Olivier Carrière

Inversion for Time-Evolving Sound-Speed Field in a Shallow Ocean by Ensemble Kalman Filtering

In the context of the recent Maritime Rapid Environmental Assessment/Blue Planet 2007 sea trial (MREA/BP07), this paper presents a range-resolving tomography method based on ensemble Kalman filtering of full-field acoustic measurements, dedicated to the monitoring of environmental parameters in coastal waters. The inverse problem is formulated in a state-space form wherein the time-varying sound-speed field (SSF) is assumed to follow a random walk with known statistics and the acoustic measurements are a nonlinear function of the SSF and the bottom properties. The state-space form enables a straightforward implementation of a nonlinear Kalman filter, leading to a data assimilation problem. Surface measurements augment the measurement vector to constrain the range-dependent structure of the SSF. Realistic scenarios of vertical slice shallow-water tomography experiments are simulated with an oceanic model, based on the MREA/BP07 experiment. Prior geoacoustic inversion on the same location gives the bottom acoustic properties that are input to the propagation model. Simulation results show that the proposed scheme enables the continuous tracking of the range-dependent SSF parameters and their associated uncertainties assimilating new measurements each hour. It is shown that ensemble methods are required to properly manage the nonlinearity of the model. The problem of the sensitivity to the vertical array (VA) configuration is also addressed.

Sequential Bayesian geoacoustic inversion for mobile and compact source-receiver configuration

Geoacoustic characterization of wide areas through inversion requires easily deployable configurations including free-drifting platforms, underwater gliders and autonomous vehicles, typically performing repeated transmissions during their course. In this paper, the inverse problem is formulated as sequential Bayesian filtering to take advantage of repeated transmission measurements. Nonlinear Kalman filters implement a random-walk model for geometry and environment and an acoustic propagation code in the measurement model. Data from MREA/BP07 sea trials are tested consisting of multitone and frequency-modulated signals (bands: 0.25-0.8 and 0.8-1.6 kHz) received on a shallow vertical array of four hydrophones 5-m spaced drifting over 0.7-1.6 km range. Space- and time-coherent processing are applied to the respective signal types. Kalman filter outputs are compared to a sequence of global optimizations performed independently on each received signal. For both signal types, the sequential approach is more accurate but also more efficient. Due to frequency diversity, the processing of modulated signals produces a more stable tracking. Although an extended Kalman filter provides comparable estimates of the tracked parameters, the ensemble Kalman filter is necessary to properly assess uncertainty. In spite of mild range dependence and simplified bottom model, all tracked geoacoustic parameters are consistent with high-resolution seismic profiling, core logging P-wave velocity, and previous inversion results with fixed geometries.

Dynamic Estimation of the Sound-Speed Profile from Broadband Acoustic Measurements

Global search and more recently adjoint-based inversion methods used in ocean acoustics showed their effectiveness in the estimation of the sound-speed profile (SSP) in water columns of several environments. In the framework of the European Seas Observatory Network (ESONET) an essential part of the research and technology focuses on continuous and long term observations to characterize dynamic ocean processes and monitor the global state of the ocean. Therefore, the development of high performance integrated tools for acoustic inversion is one of the attractive components in this network. For the purpose of efficient data assimilation this paper investigates sequential methods that are able to update sound-speed profile parameters, typically the coefficients of empirical orthogonal functions (EOF), with respect to new incoming acoustic or hydrographic measurements and take into account the seafloor and sub-seafloor acoustic properties in a shallow water environment. A formulation using Kalman filters is suitable for a sequential treatment. This paper investigates the application of two different extensions of the Kalman filter, the extended Kalman filter and the more recent unscented Kalman filter for comparison.

Acoustic monitoring of the Ushant Front: a feasibility study

Oceanic modeling and prediction are highly dependent on the availability of satellite remote sensing and hydrographic in situ measurements to provide reliable and accurate results. In coastal environments the data assimilation is a difficult problem due to the lack of data, the strong coupling between state variables and forcing and the frequent model failures encountered in the modeling. In particular, the scarcity of satellite measurements due to cloud cover makes the operational data assimilation an hard task. Acoustic tomography data can provide valuable environmental informations to complete the standard data set, on temporal and spatial scales suitable to a regional circulation model. This work presents a feasibility test of acoustic data assimilation in a basic feature model of the Ushant thermal front, west off Brittany. The proposed scheme considers the regular measurements of full-field acoustic data on a vertical array of receivers that are assimilated in the feature front model to continuously track time-evolving front parameters. The assimilation scheme is based on Kalman filtering. Nonlinear extensions of Kalman filters are required to deal with the nonlinearity between the front parameters and the acoustic measurements. Simulation results based on realistic environmental scenarios show that the developed scheme is able to track temporally the main parameters of the front.

Passive tomography in coastal areas: A feasibility study of the Ushant front monitoring

This work presents a feasibility test of acoustic data assimilation in a basic feature model of the Ushant front, west off Brittany, enabling the tracking of the principal characteristics of the front. Two monitoring applications are presented for tracking the tidal variations of the front and its seasonal variations (from April to July). The data assimilation method is based on ensemble Kalman filtering, enabling the process of the nonlinearity between front parameters and acoustic measurements. To prevent from the resolvability problem inherent to travel-time tomography method in shallow water, the proposed scheme considers full-field acoustic data and a normal-mode propagation model taking into account the seabottom properties. The complex field on a vertical array of receivers is assimilated in the front model to continuously correct the prediction of the front parameters. Simulation results demonstrate the feasibility of the method.

