基于交错卡尔曼滤波的MEMS陀螺测量修正

Measurement Correction of MEMS Gyroscope Based on Interlaced Kalman Filtering

针对战术导弹上MEMS陀螺测量角速率误差大的不足,提出利用舵面控制量与弹体控制力矩的对应关系,通过弹体姿态动力学方程构建系统的状态方程,从而比低通滤波器更加真实地描述实际弹体的姿态变化;为了避免非线性方程线性化的误差和降低滤波计算量,利用交错卡尔曼滤波器通过对状态耦合项建立状态转移方程实现对原方程的伪线性化,从而有效降低运算量;最后通过对三轴转台上的MEMS惯组半物理仿真试验验证,该算法使低精度MEMS陀螺角速率测量误差降低到一半以下。

To correct the angular rate measurement error of MEMS gyroscopes for tactical missile, this paper proposes use of dynamics correspondence between the rudder control torque and the missile body attitude to build the state equation of system, which is more realistic and precise than the description for the actual missile attitude change with low--pass filter. In order to avoid errors in the linearization for nonlinear equations and reduce the filtering computation complexity, the Interlaced Kalman Filtering is applied to achieve the pseudo--linear state equation with coupling terms, which effectively reduce the computation complexity. Finally, the semi--physical simulation with the three--axis MEMS IMU and Electro--Servo verified that the angular rate measurement error of the low--precision MEMS gyroscope By the algorithm can be reduced below one half.