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.

beamspace-ESPRIT

harmonic retrieval

Tensor

CANDECOMP/PARAFAC decomposition

Författare

Fuxi Wen

Chalmers, Elektroteknik, Kommunikation, Antenner och Optiska Nätverk

Hing Cheung So

City University of Hong Kong

Henk Wymeersch

Chalmers, Elektroteknik, Kommunikation, Antenner och Optiska Nätverk

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) (EC/H2020/700044), 2017-04-18 -- 2019-04-13.

Flerdimensionell koherentkommunikation med mikrofrekvenskammar

Vetenskapsrådet (VR) (2020-00453), 2020-12-01 -- 2026-11-30.

Ämneskategorier

Reglerteknik

Signalbehandling

Datorseende och robotik (autonoma system)

DOI

10.1109/ICASSP40776.2020.9053619

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2022-03-02