DATA error estimation in matched-field geoacoustic inversion

Authors

  • E. Dosso Stan School of Earth and Ocean Sciences, University of Victoria, Victoria, BC V8W 3P6, Canada
  • J. Wilmut Michael School of Earth and Ocean Sciences, University of Victoria, Victoria, BC V8W 3P6, Canada
  • Jan Dettmer School of Earth and Ocean Sciences, University of Victoria, Victoria, BC V8W 3P6, Canada

Keywords:

Algorithms, Amplitude modulation, Arrays, Data reduction, Frequencies, Gaussian noise (electronic), Inverse problems, Maximum likelihood estimation, Optimization, Parameter estimation, Sensors, Signal processing, Simulated annealing, Acoustic data, Error estimation, Geoacoustic inversion, Geoacoustic parameters

Abstract

The data error estimation in matched-field geoacoustic inversion was discussed. The matched-field inversion (MFI) is based on searching for the set of geoacoustic model parameters m that minimizes an objective function quantifying the misfit between measured and modeled acoustic fields. The objective function to be minimized was derived from the likelihood function corresponding to the assumed data uncertainty distribution. It is found that a hybrid optimization algorithm that combines local downhill simplex moves within a fast simulated annealing global search has proved highly effective for MFI.

Published

2004-09-01

How to Cite

1.
Stan ED, Michael JW, Dettmer J. DATA error estimation in matched-field geoacoustic inversion. Canadian Acoustics [Internet]. 2004Sep.1 [cited 2021Apr.12];32(3):192-3. Available from: https://jcaa.caa-aca.ca/index.php/jcaa/article/view/1693

Issue

Section

Proceedings of the Acoustics Week in Canada