基于EKF的天线罩误差斜率多模型估计方法  

Radome Slope Estimation Using Multiple Model Based on EKF

作　　者：曹晓瑞[1] 董朝阳[2] 王青[1] 陈宇[1] 

机构地区：[1]北京航空航天大学自动化科学与电气工程学院,北京100191 [2]北京航空航天大学航空科学与工程学院,北京100191

出　　处：《航空学报》2010年第8期1608-1613,共6页Acta Aeronautica et Astronautica Sinica

摘　　要：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 using the multiple model（MM） algorithm based on the extended Kalman filter（EKF） is proposed to estimate the radome slopes and improve the performance of active radar-guided homing missiles.The filter dynamics are built in the three dimensional engagement scenario and the states are composed of relative position,velocity,missile acceleration and target acceleration.The EKF algorithm is adopted to solve the nonlinear measurement function with radome slope interference.The proposed filter algorithm utilizes pseudo-measurements to update the mode probabilities in the MM algorithm based on a series of possible radome slope models.The estimated results of the slopes are introduced into the EKF to get state estimations without radome interference which generates the guidance law command.Simulation results indicate that the MM-EKF algorithm can estimate the radome slopes effectively and improve the accuracy of the guidance system.

关 键 词：三维制导模型 雷达制导 天线罩误差斜率 扩展卡尔曼滤波 多模型算法 

分 类 号：V243.4[航空宇航科学与技术—飞行器设计] TJ765[兵器科学与技术—武器系统与运用工程]