论文部分内容阅读
提出一种新的滤波器结构,利用基于扩展卡尔曼滤波(EKF)的多模型(MM)算法,对天线罩误差斜率进行估计,降低天线罩误差对雷达自寻的导弹的影响,提高系统性能。在三维坐标下,创建包含导弹运动方程、目标运动方程、弹目相对运动方程的滤波模型。采用EKF算法,对包含天线罩误差的非线性观测方程进行线性化处理;依照多模滤波的思想,对天线罩误差进行离散建模,构建伪观测方程,更新模型概率,得到天线罩误差斜率的估计值;将斜率估计结果代入EKF,得到滤除天线罩误差影响的系统状态量估计结果并形成制导指令。仿真结果表明,所提方法可以有效地估计天线罩斜率,提高系统制导精度。
A new filter structure is proposed. Based on the extended Kalman filter (EKF), a multi-model (MM) algorithm is proposed to estimate the error slope of the radome to reduce the influence of the radome error on the self-seeking radar and to improve the system performance . Under three-dimensional coordinates, create a filter model that contains the equation of missile motion, the equation of target motion, and the equation of relative motion of the projectile. The EKF algorithm is used to linearize the nonlinear observation equation including the radome error. According to the idea of multi-mode filtering, the error of the radome is discretizedly modeled, the pseudo observation equation is constructed, the model probability is updated, and the error slope of the radome The slope estimation result is substituted into the EKF to obtain the system state quantity estimation result of filtering the influence of the antenna cover error and form the guidance instruction. The simulation results show that the proposed method can effectively estimate the slope of the radome and improve the system guidance accuracy.