Research on MIMU adaptive filter method based on wavelet analysis

Micro Inertia Measurement Unit based on MEMS component, is the core of the Micro Navigation System. Its accuracy has a crucial effect on system precision. Eliminating stochastic noise in MIMU signal is of great significance to increase the system accuracy. Aiming at the different characteristics showed at every scale space after wavelet analysis on MIMU signal, an adaptive filtering method with decomposition level and threshold value self-adaptive adjusting is proposed by this paper. The compactly supported Daubechies4 (db4) orthogonal wavelet is applied to decompose the signal in multi-scale space with self-adaptive level based on white noise sequence check. An improved self-adaptive threshold decision making is adopt for threshold filtering. After removing high frequency detail items generated by stochastic noise, inverse wavelet transform is applied to reconstruct the original signal. The experimental results indicate that the method can eliminate MIMU stochastic noise effectively and achieve satisfactory accuracy. And the algorithm is simple and practical.