Missile guidance using neural networks

Abstract

This paper introduces a new guidance algorithm using neural networks for bank-to-turn (BTT) missiles. The proposed guidance algorithm compensates for the missile dynamics by using the inverse dynamics learned by neural networks. The new guidance law is applied to a full-order nonlinear BTT missile model, and the performance is compared with that of the proportional navigation guidance law. Copyright (C) 1997 Elsevier Science Ltd.