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Performance Comparisons of Angle of Arrival Detection Techniques Using ULA

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Abstract

This paper studies the performance of angle of arrival algorithms for closely and widely separated signals. The study aims to examine algorithms behaviour when deployed to different scenarios. The investigated techniques include Bartlett beamformer, Capon beamformer, Multiple Signal Classification (MUSIC), Root-MUSIC, estimation of signal parameters via rotational invariant techniques (ESPRIT), and Weighted Subspace Fitting (WSF). The examined scenarios consider closely and widely angular separated signals, also, the effect of varying the number of antenna elements (N), the number of snapshots (K), and the noise power level (n) were studied. We generated MATLAB codes to simulate the algorithms, where the effect of changing one setting was taken individually, then the effect of changing more than one setting was considered. It was found that varying the number of antennas has a major impact on detection accuracy for all algorithms. Root-MUSIC and ESPRIT algorithms tend to have the best results in the investigated scenarios.

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Availability of Data and Materials

The data that support the findings of this study are available on request from the corresponding author.

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The author declares that they have no fund support on their research.

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Authors and Affiliations

  1. Faculty of Engineering, Jerash University, Jerash, Jordan

    Huthaifa Obeidat

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  1. Huthaifa Obeidat
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HO conceptualized the paper’s idea, conducted the simulations and analysed the data and edited the manuscript.

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Correspondence to Huthaifa Obeidat.

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Obeidat, H. Performance Comparisons of Angle of Arrival Detection Techniques Using ULA. Wireless Pers Commun 126, 3611–3623 (2022). https://doi.org/10.1007/s11277-022-09881-x

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  • DOI: https://doi.org/10.1007/s11277-022-09881-x

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