HB-DTW: Hyperdimensional Bayesian Dynamic Time Warping for Non-uniform Doppler

Sijung Yang, Andrew C. Singer

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Acoustic signaling systems often suffer from severe distortions from motion induced Doppler. Therefore, estimation and compensation of such time warping have been considered indispensable blocks in various applications including underwater acoustic communications. However, conventional matched filtering based methods often fail to provide robust tracking of time warping trajectories, especially when non-uniform Doppler effects reside in multi-path arrivals separately. In this paper, we propose HB-DTW, a hyperdimensional generalization of standard dynamic time warping (DTW) algorithms, to precisely estimate non-uniform time varying Doppler in acoustic multipath channels. The proposed algorithm exploits a Bayesian approach to map multidimensional temporal scaling, while guaranteeing polynomial time complexity in the length of the signal. Simulation results on synthetic channels with non-uniform Doppler effects are demonstrated to evaluate the proposed method.

Original languageEnglish (US)
Title of host publication29th European Signal Processing Conference, EUSIPCO 2021 - Proceedings
PublisherEuropean Signal Processing Conference, EUSIPCO
Pages2020-2024
Number of pages5
ISBN (Electronic)9789082797060
DOIs
StatePublished - 2021
Event29th European Signal Processing Conference, EUSIPCO 2021 - Dublin, Ireland
Duration: Aug 23 2021Aug 27 2021

Publication series

NameEuropean Signal Processing Conference
Volume2021-August
ISSN (Print)2219-5491

Conference

Conference29th European Signal Processing Conference, EUSIPCO 2021
Country/TerritoryIreland
CityDublin
Period8/23/218/27/21

Keywords

  • Acoustic communications
  • Doppler estimation
  • Dynamic time warping

ASJC Scopus subject areas

  • Signal Processing
  • Electrical and Electronic Engineering

Fingerprint

Dive into the research topics of 'HB-DTW: Hyperdimensional Bayesian Dynamic Time Warping for Non-uniform Doppler'. Together they form a unique fingerprint.

Cite this