Multidimensional gray-wavelet processing in interferometric fiber-optic gyroscopes

Abstract

A multidimensional signal processing method for a single interferometric fiber-optic gyroscope (IFOG) is proposed, to the best of our knowledge, for the first time. The proposed method, based on a novel IFOG structure with quadrature demodulation, combines a multidimensional gray model (GM) and a wavelet compression technique for noise suppression and sensitivity enhancement. In the IFOG, two series of measured rotation rates are obtained simultaneously: an in-phase component and a quadrature component. Together with the traditionally measured rate, the three measured rates are processed by the combined gray-wavelet method. Simulations show that the intensity noise and non-reciprocal phase fluctuations are effectively suppressed by this method. Experimental comparisons with a one-dimensional GM(1, 1) model show that the proposed three-dimensional method achieves much better denoising performance. This advantage is validated by the Allan variance analysis: in a low-SNR (signal-to-noise ratio) experiment, our method reduces the angle random walk (ARW) and the bias instability (BI) from 1 × 10−2 deg h−1/2 and 3 × 10−2 deg h−1 to 1 × 10−3 deg h−1/2 and 3 × 10−3 deg h−1, respectively; in a high-SNR experiment, our method reduces the ARW and the BI from 9 × 10−4 deg h−1/2 and 5 × 10−3 deg h−1 to 4 × 10−4 deg h−1/2 and 3 × 10−3 deg h−1, respectively. Further, our method increases the dimension of the state-of-the-art IFOG technique from one to three, thus obtaining higher IFOG sensitivity and stability by exploiting the increase in available information.