Fast Intercept Trajectory Optimization for Multi-stage Air Defense Missile Using Hybrid Algorithm

A hybridalgorithmconsists of particle swarm optimization (PSO) and sequential quadratic programming (SQP) is proposed, and appliesto solve the optimal trajectory with maximizing the terminal velocity at predict impact point (PIP) for multi-stage air defense missile. This hybrid optimization approach combines the advantages of PSO as a global optimizer and complemented with SQP to find the accurate local optima. A simple plane motion equation of multi-stage air defense is establishedwith respect to trajectory referenceframe firstly, and restrictions on path parameters and terminal conditions are modeled.For task with given PIP, intercept trajectory optimization problem is a classical continuous optimal control problem. Then control of angle of attack (AOA) is parameterized according to empirical equations so that converting the continuousoptimal control problem into a parameters optimization problem.Finally, the hybrid algorithm is employed to solve this parameters optimization problem effectively with high accuracy. Several simulations and comparative cases are carried out, simulation results illustrate the hybrid method is feasible and it can fast converges to the optimal solution. Comparison results with the conventional optimization algorithm confirm that the proposed algorithm is more accurate and effective and more suited for missile trajectory profile optimization.