Generation of missile guidance algorithms

Traditionally analytical techniques including differential game theory and optimal control theory have been applied to the homing missile guidance problem. Unfortunately it is difficult to include all the constraints, uncertainties and nonlinearities in a single problem formulation. A genetic algorithm (GA) is used as a numerical optimisation tool to optimise a range of guidance algorithms for an air-to-air homing missile. A GA approach allows the use of a more complex missile simulation model, which includes noise, constraints and multiple target manoeuvres. Unfortunately GAs are computationally intensive. In order to assess a guidance law, a full engagement must be carried out. The laws generated in general take between 3 and 4 days to evolve using a 166 MHz PC. The power of computers is rapidly increasing so this approach is becoming more practical. A range of guidance algorithms have been evolved which use neural networks and fuzzy networks as function approximators. These laws have been shown to outperform both a classical and a modern guidance law, using a realistic model of an active monopulse homing missile. There still remains work to be carried out before laws are produced which can be of practical use