A Novel Subspace-Averaging Direction of Arrival Estimation Technique

Bin Muhammad, M., Li, M., Abbasi, Q. , Goh, C. and Imran, M. (2021) A Novel Subspace-Averaging Direction of Arrival Estimation Technique. In: 2021 IEEE 6th International Conference on Signal and Image Processing (ICSIP), Nanjing, China, 9-11 Jul 2021, pp. 744-748. ISBN 9781665439046 (doi: 10.1109/ICSIP52628.2021.9688940)

Abstract

This paper presents a preliminary study of a novel subspace-averaging direction of arrival estimation technique (SADE), which jointly utilizes both the noise and signal subspaces to estimate the direction of arrival (DOAs) instead of just the former in a wide range of Signal to Noise (SNR) scenarios. The work was carried out by exploiting the common noise subspace properties with a modified covariance matrix. To further reduce the computational load, this work employs a simple polynomial root solving technique to determine the DOAs. From the simulation results of varying snapshot values and under Additive White Gaussian Noise (AWGN), the SADE technique manages to attain 99.84% of the Cramer Rao Bound (CRB) at >15dB SNR. In addition, from the simulation of varying antenna array elements, when the number of elements is less than 8, the SADE technique performs with a Root Mean Squared Error (RMSE) of 9.5% of the true direction compared to 15.6% and 16.7% of root-MUSIC and ESPRIT respectively with the potential application such as in a low-cost intelligent transportation localization system that requires high DOA estimation accuracy without the need for high hardware costs.

• Item Type: Conference Proceedings
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Abbasi, Professor Qammer and Imran, Professor Muhammad and Bin Muhammad, Murdifi
• Authors: Bin Muhammad, M., Li, M., Abbasi, Q., Goh, C., and Imran, M.
• College/School: College of Science and Engineering > School of Engineering > Electronics and Nanoscale Engineering; College of Science and Engineering > School of Engineering > Systems Power and Energy
• ISBN: 9781665439046
• Published Online: 28 January 2022
• Copyright Holders: Copyright © 2021 IEEE
• Publisher Policy: Reproduced in accordance with the publisher copyright policy

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