We made that statement about noise really being a different convolution a while ago when we noticed that a spurious noise was really the instantiation of a different phenonema altogether. Cable and I looked into that radiation field and saw you could perform this deconvolution using advanced matrix factorizations ( see Webcam as a radiation sensor Part3 , Part 2, Part 1). Today, the good folks at UCSD use ambient noise for inversion purposes:

Compressive geoacoustic inversion using ambient noise by Caglar Yardim, Peter Gerstoft, William S. Hodgkiss and James Traer

Surface generated ambient noise can be used to infer sediment properties. Here, a passive geoacoustic inversion method that uses noise recorded by a drifting vertical array is adopted. The array is steered using beamforming to compute the noise arriving at the array from various directions. This information is used in two different ways: Coherently (cross-correlation of upward/downward propagating noise using a minimum variance distortionless response fathometer), and incoherently (bottom loss vs frequency and angle using a conventionalbeamformer) to obtain the bottom properties. Compressive sensing is used to invert for the number of sediment layer interfaces and their depths using coherent passive fathometry. Then the incoherent bottom loss estimate is used to refine the sediment thickness, sound speed,density, and attenuation values. Compressive sensing fathometry enables automatic determination of the number of interfaces. It also tightens the sediment thickness priors for the incoherent bottom loss inversion which reduces the search space. The method is demonstrated on drifting array data collected during the Boundary 2003 experiment.

of related interest: A unified theory of microseisms and hum by James Traer, Peter Gerstoft

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Please bring back full-content RSS feed. Thank you.

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