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Tensor-Based Spatial Smoothing (TB-SS) Using Multiple Snapshots
2010
IEEE Transactions on Signal Processing
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, a tensor-based subspace estimate obtained via TB-SS is a better estimate of the desired signal
doi:10.1109/tsp.2010.2043141
fatcat:2tmvl2zqkvaudkjnb5dgqev7gy