超低空拦截导弹武器系统的UKF-IMM目标跟踪算法

针对超低空拦截导弹武器系统的特点,提出了运用基于交互多模型的无迹卡尔曼滤波算法(UKF-IMM)对来袭目标进行状态估计的滤波方法.根据来袭目标的运动特点建立了特定的模型集,模型集由CV模型、比例导引模型和"当前"统计模型组成.每个模型分别采用UKF滤波器进行滤波,UKF-IMM滤波器的输出为各滤波器状态输出的概率加权融合.仿真结果表明,该模型集能够概括超低空拦截导弹拦截目标的运动样式,模型之间切换迅速,滤波算法收敛速度快.运用UKF-IMM滤波算法能够实现超低空拦截导弹火控系统对来袭目标及时准确地跟踪.

Target tracking algorithm of super-low altitude interceptors based on UKF-IMM

A new unscented Kalman filter(UKF) based on the interactive multiple model(IMM) is presented to apply in the field of target tracking according to the characteristics of the weapon system of super-low altitude interceptors.A model set including current statistical model,constant velocity model and proportional navigation model is designed according to the motion characteristics of incoming targets,and every model works by using unscented Kalman filters independently.The output of the UKF-IMM is the weighted sum of the outputs of all parallel unscented Kalman filters.Simulation results show that the model set covers the motion mode of intercepted targets and switches rapidly among models.Using the UKF-IMM algorithm makes the fire control system of the super-low altitude interceptor track targets quickly and accurately.