单球无味卡尔曼滤波在飞船姿态估计中的应用

Spherical Simplex Unscented Kalman Filter for Spacecraft Attitude Estimation

提出了一种用矢量观测来估计飞船姿态的单球无味卡尔曼滤波算法。该算法将单球无味变换与无味卡尔曼滤波结合起来,与采用尺度无味变换的无味卡尔曼滤波相比,具有更低的计算量。飞船的姿态运动学描述采用了四元数,而用广义罗德里格斯参数来克服卡尔曼滤波过程中的四元数归一化误差。仿真结果表明,该算法比标准扩展卡尔曼滤波具有更低的姿态估计误差及更快的收敛率。与无味卡尔曼滤波相比,较低的计算量及相同的估计精度使该算法更适合在实时姿态估计中应用。

A spherical simplex unscented Kalman filter is proposed to estimate the spacecraft attitude from the vector measurements. The algorithm combines a better-behaved spherical simplex unscented transformation, which can simplify the computational complexity in comparison with the scaled unscented transformation, with the unscented Kalman filter. The quaternion is used to describe the spacecraft at titude kinematics, while a three--dimensional generalized Rodrigues parameter is used to maintain the quaternion normalization constraint in the filter formulation. Simulation results indicate that the proposed filter can provide lower attitude estimate errors with faster convergence rate than the standard extended Kalman filter. Furthermore, the lower computational costs of this novel filter make it an alternative to the unscented Kalman filter for real--time spacecraft attitude estimation with the same estimation accuracy.