基于数据拟合插值的自适应姿态估计算法

Attitude Estimation with Adaptive Kalman Filtering Based on Data Fitting Interpolation

针对高精度惯导输出信息的频率有限,不能很好地满足移动卫星通信控制精度的问题,提出了一种基于数据拟合插值的Sage-Husa自适应卡尔曼滤波姿态估计算法。通过采用三次样条插值提高高精度惯导输出数据的频率,增加系统单位时间内的估计次数;通过自适应卡尔曼滤波算法不断修正滤波误差,避免系统因参数匹配不当引起的滤波发散。实验结果表明:数据拟合插值弥补了系统数据更新频率低的不足,自适应滤波提升了系统应对不同环境的鲁棒性。天线波束姿态估计精度和测控精度也得到明显提高,满足宽带移动卫星通信的波束指向需求。

The output frequency of signal in high-precision inertial navigation is limited, which is difficult to meet the accuracy requirement of control system for mobile satellite communications. To solve the problem, an attitude estimation algorithm with Sage-Husa adaptive Kalman filter based on data fitting interpolation is presented. It uses cubic spline interpolation to increase the output frequency of attitude information and increase the system estimation times per unit interval. The adaptive Kalman filter algorithm is used for constantly revising the filtering error and avoiding the possible filter divergence caused by system parameter mismatching. The experiment result shows that ： 1 ） Data fitting interpolation can make up for the deficiency of the high-precision inertial navigation in data update frequency, and the adaptive filtering can improve the robustness of the system to different environment;and 2 ） The attitude estimation and control accuracy of antenna beam attitude are improved significantly, which can satisfy the beam pointing needs of broadband mobile satellite communications.