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Article Dans Une Revue IEEE Transactions on Signal Processing Année : 2017

Improving DOA Estimation Algorithms using High-Resolution Quadratic Time-Frequency Distributions

Résumé

This paper addresses the problem of direction of arrival (DOA) estimation and blind source separation (BSS) for non-stationary signals in the underdetermined case. These two problems are strongly related to the mixing matrix estimation problem. To deal with the non-stationary characteristics of signals, this study uses high-resolution quadratic time-frequency distributions (TFDs) to reduce the cross-terms while keeping a good resolution for the construction of the spatial TFDs (STFDs). The main contributions of this paper are (1) the formulation of a statistical test for the noise thresholding step to improve robustness and avoid the use of empirical parameters; this test performs multisource selection of the time-frequency points where the signal of interest is present; (2) the use of an algorithm, based on image processing methods, which performs an auto-source selection for mixing matrix estimation. The paper presents results on simulated signals that demonstrate an improvement of 10 dB in terms of normalized mean square error for BSS and 7% in terms of relative error for DOA estimation over standard methods.
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Dates et versions

hal-01609986 , version 1 (04-10-2017)

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Samir Ouelha, Abdeldjalil Aissa El Bey, Boualem Boashash. Improving DOA Estimation Algorithms using High-Resolution Quadratic Time-Frequency Distributions. IEEE Transactions on Signal Processing, 2017, 65 (19), pp.5179 - 5190. ⟨10.1109/TSP.2017.2718974⟩. ⟨hal-01609986⟩
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