Open Access Research

Performance analysis for time-frequency MUSIC algorithm in presence of both additive noise and array calibration errors

Mohamed Khodja1*, Adel Belouchrani1 and Karim Abed-Meraim2

Author Affiliations

1 Electrical Engineering Department, Ecole Nationale Polytechnique, Algiers, Algeria

2 Télécom ParisTech, TSI, 75634, Paris Cedex 13, France

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EURASIP Journal on Advances in Signal Processing 2012, 2012:94  doi:10.1186/1687-6180-2012-94

Published: 30 April 2012

Abstract

This article deals with the application of Spatial Time-Frequency Distribution (STFD) to the direction finding problem using the Multiple Signal Classification (MUSIC)algorithm. A comparative performance analysis is performed for the method under consideration with respect to that using data covariance matrix when the received array signals are subject to calibration errors in a non-stationary environment. An unified analytical expression of the Direction Of Arrival (DOA) error estimation is derived for both methods. Numerical results show the effect of the parameters intervening in the derived expression on the algorithm performance. It is particularly observed that for low Signal to Noise Ratio (SNR) and high Signal to sensor Perturbation Ratio (SPR) the STFD method gives better performance, while for high SNR and for the same SPR both methods give similar performance.