Spacecraft Angular Rate Estimation from Magnetometer Data Only Using an Analytic Predictor

Spacecraft Angular Rate Estimation from Magnetometer Data Only Using an Analytic Predictor
复制标题

DOI:
10.2514/1.10332
复制
发表时间:
2004-05
影响因子:
2.6
通讯作者:
P. Tortora;Y. Oshman;F. Santoni
P. Tortora;Y. Oshman;F. Santoni
中科院分区:
工程技术3区
文献类型:
--
作者:
P. Tortora;Y. Oshman;F. Santoni

文献摘要

被引文献

相似文献

提出了一种根据连续的地球磁场读数快速估计近地轨道上翻滚航天器的角速度的方法。作为速率陀螺仪故障或初始捕获阶段的备用算法,估计器由扩展卡尔曼滤波组成,基于惯性地磁场矢量在短采样时间内不会有显著变化的假设。由于忽略了外部干扰力矩,因此可以在滤波器的传播阶段使用欧拉方程的解析解,与欧拉方程的数值积分相比,可以显著节省计算时间。与大多数现有的角速度估计器相反,在所提出的算法中既不使用也不估计航天器的姿态。此外,以身体为基准的地磁场观测不是作为外部预滤波程序在时间上进行区分,而是由过滤器直接处理。这种处理产生了有色有效测量噪声,通过近似马尔可夫模型和应用Bryson和Henrikson的降阶滤波理论对其进行了适当的处理。采用标准的10阶国际地磁参考场模型进行了仿真研究,验证了该算法的有效性。
A method is presented for fast estimation of the angular rate of a tumbling spacecraft in a low-Earth orbit from sequential readings of Earth’s magnetic field. Useful as a backup algorithm in cases of rate gyro malfunctions or during the initial acquisition phase, the estimator consists of an extended Kalman filter, based on the assumption that the inertial geomagnetic field vector does not significantly change during the short sampling time. As the external disturbance torque is neglected, an analytic solution of Euler’s equations can be used in the filter’s propagation phase, allowing a significant savings of computation time compared to numerical integration of Euler’s equations. Contrary to most existing angular rate estimators, the spacecraft’s attitude is neither used nor estimated within the proposed algorithm. Moreover, the body-referenced geomagnetic field observations are not differentiated with respect to time as an external prefiltering procedure but are directly processed by the filter. This processing gives rise to a colored effective measurement noise, which is properly handled via approximate Markov modeling and application of Bryson and Henrikson’s reduced-order filtering theory. A simulation study employing a standard tenth-order International Geomagnetic Reference Field model is presented to demonstrate the performance of the algorithm.