Intelligent Filter for Accurate Subsurface Heading Estimation Using Multiple Integrated MEMS Sensors

Abstract

In this paper, a sensing system for subsurface application which includes a hybrid fusion methodology and two IMUs was developed. The system improves measurement reliability through the fusion of the signals from each of the sensors. This hybrid fusion method includes two quaternion Kalman filters (QKF), and an intelligent filter whose design is based on the Adaptive Neural Fuzzy Inference System (ANFIS) method. The simulation and test results show the proposed system has improved performance as compared with other systems.