The performance of music-based DOA in white noise with missing data

Author

Suryaprakash, Raj Tejas ; Nadakuditi, Raj Rao

Author_Institution

Dept. of Electr. Eng. & Comput. Sci., Univ. of Michigan, Ann Arbor, MI, USA

fYear

2012

fDate

5-8 Aug. 2012

Firstpage

800

Lastpage

803

Abstract

The Multiple Signal Classification (MUSIC) algorithm is popular choice for estimating the direction of arrival (DOA) of signals impinging on a sensor array. In this paper, we analyze the mean-squared error (MSE) performance of MUSIC algorithm in the white noise setting with partially observed, or missing, data. Using recent results from random matrix theory, we obtain an analytic expression for the MSE of the DOA estimate in the asymptotic regime and validate the theoretical predictions with simulations.

Keywords

array signal processing; direction-of-arrival estimation; mean square error methods; signal classification; white noise; MUSIC based DOA; direction of arrival estimation; mean squared error performance; missing data; multiple signal classification algorithm; sensor array; white noise; Arrays; Direction of arrival estimation; Estimation; Multiple signal classification; Signal processing algorithms; Signal to noise ratio; Vectors; DOA estimation; MUSIC; missing data; random matrix theory;

fLanguage

English

Publisher

ieee

Conference_Titel

Statistical Signal Processing Workshop (SSP), 2012 IEEE

Conference_Location

Ann Arbor, MI

ISSN

pending

Print_ISBN

978-1-4673-0182-4

Electronic_ISBN

pending

Type

conf

DOI

10.1109/SSP.2012.6319826

Filename

6319826