Research on Gyro’s Drift Forecasting Based on Wavelet MRA and GP/MP
BAO Fei-hu1, HU Chang-hua1, Wang Xin 1, ZHANG Wei1,2, Hu Bo1 (1.Unit 302, Xi’an Research Institute of Hi-tech, Xi’ an 710025, China; 2. School of Electronic Engineering, Xidian University, Xi'an 710076, China)
A novel gyroscopic drift prediction method based on wavelet MRA was proposed. As single model is not suitable for Gyroscopic drift prediction because gyroscopic drift is influenced by different environment factors, and contains complex frequency characteristic. A wavelet decomposition was made to the original drift data and then proper method (Grey prediction model or Markov forecasting model) was chosen to make prediction of the transformed signals according to frequency characteristic. The prediction wanted could be expressed as a combination of forecasting results of the transformed signals. Simulated experiment shows that the hybrid method can increase the prediction precision comparing with Grey-Markov forecasting model.
【CateGory Index】： TN966