Abstract:

Through Lipschitz index analyzsis of changes in wavelet factor of the signal and noise in different discrete scales, the signal model of fiber optic gyroscope (FOG) is established. Based on the discrete wavelet transform, a new adaptive filtering algorithm is studied. This algorithm can automatically adjust the threshold values of the wavelet coefficients at different scales in accordance with the energy level of FOG’s output signal.
Thus, a new threshold function is obtained, which weakens wavelet coefficients lower than the threshold and maximally reserves the true signal using a multinomial. Compared with the soft and hard threshold function, the new threshold function shows perfect performance with different SNR. Simulation shows that, compared with traditional fixed threshold wave filtering, the new method can effectively eliminate noise, and improve
FOG’s bias stability, random walking and other technique parameters.

Key words: fiber optic gyroscope, wavelet transform, adaptive, threshold