Abstract:

The radar cross section （RCS） changes rapidly with the variation of attitude angle during missile flight. Based on the relationship between the two， this paper proposed a missile target attitude angle inversion method using the particle swarm optimization （PSO） algorithm. The method estimated the target attitude angle by minimizing the mean square error between the observed RCS data and the RCS data derived from attitude angle inversion. Theoretical analysis shows that， under the premise that the target attitude angle does not change abruptly within a short time， the proposed method achieves a more accurate estimation of the target attitude angle. A series of simulation experiments was performed， and the results show that the proposed method can effectively invert the attitude angle sequence of the missile target.

Key words: missile, rader cross section（RCS）, attitude angle, attitude inversion, particle swarm optimization（PSO） algorithm

摘要：

导弹在飞行过程中，其雷达散射截面积(radar cross section，RCS)随着姿态角的变化而快速变化，利用两者之间的对应关系，提出了一种基于粒子群优化算法(particle swarm optimization，PSO)的导弹目标姿态角反演方法。该方法通过最小化观测RCS数据与姿态角反演得到的RCS数据的均方误差得到估计的目标姿态角，理论分析表明，在假定目标姿态角短时间内不发生突变的前提下，提出的方法可以实现对目标姿态角较为精确的估计。通过执行一系列仿真实验，验证了所提方法能有效反演导弹目标姿态角序列。

关键词: 导弹, 雷达散射截面积（RCS）, 姿态角, 姿态反演, 粒子群优化算法