基于非平稳时间序列的陀螺漂移性能建模与预测方法研究

Study on the methods for modeling and forecasting gyro's drift performance based on non-stationary time series

研究了利用Kalman滤波和小波分析两种方法对陀螺漂移非平稳时间序列建模预测的基本思想和具体算法。实验证明,这两种方法较传统的差分法优越,可以很好地完成非平稳时间序列的建模预测,并且通过比较分析了它们各自的优缺点,为选用合理的建模方法提供了依据。

The basic ideas and the idiographic arithmetics are studied to model and forecast the non-stationary time series of the gyro's drift through Kalman filter and Wavelet analysis. The experiment shows that these two methods are better than the traditional difference method, through which the non-stationary time series can be modeled very well. Finally, their own merits and disadvantages are analyzed respectively by the comparison, which provide the basis for choosing the reasonable modeling method.