Seismic classification of military vehicles using neural networks

The problem of using neural networks for military vehicle classification on the basis of ground vibrations is presented in this paper. One of the main elements of the system is a unit called geophone, This unit allows to measure amplitude of ground vibrations in each direction for certain period of time. The value of amplitude is used to fix the characteristic frequencies of each vehicle. If we want to fix the main frequency it is necessary to use Fourier transform. In this case the fast Fourier transform (FFT) is used. Because the neural network (radial basis function network) is used, the learning set has to be prepared. Please find attached the results of using RBT neural network such as: example of learning, validation and test sets, structure of the networks and learning algorithm, learning and testing results.