DOA estimation of closely-spaced and spectrally-overlapped sources using a STFT-based MUSIC algorithm |
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Affiliation: | 1. University of Montenegro, Electrical Engineering Department, Cetinjski put bb, Podgorica 81 000, Montenegro;2. Institute for Cutting Edge Information and Communication Technologies, D? ord?a Va?ingtona 66/354, Podgorica 81000, Montenegro;3. Mitsubishi Electric Research Laboratories (MERL), 201 Broadway, Cambridge, MA 02139, USA;4. University of Donja Gorica, Faculty for Information Systems and Technologies, Oktoih 1, Podgorica 81 000, Montenegro |
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Abstract: | The multiple signal classification (MUSIC) algorithm based on spatial time-frequency distribution (STFD) has been investigated for direction of arrival (DOA) estimation of closely-spaced sources. However, the limitations of the bilinear time-frequency based MUSIC (TF-MUSIC) algorithm lie in that it suffers from heavy implementation complexity, and its performance strongly depends on appropriate selection of auto-term location of the sources in time-frequency (TF) domain for the formulation of a group of STFD matrices, which is practically difficult especially when the sources are spectrally-overlapped. In order to relax these limitations, this paper aims to develop a novel DOA estimation algorithm. Specifically, we build a MUSIC algorithm based on spatial short-time Fourier transform (STFT), which effectively reduces implementation cost. More importantly, we propose an efficient method to precisely select single-source auto-term location for constructing the STFD matrices of each source. In addition to low complexity, the main advantage of the proposed STFT-MUSIC algorithm compared to some existing ones is that it can better deal with closely-spaced sources whose spectral contents are highly overlapped in TF domain. |
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Keywords: | DOA estimation MUSIC Closely-spaced sources Spectrally-overlapped sources Short-time Fourier transform |
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