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Related Experiment Video

Updated: May 2, 2026

Implementation of a Reference Interferometer for Nanodetection

Implementation of a Reference Interferometer for Nanodetection

Published on: April 26, 2014

Spatial filtering in ambient noise interferometry.

Olivier Carrière¹, Peter Gerstoft¹, William S Hodgkiss¹

¹Scripps Institution of Oceanography, University of California San Diego, La Jolla, California 92093-0238.

The Journal of the Acoustical Society of America

|March 11, 2014

Summary

This summary is machine-generated.

This study introduces matrix-based spatial filters to improve the extraction of the empirical Green's function from ocean noise cross-correlations. These filters effectively remove directional source biases and noise, enhancing seismic data analysis.

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Area of Science:

Geophysics
Seismology
Array Signal Processing

Background:

Empirical Green's function retrieval from noise cross-correlations is theoretically sound but practically challenging in oceanic environments due to non-diffuse noise conditions.
Directional sources in the ocean can introduce significant bias into the retrieved Green's function, limiting its accuracy for seismic imaging and monitoring.

Purpose of the Study:

To develop and validate matrix-based spatial filtering techniques for removing unwanted contributions in ambient noise cross-correlations.
To address the limitations of diffuse noise assumptions in oceanic seismic studies by mitigating directional source effects.
To enable robust passive seismic wavefield separation and noise rejection using array processing.

Main Methods:

Design and application of matrix-based spatial filters using both matrix least-squares with low-rank approximation and convex optimization approaches.
Development of filter design solutions tailored for linear and planar seismic arrays.
Testing filters on real-world ocean-bottom seismic data from a linear array and simulated data from a planar array.

Main Results:

Successfully attenuated discrete interferer contributions in real-data cross-correlations from a linear array.
Achieved passive upgoing/downgoing wavefield separation with planar arrays using simulated data.
Demonstrated efficient rejection of horizontally propagating noise in planar array simulations.
Investigated the influence of array size and frequency band on the performance of filtered cross-correlations.

Conclusions:

Matrix-based spatial filtering offers a robust method for improving empirical Green's function retrieval in realistic oceanic noise conditions.
These filtering techniques are effective in mitigating directional source biases and separating wavefields passively.
The developed methods enhance the reliability of seismic data analysis from ocean-based arrays.