Dynamic gyroscope sensors fusion and calibration using Kalman filter

  • Authors

    • Mishell D. Lawas
    • Sherwin A. Guirnaldo
    2018-03-08
    https://doi.org/10.14419/ijet.v7i2.3.9959
  • Unmanned Aerial Vehicle, Sensor Fusion, Kalman Filters, Microcontrollers, Smartphone.

  • Abstract

    The stability of an Unmanned Aerial Vehicle (UAV) during actual flight conditions is one parameter that is very important in systems design in Avionics. In this research, two sensors, the autopilot microcontroller and the smartphone gyroscope sensing mechanism, are fused together and calibrated to monitor the flying behavior of the UAV prior to actual test flights. The two fused sensors and installed inside the UAV for relatively increased sensing accuracy and best flight monitoring capabilities. A Kalman filter is used as fusion technique and a Stewart Motion tracker is also used to test the ruggedness and accuracy of the fused sensor system. Experiment results show that fused system can give an overall mean square error or 1.9729.

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  • How to Cite

    D. Lawas, M., & A. Guirnaldo, S. (2018). Dynamic gyroscope sensors fusion and calibration using Kalman filter. International Journal of Engineering & Technology, 7(2.3), 18-21. https://doi.org/10.14419/ijet.v7i2.3.9959

    Received date: 2018-03-08

    Accepted date: 2018-03-08

    Published date: 2018-03-08