基于改进粒子群算法的目标航迹模拟及RCS仿真

针对雷达运动目标轨迹模拟逼真度问题和RCS特征,提出一种基于嵌入式粒子算法的目标航迹模拟和RCS仿真方法。首先,分析了无人机模拟运动目标航迹的基本原理,以及无人机和模拟目标之间的运动模型和耦合关系,确定了耦合因子和控制量。然后,分析了目标运动轨迹模拟的约束条件,并结合无人机性能和能耗等因素给出了目标优化适应度函数,建立了目标航迹模拟的最优控制模型。其次,为提高模型解算的针对性和实用性,将粒子群算法进行改进,并嵌入到模型求解中,实现了对目标航迹的有效模拟。最后,基于模拟目标航迹,利用飞行动力学原理和坐标系转换计算得到模拟飞行目标的姿态角,通过电磁计算软件仿真得到模拟飞行目标的RCS。仿真结果表明,该方法对实现运动目标轨迹模拟和RCS仿真具有广泛适用性。

A Simulation of Target Tracking and RCS Based on Improved Particle Swarm Optimization Algorithm

In view of the fidelity issue of moving target tracking simulation and RCS characteristics, a target tracking and RCS simulation method is proposed based on the improved particle swarm algorithm (PSO). Firstly, the basic principle of simulating the tracking of moving targets is analyzed by unmanned aerial vehicles (UAV), the motion model and coupling relationship between UAVs and simulated targets are discussed, and the coupling factors and control quantities are determined. And then, the constraint conditions for simulating the target tracking are analyzed, and the target optimization fitness function is given in consideration of UAV performance and energy consumption, and an optimal control model is established for simulating the target tracking. To improve the accuracy and practicality of the model solution, the particle swarm optimization algorithm is improved and embedded in the model solution, achieving an effective simulation of the target tracking. Finally, based on the simulated target tracking, the angle of altitude in simulating flight target is calculated through flight dynamics principles and coordinate system transformation, and the RCS of the simulated flight target is simulated by the electromagnetic calculation software. The simulation results show that this method is wide applicable for achieving tracking simulation of moving targets and RCS simulation.