Application of adaptive filtering to digital closed-loop fiber optic gyroscope

When the system mathematical model and the noise statistical properties are not very accurate, the Kalman filtering will reduce the precision of filtering, and even lead to filter divergence.In view of this, adaptive filtering which based on the principle of Kalman filtering is proposed. By comparison experiment, it can be obtained that the adaptive filtering can achieve better filtering effect than Kalman filtering under the condition of the noise statistical properties is not enough accuracy . The filtering effects of adaptive filtering for fiber optic gyroscope (FOG) under different conditions are tested,and obtained that adaptive filtering can improve the output signal of FOG, especially has a significant effect on random white noise. This conclusion has a great use-value and application prospects on improving the accuracy and performance of FOG in the aspects of real-time and accuracy.