Abstract:

In order to solve the problem of real-time route planning of unmanned combat aerial vehicle (UCAV), the damage and injury distance are got through threat classification and delamination. A simple two-dimensional UCAV model is established. The threat cost function based on the detecting probability is got by utilizing the relation between flight attitude and dynamic radar cross section (RCS). Finally the adaptive learning  particle swarm optimization (PSO) algorithm is used to simulate the new way， and the result indicates the validity of this method