Abstract:
We present a method for ambient noise cross-correlation modelling and source inversion, which accounts for spatiospectral variability in noise source distributions. It is based on numerical wavefield simulations in 2-D acoustic media. The source power spectral density is parametrized by a sum of a small number of spatial source distributions, each with a corresponding frequency spectrum held fixed during the inversion. Algorithmically, this is an extension of our previous work which assumed spatially homogeneous source spectra. In this paper, we use it to study the impact of incorrectly estimating source spectra from observed data. This is done using synthetic tests involving sources with closely spaced frequency spectra. The tests demonstrate that when the spatial variability of sources is either partially or wholly unaccounted for, the recovery of true source locations is compromised.