Surface shape reconstruction from phaseless scattered acoustic data using a random forest algorithm.

Recent studies have demonstrated that acoustic waves can be used to reconstruct the roughness profile of a rigid scattering surface. In particular, the use of multiple microphones placed above a rough surface as well as an analytical model based on the linearised Kirchhoff integral equations provides a sufficient base for the inversion algorithm to estimate surface geometrical properties. Prone to fail in the presence of high noise and measurement uncertainties, the analytical approach may not always be suitable in analysing measured scattered acoustic pressure. With the aim to improve the robustness of the surface reconstruction algorithms, here it is proposed to use a data-driven approach through the application of a random forest regression algorithm to reconstruct specific parameters of one-dimensional sinusoidal surfaces from airborne acoustic phase-removed pressure data. The data for the training set are synthetically generated through the application of the Kirchhoff integral in predicting scattered sound, and they are further verified with data produced from laboratory measurements. The surface parameters from the measurement sample were found to be recovered accurately for various receiver combinations and with a wide range of noise levels ranging from 0.1% to 30% of the average scattered acoustical pressure amplitude.

Doppler spectra of airborne ultrasound forward scattered by the rough surface of open channel turbulent water flows.

Experimental data are presented on the Doppler spectra of airborne ultrasound forward scattered by the rough dynamic surface of an open channel turbulent flow. The data are numerically interpreted based on a Kirchhoff approximation for a stationary random water surface roughness. The results show a clear link between the Doppler spectra and the characteristic spatial and temporal scales of the water surface. The decay of the Doppler spectra is proportional to the velocity of the flow near the surface. At higher Doppler frequencies the measurements show a less steep decrease of the Doppler spectra with the frequency compared to the numerical simulations. A semi-empirical equation for the spectrum of the surface elevation in open channel turbulent flows over a rough bed is provided. The results of this study suggest that the dynamic surface of open channel turbulent flows can be characterized remotely based on the Doppler spectra of forward scattered airborne ultrasound. The method does not require any equipment to be submerged in the flow and works remotely with a very high signal to noise ratio.

Doppler spectra of airborne sound backscattered by the free surface of a shallow turbulent water flow.

Measurements of the Doppler spectra of airborne ultrasound backscattered by the rough dynamic surface of a shallow turbulent flow are presented in this paper. The interpretation of the observed acoustic signal behavior is provided by means of a Monte Carlo simulation based on the Kirchhoff approximation and on a linear random-phase model of the water surface elevation. Results suggest that the main scattering mechanism is from capillary waves with small amplitude. Waves that travel at the same velocity of the flow, as well as dispersive waves that travel at a range of velocities, are detected, studied, and used in the acoustic Doppler analysis. The dispersive surface waves are not observed when the flow velocity is slow compared to their characteristic velocity. Relatively wide peaks in the experimental spectra also suggest the existence of nonlinear modulations of the short capillary waves, or their propagation in a wide range of directions. The variability of the Doppler spectra with the conditions of the flow can affect the accuracy of the flow velocity estimations based on backscattering Doppler. A set of different methods to estimate this velocity accurately and remotely at different ranges of flow conditions is suggested.