Julien Bonnel

Geoacoustic inversion in a dispersive waveguide using warping operators

This paper presents a single receiver geoacoustic inversion method adapted for low-frequency impulsive sources. It is applied to light bulb data collected during the Shallow Water 2006 experiment. The inversion is carried out by extracting dispersion curves from the received signal, and comparing them to simulated replicas. To achieve dispersion curve estimation in the time-frequency domain, modal separability is improved using a signal processing method called warping. The inversion scheme allows for a reliable estimation of the New Jersey Shelf sediment properties (compressional sound speed and density). It also provides an accurate estimation of the source/receiver range.

Estimation of modal group velocities with a single receiver for geoacoustic inversion in shallow water

Due to the expense associated with at-sea sensor deployments, a challenge in underwater acoustics has been to develop methods requiring a minimal number of sensors. This paper introduces an adaptive time-frequency signal processing method designed for application to a single source-receiver sensor pair. The method involves the application of conjugate time-frequency warping transforms to improve the SNR and resolution of the time-frequency distribution (TFD) of the measured field. Such refined knowledge of the TFD facilitates efforts to extract tomographic information about the propagation medium. Here the method is applied to the case of modal propagation in a shallow ocean range independent environment to extract a refined TFD. Given knowledge of the source-receiver separation, the refined TFD is used to extract the frequency dependent group velocities of the individual modal components. The extracted group velocities are then incorporated into a computationally light tomographic inversion method. Simulated and experimental results are discussed.

Single-receiver geoacoustic inversion using modal reversal

This paper introduces a single-receiver geoacoustic-inversion method based on dispersion analysis and adapted to low-frequency impulsive sources in shallow-water environments. In this context, most existing methods take advantage of the modal dispersion curves in the time-frequency domain. Inversion is usually performed by matching estimated dispersion curves with simulated replicas. The method proposed here is different. It considers the received modes in the frequency domain. The modes are transformed using an operator called modal reversal, which is parameterized using environmental parameters. When modal reversal is applied using parameters that match the real environment, dispersion is compensated for in all of the modes. In this case, the reversed modes are in phase and add up constructively, which is not the case when modal reversal is ill-parameterized. To use this phenomenon, a criterion that adds up the reversed modes has been defined. The geoacoustic inversion is finally performed by maximizing this criterion. The proposed method is benchmarked against simulated data, and it is applied to experimental data recorded during the Shallow Water 2006 experiment.

Bayesian geoacoustic inversion of single hydrophone light bulb data using warping dispersion analysis.

This paper presents geoacoustic inversion of a light bulb implosion recorded during the Shallow Water 2006 experiment. The source is low frequency and impulsive, the environment is shallow water, and the acoustic signal is recorded using a single receiver. In this context, propagation is described by modal theory, and inversion is carried out by matching modal dispersion curves in the time-frequency domain. Experimental dispersion curves are estimated using an advanced signal processing method called warping, allowing inversion to be carried out at a relatively short range (~/=7 km). Moreover, the inversion itself is performed using Bayesian methodology. This allows inference of the seabed structure from the data, including the number of seabed layers resolved, optimal estimates of the seabed parameters, and quantitative uncertainty estimates. Inversion results of the experimental data are in good agreement with both ground truth and estimates from other experimental data in the same region.

Modal depth function estimation using time-frequency analysis

Acoustic propagation in shallow water is characterized by a set of depth-dependent modes, the modal depth functions, which propagate in range according to their horizontal wavenumbers. For inversion purposes, modal depth function estimation in shallow water is an issue when the environment is not known. Classical methods that provide blind mode estimation rely on the singular value decomposition of the received field at different frequencies over a vertical array of transducers. These methods require that the vertical array spans the full water column. This is obviously a strong limitation for the application of such methods in an operational context. To overcome these shortcomings, this study proposes to replace the spatial diversity constraint by a frequency diversity condition, and thus considers the case of a field emanating from an impulsive source. Indeed, because of the discrete nature of the wavenumber spectrum and due to their dispersive behavior, the modes are separated in the time-frequency domain. This phenomenon enables the design of a modal filtering scheme for signals received on a single receiver. In the case of a vertical receiver array, the modal contributions can be isolated for each receiver even when using a partial water column spanning array. This method thus eliminates the receiving constraints of classical methods of modal depth function estimation, although it imposes the use of an impulsive source. The developed algorithm is benchmarked on numerical simulations and validated on laboratory experimental data recorded in an ultrasonic waveguide. Practical applications are also discussed.

