动中通多传感器融合超球体采样UKF姿态估计

UKF Based Low-Cost Attitude Estimation Algorithm for Satcom-on-the-Move

针对动中通系统低成本姿态估计计算复杂、易受侧滑角和机动加速度等外界因素干扰的问题,提出一种基于超球体采样无迹卡尔曼滤波算法,融合微机械陀螺、加速度计和单基线GPS,对载体姿态进行精确估计。为了提高姿态估计的实时性,采用超球体采样减少无迹卡尔曼滤波器的采样点数量,在不影响精度的前提下,有效降低了算法的计算量;此外,加速度计姿态角测量值在加速、转弯行驶过程中会受到机动加速度的影响,为解决这一问题,通过单基线GPS提供的速度、侧滑角信息进行机动加速度补偿。行车实验表明,提出的低成本姿态估计方法估计精度较高,在降低成本的同时能够满足宽带移动卫星通信波束对准要求。

The low-cost attitude estimation algorithm for Sitcom-on-the-Move （SOTM） system is usually complicated,and easily affected by the maneuvering acceleration and the sideslip angle.To solve the problems,we proposed an algorithm based on the spherical simplex transformation Unscented Kalman Filter （UKF）,which fused the information from micromechanical gyroscope,accelerator and GPS for estimating the attitude accurately.To improve the real-time performance,the filter used the spherical simplex transformation to reduce the number of sigma points for speeding up the calculation,reducing the computation load and providing better filtering performance.The GPS-measured velocity was used to compensate for the maneuvering acceleration,and the sideslip angle was used to further correct the maneuvering acceleration when the vehicle was turning.Experimental results show that the low-cost attitude estimation algorithm is feasible for attitude stabilization of SOTM in both pitch angle and roll angle with accuracy of ＆#177;0.5°.