A more efficient AOA method for 2D and 3D direction estimation with arbitrary antenna array geometry

Al-Sadoon, M. A. G., Abduljabbar, N. A., Ali, N. T., Asif, R., Zweid, A., Alhassan, H., Noras, J. M. and Abd-Alhameed, R. A. (2019) A more efficient AOA method for 2D and 3D direction estimation with arbitrary antenna array geometry. In: Broadband Communications, Networks, and Systems - 9th International EAI Conference, Broadnets 2018, Proceedings. Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST . Springer-Verlag Berlin Heidelberg, PRT, pp. 419-430. ISBN 9783030051945

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Direction of arrival (DOA) estimation is currently an active research topic in array signal processing applications. Thus, a more efficient method with better accuracy than the current subspace angle of arrival (AOA) methods is proposed in this paper. The proposed method is called subtracting signal subspace (SSS), which exploits the orthogonality between the signal subspace (SS) and the array manifold vector (AMV). A novel approach applied to the pseudospectrum extracts the correct peaks and removes the sidelobes perfectly. The principle working of the proposed algorithm is given and mathematical model derived. The computational burden of the new method is also presented and compared with other methods. The SSS algorithm is implemented with both linear and planar antenna arrays. An intensive Monte Carlo simulation is conducted and compared with other popular AOA methods to verify the effectiveness of the SSS algorithm.

Item Type: Book Section
Additional Information: Publisher Copyright: © ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2019.
Uncontrolled Keywords: computational burden,direction of arrival,sensor array,signal processing,signal subspace,wireless communication,computer networks and communications ,/dk/atira/pure/subjectarea/asjc/1700/1705
Faculty \ School: Faculty of Science > School of Computing Sciences
UEA Research Groups: Faculty of Science > Research Groups > Smart Emerging Technologies
Faculty of Science > Research Groups > Cyber Security Privacy and Trust Laboratory
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Depositing User: LivePure Connector
Date Deposited: 23 Aug 2022 13:30
Last Modified: 14 Mar 2023 08:38
URI: https://ueaeprints.uea.ac.uk/id/eprint/87569
DOI: 10.1007/978-3-030-05195-2_41

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