This work addresses the design and implementation of an integrated navigation system that combines Global Positioning System (GPS), Inertial Navigation System (INS), and Kalman Filter (KF). The system is designed using Arduino microcontroller and Gy80 type Inertial Measurement Unit (IMU). The aim of the paper is to provide accurate navigation and positioning information for autonomous vehicles without relying solely on GPS data. The KF is used to combine the data from both GPS and INS and to estimate the true position and orientation of the system. The experimental results show that the integrated navigation system provides accurate and reliable position and orientation information for autonomous vehicles. The system can also work in challenging environments, such as areas with poor GPS signal quality or GPS signal outage. The proposed system can be used in various applications, such as unmanned aerial vehicles and robotics.


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    Title :

    Integrated Land Vehicle Navigation System Using Kalman Filtering


    Contributors:
    Hakaya, A. (author) / Tresh, A. (author) / Salim, A. (author) / Maklouf, O. (author)


    Publication date :

    2024-05-12


    Size :

    805262 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English




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