Time difference of arrival estimation of speech source in a noisy and reverberant environment
Signal Processing - Content-based image and video retrieval
A new sound source location algorithm based on formant frequency for sound image localization
ICME '03 Proceedings of the 2003 International Conference on Multimedia and Expo - Volume 2
Source localization using a sparse representation framework to achieve superresolution
Multidimensional Systems and Signal Processing
IEEE Transactions on Signal Processing
Direction-of-arrival estimation using a mixed l2,0norm approximation
IEEE Transactions on Signal Processing
The generalized likelihood ratio test and the sparse representations approach
ICISP'10 Proceedings of the 4th international conference on Image and signal processing
Sparse representations for spatial prediction and texture refinement
Journal of Visual Communication and Image Representation
Bayesian compressive sensing as applied to directions-of-arrival estimation in planar arrays
Journal of Electrical and Computer Engineering - Special issue on Advances in Radar Technologies
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The problem of estimating the direction of arrivals (DOA) of narrowband sources impinging on a uniform circular array is considered. We present a method that uses as input the values of a small number of uniformly spaced beams and apply a model-fitting approach taking into account the statistical properties of the beams. The approach, which is called the "global matched filter" fits simultaneously to the observations all the elements needed to explain them. It chooses, among all the representations satisfying a constraint with a sensible physical interpretation, the one with minimal energy. The method drastically improves upon the conventional beamformer and has a performance comparable with the best high-resolution (HR) techniques. It further applies when the number of sources exceeds the number of sensors: a situation that cannot be handled by standard HR techniques.