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.

The European Defence Agency project RUMBLE-2 (ref.[1]) offered the opportunity for investigating experimentally acoustic reverberation at about 1.kHz, under grazing incidence (less than about 20°), from very porous clayey seafloors of a continental shelf (mean grain size spanning from about 7 to 10 in  units); the instrument was an operational, carefully calibrated LF towed triplet-array sonar. Assuming Lambert law, observed values for the normal backscattering strength μ0 spanned between –20 dB to –12 dB, i.e. 10-15 dB higher than usually recommended values for soft seabeds. The objective of this article is to understand such high values of inverted μ0’s during the RUMBLE2 experiments, which appear at first glance considerably high, particularly when considering the nature of the sedimentary cover. As displayed by the map on the left of Figure 1, the inverted μ0’s are ranging from about –20 to –12 dB, for a seabed covered by very thin clays with Mean Grain Sizes of 8 to 10  units (porosities more than 85%), as shown by the chart on the right of Figure 1. Usually recommended values for μ0 are 10 to 15 dB lower, or even more; we have to explain such a disturbing discrepancy.

An operational low-frequency active sonar system has been used in the European Defence Agency (EDA) project Rumble-2 to collect reverberation data in the North Sea. Using a fast ray model for 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 thickness h of the sediment. Hamilton-Bachman regression relations for c, ρ, and α, are hereby 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 a priori probability density function. Markov-chain Monte-Carlo techniques are applied to produce an ensemble of models distributed in model space according to the a posteriori probability density function, which is thereby assessed. Laplace distributions are chosen to model non-stationary data errors, and particular attention is given to corresponding covariance matrix estimation. Application to actual reverberation data pings shows 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, and the inversion results reflect this difference in the anticipated way.

This paper presents the European Defence Agency project called “RUMBLE 2” carried out with contribution of several European organizations: TUS in France, TNO in the Netherlands, KDS and FFI in Norway, FOI in Sweden. The objective was to assess the capability of an operational Low Frequency Active Sonar (LFAS) to estimate bottom parameters in shallow water necessary to predict LFAS performance. An inversion method based on the observation of broadside beam reverberation power decay received on a towed array was developed by TNO and applied to experimental results obtained in the North Sea. The result of the inversion is a real time mapping of sea bed parameters, used for improving the prediction of the sonar performance. A demonstrator has been realized, mounted onboard a new Norwegian frigate, using a CAPTAS triplet array sonar and tested at sea. Satisfying agreement with ground truth has been obtained over the set of investigated data. Experimental results lead to a good description of the sea bed reverberation parameters in real time resulting in improved sonar performance predictions. During sea trials, the demonstrator has shown its capability to be used during standard missions of the frigate.