Neural network application for emitter identification

A common function of Electronic Support Measures (ESM) system is a threat detection in the electromagnetic environment and the area surveillance so as to determine the identity of surrounding emitters. The paper presents the application of neural networks as a new way to cluster and classify radar signals in the reconnaissance systems. The basic concepts of this technique are described. The efficiency of application back-propagation (BP) neural network with two hidden layers to emitter identification was examined. The recognition results obtained through the simulation of some prototype models of radar signals are illustrated in appropriate tables.