Design and Implementation of a Centralized Predictive Model Estimation Algorithm with the Fuzzy Approach for In-Motion Alignment of a Low-cost Integrated INS/GPS Inertial Navigation System

The process of computing the true values of the direction cosine matrix (DCM) is one of the important parameters for exact navigation of vehicles. In other words, determination of the directions of the INS vectors in terms of the directions of the reference system (alignment) is one of the important parameters of a navigation system. In order to improve the performance of such systems, this procedure is done according to the inertial measurement unit (IMU) and global positioning system (GPS) data, when the vehicle is in motion. Duo to the stochastic noise and uncertainties in inertial measurement sensors, a data fusion algorithm is used to integrate the outputs of the IMU and GPS sensors. In this paper a novel variant horizon predictive model estimation algorithm is proposed to construct an integrated INS/GPS inertial navigation system. The horizon of the proposed algorithm is calculated based on the vehicle maneuvers. Several vehicular tests have been carried out to assess the long-term performance and accuracy of the proposed navigation algorithm. The results indicate that the proposed algorithm significantly enhances the overall navigation accuracy of low-cost integrated INS/GPS inertial navigation system, in comparison to the conventional Kalman filter algorithm.