Xavier Cristol

Improved Active Sonar Tactical Support by Through-the-Sensor Estimation of Acoustic Seabed Properties

Accurate environmental information is required for obtaining confident sonar performance predictions. This environmental information is, however, often unreliable or unavailable. To support antisubmarine warfare (ASW) operations, a through-the-sensor approach has been developed in which relevant acoustic seabed properties are derived from reverberation data, and a demonstrator system has been installed on a Royal Norwegian Navy frigate. It determines relevant acoustic seabed parameters from the reverberation data near real time. This demonstrator system has been validated in several sea trials conducted off the coast of Bergen, Norway. The acoustic seabed parameters derived in these trials have a good correspondence with the available prior information. Furthermore, the results show that acoustic seabed parameters derived from reverberation data in previous trials can be used to improve reverberation prediction for subsequent trials, even when environmental conditions, i.e., sound-speed profiles, are different. Because the demonstrator makes information on acoustic seabed properties directly available for in situ sonar performance prediction, it can be used as a tactical decision aid.

Stabilizing reverberation inversion by regression relations involving a grain size parameter

Within the European Defence Agency (EDA) project Rumble-2, an operational low-frequency active sonar system has been used to collect reverberation data at several sea trials in the North Sea. A global optimization method is used to determine the bottom parameters that provide the best match between measured and modeled time traces. A fast ray model is used for the forward computations. The bottom parameters are the Lambert back-scattering parameter and the sound speed c, density ρ, absorption α, and thickness of the sediment. The reverberation data do not constrain all these parameters to unique values, however, and different approaches have been tried in the project to reduce the ambiguity problems. The approach reported here is to use the mean grain size Mz as a common descriptive parameter. From regression relations by Hamilton and Bachman, c, ρ, and α can be set as functions of Mz. More ambitiously, the regression relations could be applied as a priori constraints, with uncertainties, in a Bayesian fr...

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.

Bayesian reverberation inversion incorporating grain-size dependent regression relations as a priori information

An operational low-frequency active sonar system has been used in the EDA (European Defence Agency) project Rumble-2 to collect reverberation data at sea trials in the North Sea. Using a fast ray model for the forward computations, the reverberation data are inverted to determine bottom parameters: Lambert back-scattering parameter μ and sound speed c, density ρ, absorption α, and sediment thickness h. Hamilton-Bachman regression relations for c, ρ, and α, are incorporated with uncertainties and with the mean grain size Mz as a common descriptive parameter. This fits nicely into a Bayesian inversion framework, but with a non-uniform prior pdf (probability density function). Markov-chain Monte-Carlo techniques are applied to produce an ensemble of models distributed in model space according to the PPD (posterior probability density), which is thereby assessed. Laplace distributions are chosen to model the data residuals, or data errors, and particular attention is given to estimation of the corresponding covariance matrix in the non-stationary case. There appears to be a risk of finding a point in model space for which the reverberation trace matches the noisy data trace better than the “true“ model. This could lead to too small data error estimates and a too narrow estimate of the PPD. Application to the actual Rumble-2 reverberation data pings indicates that the mean grain size Mz and the Lambert parameter μ are reasonably well determined, whereas there are uncertainties concerning the sediment thickness. The pings involve bottom areas mainly covered by sand and silt, respectively, and the inversion results reflect this difference in the anticipated way

Hausdorff distance applied on real data experiment for underwater localization

This paper addresses the problem of localizing and tracking a surface or underwater vessel with the technique called as Hausdorff Distance. Two proposed approaches, based on TDOAs comparison, were used for 2-D localization, in range and depth, with one sensor only, and have been successfully applied to localize a motionless unknown target in a tanks experiment. Results in terms of the localization accuracy have been obtained with real signal and the performance of the proposed localization techniques have been demonstrated and confirmed by simulation with respect of signal-to-noise ratio and compared with the correlation techniques used nowadays for single hydrophones.

Decoherence effects in 3D fluctuating environments: Numerical and experiment study

This paper is devoted to the study of the effects of ocean fluctuations on acoustic propagation. The development of an ultrasonic testbench allowing to reproduce, under laboratory conditions, the influence of 3D fluctuations on received acoustic data is presented. The experimental protocol consists in transmitting, in a water tank, a high-frequency wavetrain throughout an acoustic slab presenting a plane input face and a randomly rough output face. The various regimes of saturation and unsaturation classically used in the literature are explored by tuning the statistics of the so-called RAFAL (RAndom Faced Acoustic Lens). Comparisons to a “corresponding” oceanic medium are obtained via a scaling procedure. In parallel, numerical tools were developed to provide meaningful comparison with the acquired data. Both based on a split-step Fourier algorithm, a 3D PE simulation of the tank experiment and a 3D PE simulation of real scale acoustic propagation programs are presented. Features of acoustic fields pertu...