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Single Snapshot R-D Unitary Tensor-ESPRIT Using an Augmentation of the Tensor Order

Publication Type : Conference Paper

Publisher : 2009 3rd IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP)

Source : 2009 3rd IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP) (2009)

Keywords : Algebra, augmentation of the tensor order, Conferences, ESPRIT, HOSVD, MIMO, multidimensional signal processing, Multidimensional systems, multilinear algebra, Multiple signal classification, Music information retrieval, Parameter estimation, R higher-order tensors, R-D unitary tensor, R-dimensional undamped harmonics, single snapshot, Smoothing methods, spatially smoothed tensor, subspace-based parameter estimation, Tensile stress, Tensors, undamped harmonics

Campus : Bengaluru

School : School of Engineering

Department : Electrical and Electronics

Verified : No

Year : 2009

Abstract : Single snapshot R-D unitary tensor-ESPRIT using an augmentation of the tensor order (SS-U-TE-ATO) is a subspace-based parameter estimation technique for R-dimensional (R-D) undamped harmonics using a single snapshot of data. In SS-U-TE-ATO the measurement data is packed into a measurement tensor to which spatial smoothing is applied. We propose the construction of R higher-order tensors from the spatially smoothed tensor by exploiting the inherent structure of the spatially smoothed tensor. In the next step of SS-U-TE-ATO, R enhanced real-valued signal subspace estimates, one for each dimension, are obtained from the R complex-valued higher-order tensors. We show that SS-U-TE-ATO performs significantly better than unitary tensor-ESPRIT (U-TE) directly applied to the spatially smoothed tensor. Moreover, for each dimension, SS-U-TE-ATO is almost insensitive to changes in the number of sensors per subarray provided that the number of subarrays is greater than the number of sources. Thereby we avoid the problem of selecting the optimum subarray size for a given source configuration.

Cite this Research Publication : Arpita Thakre, Haardt, M., and Giridhar, K., “Single Snapshot R-D Unitary Tensor-ESPRIT Using an Augmentation of the Tensor Order”, in 2009 3rd IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP), 2009.

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