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A new method for multipath channel time delay estimation is proposed. The authors present a Bayesian approach which takes into account the attenuations and noise distributions at the output of the receiver. This leads to a simple criterion which can be written as the I/sub 1/ norm of an affine function of the desired attenuations. The good behaviour of this algorithm is shown on synthetic and real acoustic oceanic tomographic data.

As ocean insonification for basin scale Ocean Acoustic Tomography (OAT) appears to be a rather complicated and expensive matter, it is then interesting to get as much as possible information from each insonification. One possibility is then to increase the number of reception points. In that context, IFREMER started the design of a new autonomous receiver which could fulfill OAT requirements.

The travel time measurements of acoustic rays propagating between a source and a receiver are the basic data of an ocean acoustic tomography system. The author shows that the use of a simple 2-channel array allows the ability of the instruments to separate close arrivals to be significantly increased. >

In 1994, IFREMER launched the development of a new modular instrumentation for meso-scale OCEAN Acoustic Tomography (OAT). Previous instruments made by Woods Hole Oceanographic Institution (WHOI), Webb Research Corporation (WRC) and IFREMER are actually not adapted to basin scale studies (@1000 km). The new autonomous instrument is made up of a wide-band unlimited depth acoustic source, a high efficiency class D power amplifier, a programmable multi-function receiver, a long baseline positioning system and a low power high stability clock. Because of great depth and high efficiency requirements, the Janus-Helmholtz transducer technology was well suited to the long range OAT applications. For the 1997 CAMBIOS experiment, the instrument has been deployed in Atlantic at a 600 m depth. The working central frequency is 400 Hz and 600 km ranges are expected. In parallel to the source development, a 1 Gbyte storage capacity autonomous receiver able to work in various frequency bands has been realised. Fully compatible with the acoustic source, it can be used for standard OAT experiments. Following a description of the present instrumentation and the first result of CAMBIOS experiment, the evolution of the autonomous instrument for the near future is presented: a new optimised 250 Hz Janus-Helmholtz transducer for basin scale studies, a high stability rubidium clock, a four hydrophones receiving array and a multi-channel receiver, and the possibility to make a reliable acoustic control of all instruments from surface.

Multipath arrivals tracking and identification of SOFAR propagation are central points in ray ocean acoustic tomography data processing because one must know the ray geometry to solve the tomography inverse problem. Tracking resolved peaks all along an experiment allows to create temporal series of acoustic arrivals. Identification is achieved by comparing peak time series with outputs of a ray tracing model. The authors present a method based on neural networks to perform the tracking step. Two types of neural architecture (multi-layer perceptron and Hopfield) are used. As an intermediate result of the tracking, a global arrival peaks pattern is computed which used in conjunction with the predicted one in an iterative constrained minimisation allows one to perform the identification phase in a few iterations. Results obtained with a data set acquired during a four-month experiment illustrate the paper.

We propose, from experimental data, to identify the ocean acoustic multipaths, between acoustic sources and receivers separated about 100 km. After the description of experiment, we show that the active beamforming, using the knowledge of emitted signal, leads to satisfying spatial identification when the multipaths are temporarily separed, in spite of an antenna with only two phase centers. A fast spatio-temporal localization algorithm is used and useful results for acoustic tomography are obtained