在轨运行过程中, 受空间热环境的影响, 星敏感器的安装矩阵具有轨道周期变化的特征。为了校准卫星结构变形导致的星敏感器之间安装矩阵变化, 提出了一种基于四元数自适应卡尔曼滤波(quaternion Adaptive Kalman Filter, q-AKF)的安装矩阵在轨实时校准方法。该方法结合衰减记忆滤波与简化的Sage_Husa自适应滤波, 通过自适应调整衰减因子, 调节当前量测值在滤波过程中的权重, 以抑制因模型参数不准确造成的滤波性能下降甚至发散问题。仿真试验结果与在轨数据验证结果表明: q-AKF算法不但可以抑制参数不准确造成的滤波发散问题, 而且在0~5 (°)/s的姿态机动速率范围内, 仍能稳定跟踪安装矩阵的真值(偏差均值的绝对值<0.15″), 具有良好的自适应性与鲁棒性。

In flight, the installation matrix of star tracker changed with the orbital period affected by the space thermal environment. In order to calibrate the variation of the installation matrices between star trackers caused by the structural distortion of the satellite, a real time on-orbit installation matrix calibration method based on quaternion adaptive Kalman filter was proposed. The algorithm was based on the combination of fading memory filter and simplified Sage_Husa adaptive filter. The algorithm adjusted the weight of the current measurement by adjusting the fading factor adaptively, which could restrain the filter divergence caused by the inaccurate model parameters. The results of simulation experiments and on-board data verification show that the q-AKF algorithm not only could restrain the divergence problem caused by the inaccurate model parameters, but also could track the real values of the installation matrix stably, when the attitude maneuver rates ranged from 0 to 5 (°)/s. It is better in adaptability and robustness.