Underwater microorganisms observation with off-axis digital holography microscopy using partially coherent illumination

Nowadays, the plankton net is replaced by underwater imaging systems. With the advent of digital technologies, detection and classification of plankton and subcentimetre-scale pelagic organisms may be largely accelerated even if still requiring human expertise at some processing stages. Moreover, the non intrusive aspect of in situ imaging systems are preferable for preserving the organisms in their natural habitat to avoid damaging those most fragile. This paper presents experimental results of a new digital holography microscope (DHM) prototype, Holoflow@Sea, based on an off-axis configuration. Using a partially coherent laser illumination, the DHM has been developed for in situ observation with and without microscope objectives. The holograms can be acquired with a frame rate up to 15 images per second on a CCD array of 2456×2058 pixels. Reconstruction algorithms enable then refocusing and tracking of objects in the probed volume with a resolution up to a few micrometers when working with the highest magnification setup. The use of partially coherent light source is shown to efficiently reduce the speckle noise that comes with fully coherent illumination. Although an off-axis configuration results in a lower resolution than that of an equivalent in-line configuration, the approach is shown to be relevant for in situ underwater applications. Based on the results, this paper discusses the prototype performance in different natural waters.

Spatial filtering in ambient noise interferometry

Theoretically, the empirical Greens function between a pair of receivers can be extracted from the cross correlation of the received diffuse noise. The diffuse noise condition rarely is met in the ocean and directional sources may bias the Greens function. Here matrix-based spatial filters are used for removing unwanted contributions in the cross correlations. Two methods are used for solving the matrix filter design problem. First a matrix least-square problem is solved with a low-rank approximation of the pseudo-inverse, here, derived for linear and planar arrays. Second, a convex optimization approach is used to solve the design problem reformulated with ad hoc constraints. The spatial filter is applied to real-data cross correlations of elements from a linear array to attenuate the contribution of a discrete interferer. In the case of a planar array and simulated data, a spatial filter enables a passive upgoing/downgoing wavefield separation along with an efficient rejection of horizontally propagating noise. The impact of array size and frequency band on the filtered cross correlations is discussed.

Feature-Oriented Acoustic Tomography for Coastal Ocean Observatories

The deployment of coastal observatories motivates the development of acoustic inversion schemes able to characterize rapidly time-varying range-dependent environments. This paper develops feature models as parameterization schemes for the range-dependent temperature field, when the latter is mainly influenced by an identified oceanic feature, here thermal fronts. The feasibility of feature-oriented acoustic tomography (FOAT) is demonstrated in two cases of coastal thermal front known to occur regularly: the Ushant tidal front, France (48.5° N, 5° E), and the Cabo Frio coastal upwelling, Brazil (23° S, 42° W). Realistic scenarios simulated with regional circulation models provide typical environmental variations for testing the validity of the FOAT approach, with both global optimization and sequential filtering of the (synthetic) full-field acoustic data. Matched-field processing at multiple frequencies is used to reduce ambiguities between parameters and to achieve a good tradeoff between robustness and sensitivity. The proposed feature-model parameterization is shown to provide robust estimates of the 2-D temperature field even when the simulated environment presents smaller scale inhomogeneities. Moreover, the sequential filtering based on a random walk model of the thermal front parameters enables a stable tracking of typical temperature field variations along several days. This sequential approach is particularly convenient for continuous, long-term monitoring operated with bottom-moored ocean observatories.

Water mass, front and meanders of the Brazil Current seen through acoustics: A preliminary study

The Brazil Current (BC) is perhaps the least studied subtropical boundary current of the worlds oceans. Within this region, the BC develops vigorous meanders and rings. A combination of numerical simulations and observational studies are important tools for unravelling these phenomena. Direct current measurements are rare and usually too short to depict the mean, long term circulation patterns. Similarly, quasi-synoptic hydrographic data in the region is sparse. Acoustic waves are an efficient tool for covering large regions of the water column in a synoptic way. Acoustic tomography can, therefore, be useful to better predict, through inversion for the effective sound speed field and its assimilation to a circulation model, the oceanographic fields of interest (temperature, salinity, density). Such information is particularly important for initialization and data assimilation to regional models for which small and meso-scale processes are of fundamental interest. In this paper, a preliminary study of acoustic propagation modelling through one vertical section off the Brazilian southeastern coast is presented. The acoustic rays are trapped in a minimum sound speed channel bounded by Antarctic Intermediate Water and Upper Circumpolar Deep Water. Between this so-created deep channel and the shel break, one interesting region from the acoustic viewpoint is identified. Notable variations in the transmission loss field are found in this region when the Brazil Current front is moving. In addition, the results show the baroclinic currents more sensitive to salinity variations than sound speed structure, as well as acoustic propagation.

Feature-oriented acoustic tomography of a coastal thermal front

The continuous monitoring of coastal processes presents a great interest both from the environmental and economic viewpoints. Passive acoustic tomography can be a good candidate to provide synoptic measurements over wide areas while a range-dependent inversion scheme allows to achieve a reasonable spatial resolution along each vertical slice section. This work develops a feature-oriented parameterization scheme for acoustic tomography purposes, enabling the tracking of the main structure of a thermal front. A Kalman algorithm filters sequentially acoustic data recorded on a vertical array, in a frequency regime corresponding to a useful part of ship noise spectrum.