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A Method for Tracking the Time Evolution of Steady-State Evoked Potentials

A Method for Tracking the Time Evolution of Steady-State Evoked Potentials

Published on: May 25, 2019

A method for tracking time-evolving sound speed profiles using Kalman filters.

Jiamin Huang¹, Jianlong Li¹, Wen Xu¹

¹Department of Information Science and Electronic Engineering, Zhejiang University, Hangzhou, 310027, China zjuhjm@126.com, jlli@zju.edu.cn, wxu@zju.edu.cn.

The Journal of the Acoustical Society of America

|August 7, 2014

Summary

This summary is machine-generated.

This study introduces a weighted ensemble Kalman filter to track sound speed profiles, improving accuracy over standard methods. This weighted approach enhances particle filtering for acoustic applications with similar computational costs.

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Area of Science:

Ocean acoustics
Geophysical signal processing

Background:

Accurate sound speed profiles are crucial for underwater acoustic propagation modeling.
Traditional methods for tracking time-evolving sound speed profiles face challenges in dynamic ocean environments.

Purpose of the Study:

To develop and evaluate a novel weighted ensemble Kalman filter for enhanced tracking of time-evolving sound speed profiles.
To improve the accuracy and robustness of sound speed profile estimation in underwater acoustics.

Main Methods:

Implementation of a weighted ensemble Kalman filter algorithm.
Particle updating using ensemble Kalman filter procedures.
Particle resampling based on importance weights derived from geoacoustic inversion likelihood.
Utilizing Bartlett power objective functions for likelihood evaluation.

Main Results:

The proposed weighted ensemble Kalman filter demonstrates superior performance compared to the standard ensemble Kalman filter.
The method achieves improved tracking of sound speed profiles.
The enhanced accuracy is obtained with a computational load comparable to existing ensemble methods.

Conclusions:

The weighted ensemble Kalman filter offers a more effective approach for tracking dynamic sound speed profiles.
This method provides a valuable tool for acoustic propagation modeling and geoacoustic inversion.
The technique balances accuracy improvements with computational efficiency.