Tracking and Inversion Using Midfrequency Signals in the Seabed Characterization Experiment

Zoi Heleni Michalopoulou, Peter Gerstoft, Diego Rios, William S. Hodgkiss

Research output: Contribution to journalArticlepeer-review

Abstract

Multipath arrivals are identified and extracted from midfrequency impulse responses at a vertical line array produced by a broadband source transmitting linearly frequency modulated pulses in the SBCEX 17 experiment. Arrival times are extracted from received data using particle filtering and smoothing. Specifically, sequential filtering is applied to the received time series at sixteen phones for the estimation of three paths generated by sound interacting with the propagation medium. This is followed up with a smoother that provides “crisp” arrival time probability densities. A peak-finding method is used to identify a fourth path. The estimated arrival times obtained by the process above are linked with a sound propagation model based on ray tracing and linearization for estimation of source location and water column depth and sound speed. An exhaustive search follows for inversion for sediment sound speed and thickness. Because the source is moving, receptions are available on a track and arrival time estimation and corresponding inversion are performed at every source location within the track. The unknown parameters are estimated sequentially with two approaches. Approach one is linearization using prior information from one location propagated to the next. Approach two relies on a second particle filter, capturing the dynamic evolution of parameters along the track. Both techniques lead to sediment property estimation. Results from the two methods agree, pointing to robustness in inversion when impulse responses and arrival times estimated from those are employed as input to the inverse problem.

Original languageEnglish (US)
JournalIEEE Journal of Oceanic Engineering
DOIs
StateAccepted/In press - 2021

All Science Journal Classification (ASJC) codes

  • Ocean Engineering
  • Mechanical Engineering
  • Electrical and Electronic Engineering

Keywords

  • Bayesian inversion
  • Data models
  • Estimation
  • geoacoustic inversion
  • linearization
  • Mathematical models
  • particle filter (PF)
  • Receivers
  • Sediments
  • Uncertainty
  • Water resources

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