Synthesis of Guidance Law for an Anti-Ship Missile Class Using Artificial Neural Networks

The current guidance methods for anti-ship missiles mainly rely on Proportional Navigation (PN), which is limited in quality when missile parameters and objectives change, or in different combat scenarios. To enhance the quality of guidance systems for anti-ship missiles, the author proposes the application of Artificial Neural Networks (ANNs) as a replacement for the proportional navigation approach. In this article, the author employs multilayer feedforward neural networks to synthesize guidance laws for anti-ship missiles. This enables the system to achieve better results for combat scenarios with different initial conditions. Simulation results demonstrate the potential of artificial neural networks to replace and upgrade a range of modern missile guidance laws in the future. © 2024 The Aeronautical and Astronautical Society of the Republic of China. All rights reserved.