Application of different EMD-based denosing methods for fiber optic gyro

Abstract

The drift signal of Fiber Optic Gyroscope (FOG) is often buried in noise. It is difficult to compensate drift directly, and three filtering methods based on Empirical Mode Decomposition (EMD) are applied. Comparison analysis with filtering methods based on EMD, Ensemble Empirical Mode Decomposition (EEMD) and the Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN) is done. Experimental analysis results show that CEEMDAN outperforms than other denoising methods based on EMD and EEMD. The CEEMDAN method saves computational cost, requiring only 29.7% of the sifting iterations of the EEMD. Meanwhile, the rate white noise, bias instability and quantization noise involved in original signal is decreased from 0.0029°/√h , 0.0313°/h and 0.7814° to 0.0003°/√h , 0.0034°/h and 0.0111°, respectively, after applying CEEMDAN method.