Estimation of Doubly Spread Underwater Acoustic Channel via Gram-Schmidt Matching Pursuit

Fei Yun Wu, Kunde Yang, Tian Tian, Chunlong Huang, Yunchao Zhu, Feng Tong

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

3 Scopus citations

Abstract

The underwater acoustic channel (UAC) exhibits strongly time delay and Doppler (DD) spread especially when the UAC is rapidly time-varying. These dynamic factors result to a serious impact on communication performance such as Inter-Symbol Interference (ISI). Hence, estimation of complex amplitude, time delay and the Dopplers of the UAC becomes the key part in underwater acoustic communication and is hopeful for improving the performance of equalization. However, the estimation is challenged by multiple factors to be estimated in delay and Doppler dimensions. This study exploits the sparsity of the UAC and develops an estimator via using Gram-Schmidt to find orthogonal bases, which leads to the fast and orthogonal way to select the supports of the dictionaries. The support list of the dictionaries constructed by probe signal can be used for estimating the DD functions from a noisy received signal. Matching Pursuit (MP) and Least Square (LS) methods are used for comparisons. The effectiveness of the proposed method is verified by the experimental data.

Original languageEnglish
Title of host publicationOCEANS 2019 - Marseille, OCEANS Marseille 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728114507
DOIs
StatePublished - Jun 2019
Event2019 OCEANS - Marseille, OCEANS Marseille 2019 - Marseille, France
Duration: 17 Jun 201920 Jun 2019

Publication series

NameOCEANS 2019 - Marseille, OCEANS Marseille 2019
Volume2019-June

Conference

Conference2019 OCEANS - Marseille, OCEANS Marseille 2019
Country/TerritoryFrance
CityMarseille
Period17/06/1920/06/19

Keywords

  • Gram-Schmidt matching pursuit (GSMP)
  • matching pursuit (MP)
  • Time delay and Doppler domains
  • underwater acoustic channel (UAC)

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