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Nowadays, GPS (global positioning system) receivers are aided by INS (inertial navigation systems) to achieve more precision and stability in land-vehicular navigation. KF (Kalman filter) is a conventional method which is used for the navigation system to estimate the navigational parameters, when INS measurements are fused with GPS data. However, new generation of INS, which relies on MEMS (micro-electro-mechanical systems) based low-cost IMUs (inertial measurement units) for the land navigation systems, decreases the accuracy and the robustness of navigation system due to their inherent errors. This paper provides a new method for fusing the low-cost IMU and GPS measurements. The proposed method is based on KF aided by AFIS (adaptive fuzzy inference systems) as a promising solution to overcome the mentioned problems. The results of this study show the efficiency of the proposed method to reduce the navigation system errors in comparison with KF alone.

Low-Cost GPS/INS Integrated Land-Vehicular Navigation System for Harsh Environments Using Hybrid Mamdani AFIS/KF Model