A Hierarchical Identity Based Key Management Scheme in Tactical Mobile Ad Hoc Networks

A seafloor classification methodology, based on a parametrization of the reverberation probability den­ sity function in conjunction with neural net classifiers, is evaluated through computer simulations. Different seafloor "provinces" are represented by a number of scatterer distributions exhibiting various degrees of de­ parture from the nominal Poisson distribution. Using the computer simulation program REVGEN/SST, these distributions were insonified at different spatial scales by varying the transmitted pulse length. The statisti­ cal signature obtained consists of reverberation kurto­ sis and coherent component estimates as a function of pulse length. The adaptive neural network algorithms are trained through supervised learning to recognize each statistical pattern and are presented with the task of dis­ criminating among the various scatterer distributions. The initial results indicate that this approach offers con­ siderable promise for practical, realizable solutions to the problem of remote seafloor classification.