基于地磁场测量估计卫星姿态的UKF算法

UKF for Satellite Attitude Estimation Based on Geomagnetic Field

提出了利用UKF(Unscented Kalman Filter)处理地磁场测量数据进行低轨道(LEO)卫星自主定姿的算法。通过使用估计姿态、轨道参数和国际地磁场参考(IGRF)计算得到的地磁矢量与三轴磁强计(TAM)的测量矢量之差作为更新信息,可以实现实时的姿态角和角速度估计。针对卫星稳态定姿、大角度快速机动的定姿以及姿态失控状态下的定姿等三种任务,分别用UKF和传统的EKF(Extended Kalman Filter)进行了数值仿真。仿真结果显示出本文提出的定姿算法的优越性。

An autonomous attitude determination algorithm based on Unscented Kalman Filter （UKF） for low-Earth orbit （LEO） satellite is developed by processing geomagnetic field measurements. The Earth＇s magnetic field is well modeled and can be calculated from estimated attitude, orbit parameters and international geomagnetic reference field （IGRF）. The difference between the calculated geomagnetic vectors and the measured geomagnetic vectors from the onboard three-axis magnetometer （TAM） is used as updating information, such that the attitude angle and angular velocity can be estimated online. A compared research on UKF and conventional Extended Kalman Filter （EKF） was carried out by means of numerical simulation for three different attitude determination missions which were attitude stabilization, large angle rapid maneuver and attitude loss control. The simulation resuits show the validity of the proposed approach.