Subspace perturbation bounds with an application to angle of arrival estimation using the MUSIC algorithm

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Delaosa, Connor and Pestana, Jennifer and Weiss, Stephan and Proudler, Ian (2020) Subspace perturbation bounds with an application to angle of arrival estimation using the MUSIC algorithm. In: International Conference on Sensor Signal Processing for Defence, 2020-09-15 - 2020-09-16. (https://doi.org/10.1109/SSPD47486.2020.9272125)

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Abstract

This paper explores how angle of arrival (AoA) estimation using the multiple signal classification (MUSIC) algorithm, is affected by estimation errors in space-time covariance matrix. In particular, we explore how this estimation error perturbs the signal-plus-noise and noise-only subspaces of this matrix, and how this subsequently affects the performance of MUSIC for AoA estimation. This subspace perturbation is shown to depend on the space-time covariance matrix itself, the sample size over which it is estimated, as well as the distance of the smallest signal-related eigenvalue to the noise floor. We link a bound of this perturbation to a bound on MUSIC performance, and demonstrate its utility for AoA estimation in simulations.

ORCID iDs

Delaosa, Connor, Pestana, Jennifer ORCID logoORCID: https://orcid.org/0000-0003-1527-3178, Weiss, Stephan ORCID logoORCID: https://orcid.org/0000-0002-3486-7206 and Proudler, Ian;
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