Abstract:

In order to solve the interception problem of aircraft under the condition of unknown target maneuver strategy, a three-dimensional rolling optimal guidance strategy based on neural network is proposed. Firstly, aiming at the problem that it is difficult to determine the terminal time of the global optimal guidance law, the zero effort miss is introduced to design the local optimal guidance law under the framework of rolling horizon optimization, and the particle swarm optimization algorithm is used to solve it. Secondly, in order to improve the efficiency of on-line solution of guidance law, a neural network is constructed to learn several groups of guidance training data obtained by rolling solution of particle swarm optimization algorithm off-line, and the trained network is used for on-line rolling optimization of guidance instructions. The simulation results show that the neural network rolling optimization guidance strategy has good guidance performance for targets with various maneuver modes, effectively improves the on-line optimization efficiency of guidance instructions, and can provide a reference for the real-time rolling solution of aircraft guidance law.

Key words: guidance strategy, rolling horizon optimization, particle swarm optimization, neural network