航姿系统内阻尼的模糊自适应滤波算法

平台式惯性航姿系统的内阻尼算法通过阻尼网络将自身的速度信息加到系统中,达到提高姿态精度的目的.本文将该思想引入到捷联式惯性航姿系统中,在系统加速度较小时,利用加速度计的输出估计系统姿态角,通过卡尔曼滤波的形式补偿姿态误差.由于内阻尼算法只有在系统加速度较小的情况下才能使用,本文设计了模糊自适应控制器,根据三轴加速度计的输出进行自适应判断内阻尼算法是否可用,调整内阻尼卡尔曼滤波器的量测误差方差阵,从而避免了滤波器的发散.仿真和实验表明,内阻尼的模糊自适应算法可明显抑制舒勒周期振荡和傅科周期振荡,避免了系统姿态漂移,有效提高了捷联惯性航姿系统的精度.

Damp Kalman Filter with Fuzzy Adaptive Algorithm in AHRS

Schuler oscillation and Foucault oscillation take errors to strapdown attitude heading reference system(AHRS).By introducing the idea of damped algorithm of inertial navigation system(INS),this paper designs a damp Kalman filer in strapdown AHRS.When the acceleration is small enough,the system can use the three accelerometer outputs and the Kalman filter to compensate attitude errors.The system acceleration must be small enough,then the damp algorithm can be applied in the fuzzy logic adaptive controller to judge the damp Kalman filter usability and adjust the filter measure error matrix.Simulations and experimental results prove that the damp algorithm can damp most of Schuler oscillation and Foucault oscillation,thus assuring the filter convergence and improving the precision of strapdown AHRS.