The characteristics of noise in fiber-optic gyros are analyzed quantitatively. Based on its physical characteristics and on autocorrelation function evidence, the noise is modeled as the addition of fractal Brownian motion (FBM) and Gaussian white noise (GWN). The value of self-similarlity parameter H in FBM and the intensity of GWN, , in the model are robustly determined with an algorithm based on an orthonormal wavelet transform, which demonstrates well the coexistence of the long- and short-term correlation components of the gyro noise. Moreover, it is revealed that FBM dominates the gyro noise, whereas the GWN is minor.
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