Abstract
Underwater object identification has been of great interest for a few years to acousticians (detection of boulders) or marines (detection of buried mines). Image and signal processing succeed in identifying objects lying on the sea bottom, however identification of an object buried in sediment remains complex. The purpose of this paper is to develop a complete identification of objects embedded in the sediment using array processing methods. We use a parametric source whose properties are based on the water nonlinear propagation characteristics, the signals are received on a uniform linear antenna. The higher order statistics of the recorded data and the high resolution methods are used to localize the objects and to estimate their ranges. This paper presents also a procedure which estimates discriminant parameters from the signals in order to classify the different objects. The developed algorithms are applied on the experimental underwater acoustic data. The obtained results show the good performance of our algorithms.
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