Ion Iturbe

Travel-time tomography in shallow water: Experimental demonstration at an ultrasonic scale

Acoustic tomography in a shallow ultrasonic waveguide is demonstrated at the laboratory scale between two source-receiver arrays. At a 1/1,000 scale, the waveguide represents a 1.1-km-long, 52-m-deep ocean acoustic channel in the kilohertz frequency range. Two coplanar arrays record the transfer matrix in the time domain of the waveguide between each pair of source-receiver transducers. A time-domain, double-beamforming algorithm is simultaneously performed on the source and receiver arrays that projects the multi-reflected acoustic echoes into an equivalent set of eigenrays, which are characterized by their travel times and their launch and arrival angles. Travel-time differences are measured for each eigenray every 0.1 s when a thermal plume is generated at a given location in the waveguide. Travel-time tomography inversion is then performed using two forward models based either on ray theory or on the diffraction-based sensitivity kernel. The spatially resolved range and depth inversion data confirm the feasibility of acoustic tomography in shallow water. Comparisons are made between inversion results at 1 and 3 MHz with the inversion procedure using ray theory or the finite-frequency approach. The influence of surface fluctuations at the air-water interface is shown and discussed in the framework of shallow-water ocean tomography.

Shallow-Water Acoustic Tomography Performed From a Double-Beamforming Algorithm: Simulation Results

Recent shallow-water experiments in sea channels have been performed using two vertical coplanar densely sampled source and receive arrays. Applying a double-beamforming algorithm on the two arrays both on synthetic numerical simulations and on experimental data sets, we extract efficiently source and receive angles as well as travel times for a large number of acoustic rays that propagate and bounce in the shallow-water waveguide. We then investigate how well sound-speed variations in the waveguide are reconstructed using a ray time-delay tomography based on a Bayesian inversion formulation. We introduce both data and model covariance matrices and we discuss on the synthetic numerical example how to choose the a priori information on the sound-speed covariance matrix. We attribute the partial sound-speed reconstruction to the ray-based tomography and we suggest that finite-frequency effects should be considered as the vertical and horizontal size of the Fresnel zone significantly spreads in the waveguide. Finally, the contribution of a different set of ray angles for tomography goal is also presented.

Travel-time sensitivity kernels versus diffraction patterns obtained through double beam-forming in shallow water

In recent years, the use of sensitivity kernels for tomographic purposes has been frequently discussed in the literature. Sensitivity kernels of different observables (e.g., amplitude, travel-time, and polarization for seismic waves) have been proposed, and relationships between adjoint formulation, time-reversal theory, and sensitivity kernels have been developed. In the present study, travel-time sensitivity kernels (TSKs) are derived for two source-receiver arrays in an acoustic waveguide. More precisely, the TSKs are combined with a double time-delay beam-forming algorithm performed on two source-receiver arrays to isolate and identify each eigenray of the multipath propagation between a source-receiver pair in the acoustic waveguide. A relationship is then obtained between TSKs and diffraction theory. It appears that the spatial shapes of TSKs are equivalent to the gradients of the combined direction patterns of the source and receiver arrays. In the finite-frequency regimes, the combination of TSKs and double beam-forming both simplifies the calculation of TSK and increases the domain of validity for ray theory in shallow-water ocean acoustic tomography.

Ocean acoustic tomography using a double‐beamforming algorithm

Since Munk and Wunsch proposed the basis for ocean acoustic tomography, many experiments have been performed to estimate sound speed fluctuations in the ocean, using ray identification and measurement of their travel times. However, technical limitations appeared such as the precision of the arrival time measurements or the number of ray arrivals that can be extracted from the signal. Recently, technical improvements allowed more complete experiments using two vertical arrays of sensors (source array and hydrophone array). In this configuration, the signals between each source and receiver are recorded which greatly improve the available information to identify the acoustic rays. One way to increase the number of rays in the tomography algorithm is to perform double‐beamforming on the source and receive arrays. With double‐beamforming, ray arrivals are separated by emission angle, reception angle and arrival time. Thus, we solve more ray arrivals than with a single beamforming or with a point‐to‐point app...

Shallow water tomography: Ray theory vs travel‐time sensitivity kernels.

In underwater acoustics, ray tomography is the classical method used to estimate velocity variations, but recently. Travel‐Time Sensitivity Kernels (TSK) approaches have been developed. In this paper, we deal with TSK for two source‐receive arrays in an acoustic waveguide for shallow water tomography. As a first step, we show that separation of the different raypaths is improved by using a recently proposed new array processing [time‐delay double beamforming (DBF) algorithm]. DBF consists of changing the 3‐D data space from source depth, receiver depth and time into a new 3‐D space related to ray propagation expressed by the beamformed variables, source angle, receive angle and time. As a consequence, each eigenray of the multipath propagation for a source‐receiver couple can be identified and separated through DBF. In this context of DBF, the TSK is no longer point‐to‐point as usual, but relies on all source‐receiver time series. Kernels are computed using the fact that the processed signal is a linear c...

An acoustic barrier based on amplitude variations of the ray paths and double beamforming

The objective of this work is to build an acoustic barrier to detect and localize a target between two vertical arrays of sensors. To perform this detection/localisation, we record the signal between each source (of the source array) and each reveiver (of the receiver array). Using these data, we extract the different ray paths between sources and receivers thanks to a new signal processing method: double beamforming. Then, we show that ray paths and their arrival times are not affected by a target in the medium but that ray amplitudes change. As a result, it is possible to use amplitude variation of the rays to find the target localisation. To validate these methods we perform ultrasonic experiments in a tank. These experiments are often used in underwater acoustics as they emulate shallow water waveguides: indeed, by multiplying the frequency by a factor x, distances are divided by the same factor. As acoustic and elastic propagation properties are not affected by this scaling down, it is possible to ac...