Picture of athlete cycling

Open Access research with a real impact on health...

The Strathprints institutional repository is a digital archive of University of Strathclyde's Open Access research outputs. Strathprints provides access to thousands of Open Access research papers by Strathclyde researchers, including by researchers from the Physical Activity for Health Group based within the School of Psychological Sciences & Health. Research here seeks to better understand how and why physical activity improves health, gain a better understanding of the amount, intensity, and type of physical activity needed for health benefits, and evaluate the effect of interventions to promote physical activity.

Explore open research content by Physical Activity for Health...

An extension of the MUSIC algorithm to broadband scenarios using polynomial eigenvalue decomposition

Alrmah, Mohamed Abubaker and Weiss, Stephan and Lambotharan, Sangarapillai (2011) An extension of the MUSIC algorithm to broadband scenarios using polynomial eigenvalue decomposition. In: 19th European Signal Processing Conference, 2011-08-29 - 2011-09-02.

Full text not available in this repository. Request a copy from the Strathclyde author

Abstract

The multiple signal classification (MUSIC) algorithm for direction of arrival estimation is defined for narrowband scenarios. In this paper, a generalisation to the broadband case is presented, based on a description of broadband systems by polynomial space-time covariance matrices. A polynomial eigenvalue decomposition is used to determine the noiseonly subspace of the this matrix, which can be scanned by appropriately defined broadband steering vectors. Two broadband MUSIC algorithm versions are presented, which resolve either angle of arrival alone or in combination with the frequency range over which sources are active. Initial results for these approaches are presented and demonstrate a significant benefit over independent frequency bin processing using narrowband MUSIC.