Optimization of trajectories based on APF-PSO with radar threats

This paper focuses on the trajectory optimization problem of the multi-observer system with the radar threat. By introducing the artificial potential field(APF) theory into particle swarm optimization(PSO), a new observer trajectory optimization algorithm is proposed based on artificial potential field and particle swarm optimization (APF-PSO). This algorithm simplifies the detection probability model by using the repulsion function. With Geometrical Dilution of Precision (GDOP), a new fitness function of particle swarm is constructed which makes the particle avoid obstacles in the initialization and update process. For solving the calculated inflation problems of PSO algorithm, the resultant force direction is applied in the particles renewal process as gradient information. In this case, the particles learn the direction of the resultant force with personal best solution and global best solution to update their position and speed, as a result, the movement of particle will be more efficient.