Tensor Decomposition-based Beamspace Esprit Algorithm for Multidimensional Harmonic Retrieval
Paper in proceedings, 2020

Beamspace processing is an efficient and commonly used approach in harmonic retrieval (HR). In the beamspace, measurements are obtained by linearly transforming the sensing data, thereby achieving a compromise between estimation accuracy and system complexity. Meanwhile, the widespread use of multi-sensor technology in HR has highlighted the necessity to move from a matrix (two-way) to tensor (multi-way) analysis. In this paper, we propose a beamspace tensor-ESPRIT for multidimensional HR. In our algorithm, parameter estimation and association are achieved simultaneously.

harmonic retrieval

beamspace-ESPRIT

Tensor

CANDECOMP/PARAFAC decomposition

Author

Fuxi Wen

Chalmers, Electrical Engineering, Communication and Antenna Systems, Communication Systems

Hing Cheung So

City University of Hong Kong

Henk Wymeersch

Chalmers, Electrical Engineering, Communication and Antenna Systems, Communication Systems

ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings

15206149 (ISSN)

Vol. 2020-May 4572-4576 9053619

2020 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2020
Barcelona, Spain,

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Subject Categories

Control Engineering

Signal Processing

Computer Vision and Robotics (Autonomous Systems)

DOI

10.1109/ICASSP40776.2020.9053619

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3/8/2021 1