基于模糊卡尔曼滤波的内阻尼姿态算法研究

在系统机动性不强的情况下，传统的平台内阻尼算法将系统本身的速度信息通过阻尼网络加到系统中，达到提高姿态角精度的目的。将这种平台内阻尼的思想引入到捷联惯性航姿系统中，在系统加速度较小的情况下，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系统姿态误差。由于加速度的大小直接影响滤波器精度，本文设计了模糊自适应卡尔曼滤波算法，根据三轴加速度计的输出调整内阻尼量测误差方差阵，从而避免了滤波器的发散。仿真和实验验证，内阻尼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。

The Fuzzy Kalman Filter of Damp Attitude Algorithm

Traditional inertial mechanized-platform uses velocities to damp the system attitude to improve the precision of attitude,when the system acceleration is small.Referring to the idea,this paper designeda damp Kalman filter in Strap-down Attitude Heading Reference System(AHRS).The new method makes use of 3-D accelerometer's measurements to estimate the system attitude,which is measured to compensate attitude errors.Because the acceleration affected the precision of filter directly,the Fuzzy adaptive system was presented.The Fuzzy Logic inputs are three accelerations and the output is to control the measurement noise covariance matrix.Simulations and experimental results prove that the damp algorithm can damp most of Schuler oscillation and Foucault oscillation,so that to assure the filter convergence and efficiently improve the precision of strap-down AHRS.