Application of multiple-scale variable step least mean square adaptive algorithm to fiber optic gyroscope data processing

In order to get a better filtering result for the output of data of fiber optic gyroscope (FOG), an adaptive LMS Algorithm with Variable Step and Multi-scale Wavelet Transform(MVSLMS) was applied to FOG data processing. A MVSLMS filter was constructed on the basis of the characteristics of FOG data, and the specific implementation steps were proposed. The measured static data, vibration test data and rate test data of FOG were filtered. The experimental results show that the proposed algorithm significantly inhibits the random noise of FOG. Compared with the conventional LMS algorithm, after filtered with new algorithm, the zero drift stability of FOG output data is decreased by 72% under static condition, 91.5%, 77.4% and 96.5% before vibration, in vibration and after vibration. The standard deviation of FOG output data is decreased by 54.4% under rate test condition. The filter results under rocking motion condition confirmed that the proposed algorithm has better signal tracking capability.