基于Adaptive Sigma-Point滤波的智能导弹对目标协同定位方法研究

在对智能导弹协同作战过程详细描述的基础上,提出了一种利用多枚智能导弹协同对目标定位的方法。考虑目标运动模型为静止模型和运动模型两种情况,将Sigma-Point滤波方法与过程噪声的自适应估计方法相结合,融合目标运动状态和目标到达角信息,克服了常规Sigma-Point滤波性能依赖于目标运动模型的先验统计信息的缺点。通过比较目标可能存在区域面积的大小,确定了参与协同定位的智能导弹数目和编队构型。仿真研究表明,多枚智能导弹协同对目标定位可以显著提高定位精度和速度。

Using Cooperative Intelligent Missile to Localize Targets Based on Adaptive Sigma-Point Filtering

Based on describing the course of cooperative fight, the method to localize targets using multiple intelligent missiles is presented. Considering the target model as stationary model and mobile model, Sigma-Point filtering which is combined with noise adaptive algorithm is used to fuse the target state and angle of arrival. Therefore, the drawback of Sigma-Point filtering whose accuracy depends on prior statistic information could be overcome. By contrasting the area of possible target location, the number and formation of missiles which participate the cooperative localization could be determined. Simulation results show that the accuracy and velocity of target localization could be improved obviously via cooperation.