Narrowband angle of arrival estimation exploiting graph topology and graph signals

Tools

Proudler, Ian K. and Stankovic, Vladimir and Weiss, Stephan; (2020) Narrowband angle of arrival estimation exploiting graph topology and graph signals. In: 2020 Sensor Signal Processing for Defence Conference (SSPD). IEEE, GBR. ISBN 9781728138114 (https://doi.org/10.1109/SSPD47486.2020.9272170)

[thumbnail of Proudler-etal-SSPD-2020-Narrowband-angle-of-arrival-estimation-exploiting-graph]
Preview
 Text. Filename: Proudler_etal_SSPD_2020_Narrowband_angle_of_arrival_estimation_exploiting_graph.pdf
Accepted Author Manuscript
Download (568kB)| Preview

Abstract

Based on recent results of applying graph signal processing (GSP) to narrowband angle of arrival estimation for uniform linear arrays, we generalise the analysis to the case of arrays with elements placed arbitrarily in three dimensional space. We comment on the selection of the adjacency matrix, analyse how this new approach compares to the multiple signal classification (MUSIC) algorithm, and provide an efficient implementation. We demonstrate that the GSP approach can perform as well as the MUSIC algorithm in terms of accuracy and computational cost. Simulations indicate that the proposed GSP approach avoids the severe performance degradation with which MUSIC is associated at low signal to noise ratios.

ORCID iDs

Proudler, Ian K., Stankovic, Vladimir ORCID logoORCID: https://orcid.org/0000-0002-1075-2420 and Weiss, Stephan ORCID logoORCID: https://orcid.org/0000-0002-3486-7206;
CORE (COnnecting REpositories)