Improving the spectral resolution for closely spaced targets based on MUSIC algorithm
DOI: 10.1080/17415977.2012.749468
Title: Improving the spectral resolution for closely spaced targets based on MUSIC algorithm
Journal Title: Inverse Problems in Science and Engineering
Volume: Volume 21
Issue: Issue 7
Publication Date: October 2013
Start Page: 1219
End Page: 1238
Published online: 3 Oct 2013
ISSN: 1741-5977
Author: Majid Pourahmadia*, Mansor Nakhkashb & Ali Akbar Tadaionb
a Department of Electrical Engineering , Yazd Branch, Islamic Azad University , Yazd , Iran
b Department of Electrical Engineering , Yazd University , PO Box 89195-741, Yazd , Iran
Abstract: Multiple signal classification (MUSIC) is a high-resolution method in microwave imaging which is severely based on the number of singular values of a multistatic response matrix. However, the role of noise and multiple scattering is crucial to determine the true dimension of the signal subspace. In this article, we show that in the presence of multiple scattering between the targets, some singular values of the signal subspace will greatly be decreased which is a critical point when the noise is added to the system. In this case, these signal singular values will mix with the noise ones and the most popular MUSIC methods degrade and even fail to estimate closely spaced target locations. Here, we introduce a method to solve the ambiguity in determining the number of targets employing a pre-processing method, discrete stationary wavelet transform (DSWT). The DSWT is developed on the basis of features of the reflection coefficient between targets. The application of this algorithm to measurement data shows its superiority over another thresholding-based algorithm, empirical mode decomposition. The results indicate that DSWT+MUSIC yields accurate estimate of the target locations, even in the presence of considerable noise and multiple scattering in the received signal.
Accepted: 11 Nov 2012

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