Grégoire Le Touzé

Physics-Based Time-Frequency Representations for Underwater Acoustics: Power Class Utilization with Waveguide-Invariant Approximation

Time-frequency (T-F) analysis of signals propagated in dispersive environments or systems is a challenging problem. When considering dispersive waveguides, propagation can be described by modal theory. Propagated signals are usually multicomponent, and the group delay of each mode (i.e., each component) is nonlinear and varies with the mode number. Consequently, existing T-F representations (TFRs) covariant to group delay shifts (GDSs) are not naturally adapted to this context. To overcome this issue, one solution is to approximate the propagation using simple models for which the dispersion properties do not vary with the mode number. If the chosen model is both simple and robust to uncertainties about the waveguide, it can be used to define adapted TFRs, such as the power-class with a suitable power coefficient. This article focuses on a context where this methodology can be applied: low-frequency acoustic propagation in shallow water. In this case, the global oceanic dispersion can be summarized using a single scalar called the waveguide invariant. This parameter can be used to approximate the group delay of each mode with a power law. Consequently, it is possible to use power-class TFRs with a -based power coefficient. Their practical use is demonstrated on two experimental data sets: a man-made implosion used for underwater geoacoustic inversion, and a right-whale impulsive vocalization that can be used to localize the animal.

Double-Capon and double-MUSICAL for arrival separation and observable estimation in an acoustic waveguide

AbstractRecent developments in shallow water ocean acoustic tomography propose the use of an original configuration composed of two source-receiver vertical arrays and wideband sources. The recording space thus has three dimensions, with two spatial dimensions and the frequency dimension. Using this recording space, it is possible to build a three-dimensional (3D) estimation space that gives access to the three observables associated with the acoustic arrivals: the direction of departure, the direction of arrivals, and the time of arrival. The main interest of this 3D estimation space is its capability for the separation of acoustic arrivals that usually interfere in the recording space, due to multipath propagation. A 3D estimator called double beamforming has already been developed, although it has limited resolution. In this study, the new 3D high-resolution estimators of double Capon and double MUSICAL are proposed to achieve this task. The ocean acoustic tomography configuration allows a single recording realization to estimate the cross-spectral data matrix, which is necessary to build high-resolution estimators. 3D smoothing techniques are thus proposed to increase the rank of the matrix. The estimators developed are validated on real data recorded in an ultrasonic tank, and their detection performances are compared to existing 2D and 3D methods.

Underwater broadband source localization based on modal filtering and features extraction

Passive source localization is a crucial issue in underwater acoustics. In this paper, we focus on shallow water environment (0 to 400 m) and broadband Ultra-Low Frequency acoustic sources (1 to 100 Hz). In this configuration and at a long range, the acoustic propagation can be described by normal mode theory. The propagating signal breaks up into a series of depth-dependent modes. These modes carry information about the source position. Mode excitation factors and mode phases analysis allow, respectively, localization in depth and distance. We propose two different approaches to achieve the localization: multidimensional approach (using a horizontal array of hydrophones) based on frequency-wavenumber transform ( method) and monodimensional approach (using a single hydrophone) based on adapted spectral representation ( method). For both approaches, we propose first complete tools for modal filtering, and then depth and distance estimators. We show that adding mode sign and source spectrum informations improves considerably the localization performance in depth. The reference acoustic field needed for depth localization is simulated with the new realistic propagation modelMoctesuma. The feasibility of both approaches, and , are validated on data simulated in shallow water for different configurations. The performance of localization, in depth and distance, is very satisfactory.

Wavefield extraction using multi-channel chirplet decomposition.

In acoustical and seismic fields, wavefield extraction has always been a crucial issue to solve inverse problem. Depending on the experimental configuration, conventional methods of wavefield decomposition might no longer likely to hold. In this paper, an original approach is proposed based on a multichannel decomposition of the signal into a weighted sum of elementary functions known as chirplets. Each chirplet is described by physical parameters and the collection of chirplets makes up a large adaptable dictionary, so that a chirplet corresponds unambiguously to one wave component.

Mode characterization in shallow water using warping tools.

In underwater acoustics, shallow water is a complex and dispersive medium. For low frequencies, the propagation is described by normal mode theory. Modes are nonlinear structures overlapped in time, in frequency, and in time‐frequency domains. Advanced signal processing methods are needed to study them. This paper presents two different warping methods allowing modal separation and estimation of parameters of the modes. As these transformations are invertible, they also allow modal filtering. Thus, they are a good preprocessing tool for source localization or tomography. This is shown on simulations and real data. Warping is a transformation of a propagated signal and is based on an environment model. Here the environment is modeled with isovelocity or Pekeris waveguide. However, both methods are quite robust to mismatches with the real environment and can be used with minimal preliminary knowledge of the real environment. The first warping method is applied on the time domain. It transforms each mode int...