To solve the cued search problem when ESMs and radars cooperate with each other in anti-stealth detection

a MPC-based(Model Predictive Control) mission planning frame for cued search is proposed

and the targets' states predictive model and on-line receding optimization model are established based on the MPC theory.Then

this paper puts forward an improved parallel PSO(Particle Swarm Optimization) algorithm to solve the problem.Concretely

a high-dimensional matrix mode is designed for particle coding

a scale-factor is imported for boundary restriction

a probabilistic model is proposed for processing discrete variable

and a new multi-swarm parallel strategy called MM-SS(Multi-Master-Single-Slave) is presented for promoting optimization efficiency.Experiments show that the established model realizes an efficient control of multi-radars in condition of uncertainty and multiple targets

and that the proposed algorithm can solve the receding optimization problem efficiently.That is

the validity of the model and algorithm is demonstrated.