Empirical mode decomposition based denoising for high resolution direction of arrival estimation

Gültekin Ö., Erer I., Kaplan M.

17th European Signal Processing Conference, EUSIPCO 2009, Glasgow, England, 24 - 28 August 2009, pp.1983-1986 identifier

  • Publication Type: Conference Paper / Full Text
  • City: Glasgow
  • Country: England
  • Page Numbers: pp.1983-1986
  • Istanbul Technical University Affiliated: Yes


In this work, Empirical Mode Decomposition (EMD) is applied to the problem of Direction of Arrival (DoA) estimation as a preprocessing method. The preprocessing stage consists of separate denoising the rows of the array data matrix where each row corresponds to the output of a particular array sensor. The chosen denoising algorithm is an iterative interval-thresholding variant of EMD. After the denoising stage, MUSIC is applied to construct the EMD-enhanced spatial spectrum. The proposed EMD-based array denoising scheme is based on the principles of wavelet-thresholding, thus it is comparable to wavelet-based denoising of array matrix. The results show that, especially in low-SNR scenarios, the estimation performance of MUSIC is significantly enhanced when denoising is applied to array data matrix prior to DoA estimation stage. © EURASIP, 2009.