Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
1890628 | Chaos, Solitons & Fractals | 2008 | 5 Pages |
Abstract
Gyro plays an important role in navigational systems and its drift has a direct influence on the precision. Therefore it is crucial that the gyro drift be forecasted precisely. In this paper, a hybrid modeling and forecasting approach based on the grey and the Box–Jenkins autoregressive moving average (ARMA) models is proposed to forecast the gyro drift. The results of experiments show that this method can forecast the drift precisely, which provides a basis for performance analysis and fault forecasting. Meanwhile, it can also be concluded that the hybrid method has a higher forecasting precision to the complex problems than the single method.
Related Topics
Physical Sciences and Engineering
Physics and Astronomy
Statistical and Nonlinear Physics
Authors
Zhi-Jie Zhou, Chang-Hua Hu,