Tensor Decomposition-based Beamspace Esprit Algorithm for Multidimensional Harmonic Retrieval
Paper i proceeding, 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

Författare

Fuxi Wen

Chalmers, Elektroteknik, Kommunikations- och antennsystem, Kommunikationssystem

Hing Cheung So

City University of Hong Kong

Henk Wymeersch

Chalmers, Elektroteknik, Kommunikations- och antennsystem, Kommunikationssystem

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,

MassLOC

Europeiska kommissionen (EU), 2017-04-18 -- 2019-04-13.

Flerdimensionell koherentkommunikation med mikrofrekvenskammar

Vetenskapsrådet (VR), 2020-12-01 -- 2026-11-30.

Ämneskategorier

Reglerteknik

Signalbehandling

Datorseende och robotik (autonoma system)

DOI

10.1109/ICASSP40776.2020.9053619

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Senast uppdaterat

2021-03-08