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Tensor-based spatial smoothing (TB-SS) is a preprocessing technique for subspace-based parameter estimation of damped and undamped harmonics. In TB-SS, multichannel data is packed into a measurement tensor. We propose a tensor-based signal subspace estimation scheme that exploits the multidimensional invariance property exhibited by the highly structured measurement tensor. In the presence of noise,...
We propose a novel subspace-based 2-D damped harmonic retrieval algorithm that uses a single snapshot of data. The data is packed into a measurement tensor and spatial smoothing is applied to it to get a spatially smoothed tensor. We observe a structure inherent in the spatially smoothed tensor. This structure can be fully exploited by constructing multiple higher-order tensors from the spatially...
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