Passive geoacoustic inversion with a single hydrophone using broadband ship noise

An inversion scheme is proposed, relying upon the inversion of the noise of a moving ship measured on a single distant hydrophone. The spectrogram of the measurements exhibits striations which depend on waveguide parameters. The periodic behavior of striations versus range are used to estimate the differences of radial wavenumber between couples of propagative modes at a given frequency. These wavenumber differences are stacked for several frequencies to form the relative dispersion curves. Such relative dispersion curves can be synthesized using a propagation model feeded with a bottom geoacoustic model. Inversion is performed by looking for the bottom properties that optimize the fit between measured and predicted relative dispersion curves. The inversion scheme is tested on simulated data. The conclusions are twofold: (1) a minimum 6 dB signal to noise ratio is required to obtained an unbiased estimate of compressional sound speed in the bottom with a 3 m s(-1) standard deviation; however, even with low signal to noise ratio, the estimation error remains bounded and (2) in the case of a multi-layer bottom, the scheme produces a single depth-average compressional sound speed. The inversion scheme is applied on experimental data. The results are fully consistent with a core sample measured around the receiving hydrophone.

Inversion of seabed attenuation using time-warping of close range data.

An inversion scheme based on time-warping is presented for estimating seabed sound attenuation from modal dispersion of close-range single-hydrophone data. The dispersion information is extracted directly from the warped signal spectrum. Seabed sound speed and density are inverted from the modal group velocity curves, and the attenuation is inverted from the normalized modal amplitudes. The method is applied to experimental data collected in the Yellow Sea of China during the winter of 2002. The inverted sound speed and density are consistent with the sand-silt-clay sediment at the site, and the attenuation is nonlinear over the frequency band from 125-500 Hz.

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.

Small bowel image classification using cross-co-occurrence matrices on wavelet domain

This paper presents a novel system to compute the automated classification of wireless capsule endoscope images. Classification is achieved by a classical statistical approach, but novel features are extracted from the wavelet domain and they contain both color and texture information. First, a shift-invariant discrete wavelet transform (SIDWT) is computed to ensure that the multiresolution feature extraction scheme is robust to shifts. The SIDWT expands the signal (in a shift-invariant way) over the basis functions which maximize information. Then cross-co-occurrence matrices of wavelet subbands are calculated and used to extract both texture and color information. Canonical discriminant analysis is utilized to reduce the feature space and then a simple 1D classifier with the leave one out method is used to automatically classify normal and abnormal small bowel images. A classification rate of 94.7% is achieved with a database of 75 images (41 normal and 34 abnormal cases). The high success rate could be attributed to the robust feature set which combines multiresolutional color and texture features, with shift, scale and semi-rotational invariance. This result is very promising and the method could be used in a computer-aided diagnosis system or a content-based image retrieval scheme.

Automatic and passive whale localization in shallow water using gunshots

This paper presents an automatic and passive localization algorithm for low frequency impulsive sources in shallow water. This algorithm is based on the normal mode theory which characterizes propagation in this configuration. It uses specific signal processing tools and time-frequency representations to automatically extract features of the propagation. Then, it uses the dispersive properties of the oceanic waveguide as an advantage to perform the localization. Only few hydrophones are needed and neither knowledge of the oceanic environment nor simulation of the propagation is required. The proposed method is successfully applied on North Atlantic Whale gunshots in the Bay of Fundy recorded with a network of three hydrophones.