Analog neural networks solve ambiguity problems in medium PRF radar systems

Abstract

Medium pulse-repetition frequency (PRF) radars combine the features of high PRF radars and low PRF radars. Both range and Doppler (range rate) ambiguities exist in such radars. It is demonstrated that the ambiguity problems in medium PRF radars can be solved efficiently using the neural network approach. A multilayer feedforward network is designed to solve the ambiguity problems. Both the simulation results and the analog electronics implementation are presented. A theory is developed and proven to facilitate a modular approach, dividing a significantly large number of stored patterns into modules in order to make analog neural chip implementation feasible for a real-world problem. The analog electronic feedforward neural network is two orders faster than the algorithmic approach. >