Denoising of fiber optic gyroscope signal by unsupervised adaptive filtering

Angle random walk (ARW) is the noise component at the output of a fiber optic gyroscope (FOG) and it affects the FOG short-term accuracy. Using only the noise property described by random walk coefficient, we developed an unsupervised adaptive filter (UAF) for suppressing the noise. Theoretical analysis illuminates that UAF performs as good as the best FIR filter in the sense of means square. Experimental results both in stationary and non-stationary cases show that UAF is more effective than wavelet denoising and that based on fast Fourier transform.