基于磁强计和光纤陀螺的小卫星姿态确定非线性滤波算法

提出了一种小卫星姿态确定的非线性滤波算法,该算法利用三轴磁强计和光纤陀螺作为姿态敏感器。在非线性滤波器的设计中,从两个方面对平方根sigma点卡尔曼滤波方法进行改进。第一,把姿态四元数的矢量部分、光纤陀螺的漂移和噪声组合,得到滤波器的增广状态向量;第二,分别建立向量旋转模型、最优化模型和误差四元数乘法模型来确保非线性滤波过程中四元数的归一化约束。仿真分析结果表明,本文提出的非线性滤波算法能够有效地提高小卫星的定姿性能,与扩展卡尔曼滤波相比,具有较高的精度、稳定性和较快的收敛速度;与无迹卡尔曼滤波相比,收敛性相当,但是精度略优,稳定性和计算效率较高。

Nonlinear Filter Algorithm for Micro Satellite Attitude Determination via Magnetometer and Fiber Optic Gyroscope

A new nonlinear filter algorithm for micro satellite attitude determination is proposed, which adopts three-axis magnetometer(TAM) and fiber optic gyroscope(FOG) as attitude sensors. In the design of the nonlinear filter, square-root sigma point Kalman filter is modified. Firstly, an augmented state vector is derived by combining the vector part of attitude quaternion, the bias and noises of FOG. Secondly, vector rotational model, optimization model and error quaternion multiplication model are established to guarantee quaternion normalization constraint in the process of nonlinear filter. The simulation results indicate that attitude determination performance is improved effectively by the presented algorithm. Compared to EKF, accuracy and stability is much better, convergent speed is faster. Compared to UKF, convergence is equivalent, accuracy is slight better, while the stability and computing efficiency are both higher.