By the same authors

From the same journal

Multi-branch autocorrelation method for Doppler estimation in UWA channels

Research output: Contribution to journalArticle

Full text download(s)

Published copy (DOI)

Author(s)

Department/unit(s)

Publication details

JournalIEEE Journal of Oceanic Engineering
DateAccepted/In press - 4 Oct 2017
DateE-pub ahead of print - 1 Nov 2017
DatePublished (current) - Oct 2018
Issue number4
Volume43
Number of pages20
Pages (from-to)1-20
Early online date1/11/17
Original languageEnglish

Abstract

In underwater acoustic (UWA) communications, Doppler estimation is one of the major stages in a receiver. Two Doppler estimation methods are often used: cross-ambiguity function (CAF) method and single-branch autocorrelation (SBA) method. The former results in accurate estimation but with a high complexity, whereas the latter is less complicated but also less accurate. In this paper, we propose and investigate a multi-branch autocorrelation (MBA) Doppler estimation method. The proposed method can be used in communication systems with periodically transmitted pilot signals or repetitive data transmission. For comparison of the Doppler estimation methods, we investigate an OFDM communication system in multiple dynamic scenarios using the Waymark simulator, allowing virtual underwater acoustic signal transmission between moving transmitter and receiver. For the comparison, we also use the OFDM signals recorded in a sea trial. The comparison shows that the receiver with the proposed MBA Doppler estimation method outperforms the receiver with the SBA method and its detection performance is close to that of the receiver with the CAF method, but with a significantly lower complexity.

Bibliographical note

This is an author-produced version of the published paper. Uploaded in accordance with the publisher’s self-archiving policy. Further copying may not be permitted; contact the publisher for details

    Research areas

  • Ambiguity function, autocorrelation, Doppler estimation, OFDM, underwater acoustic communications.

Discover related content

Find related publications, people, projects, datasets and more using interactive charts.

View graph of relations