm is implemented on a Xilinx FPGA using LabVIEW FPGA modules. Simulations results as well as FPGA resource utilization and computation speed are presented to validate the efficacy of the proposed method and the efficiency of hardware implementation.

Item Type:	Book Chapter, Section or Conference Proceeding
Additional Information:	© 2021 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Faculty:	School of Digital, Technologies and Arts > Engineering
Event Title:	2021 International Conference on Radar, Antenna, Microwave, Electronics, and Telecommunications (ICRAMET)
Event Location:	Online
Event Dates:	23-24 November 2021
Depositing User:	Abdel-Hamid SOLIMAN
Date Deposited:	03 Nov 2023 15:27
Last Modified:	22 Dec 2023 01:38
URI:	https://eprints.staffs.ac.uk/id/eprint/7586

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