Adaptive noise reduction for fiber optic gyroscopes in borehole applications

Fiber Optic Gyroscopes (FOGs) have been investigated and proposed as alternative sensors to magnetometers in borehole surveying applications due to their compactness, ruggedness, low cost and high environmental insensitivity. However, FOGs are subject to high measurement noise from various sources, which deteriorates the performance and quality of FOGs, thus the overall system accuracy is limited. To improve the accuracy of the surveying system, adaptive filtering techniques are utilized to reduce the noise level at the output of the FOG. A Forward Linear Prediction (FLP) filter based on Normalized Least-Mean-Square (NLMS) adaptive algorithm was designed and evaluated using kinematic data. Results show that the FLP filter can suppress the FOG noise to a certain degree and a satisfactory signal-to-noise ratio improvement can be achieved using this method.