Sequential geoacoustic inversion and source tracking using Ensemble Kalman-particle filter

Hong Liu, Kunde Yang, Qiulong Yang, Yuanliang Ma, Chunlong Huang

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

Abstract

The estimation of geoacoustic parameters of such a varying field can be reformulated as a sequential filter track problem. Sequential Bayesian filtering is widely applied in ocean geoacoustic inversion such as ensemble Kalman filter and particle filter. We introduce the ensemble Kalman particle filter to a sequential geoacoustic inversion problem in shallow water. This filter combines the advantages of particle filter and ensemble Kalman filter so its ability of tracking dynamical geoacoustic parameters is improved.

Original languageEnglish
Title of host publication2020 Global Oceans 2020
Subtitle of host publicationSingapore - U.S. Gulf Coast
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728154466
DOIs
StatePublished - 5 Oct 2020
Event2020 Global Oceans: Singapore - U.S. Gulf Coast, OCEANS 2020 - Biloxi, United States
Duration: 5 Oct 202030 Oct 2020

Publication series

Name2020 Global Oceans 2020: Singapore - U.S. Gulf Coast

Conference

Conference2020 Global Oceans: Singapore - U.S. Gulf Coast, OCEANS 2020
Country/TerritoryUnited States
CityBiloxi
Period5/10/2030/10/20

Keywords

  • Geoacoustic inversion
  • Kalman filter
  • particle filter
  • shallow water

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