Open AccessDynamic gyroscope sensors fusion and calibration using Kalman filter
Author(s) -
Mishell D. Lawas,
Sherwin A. Guirnaldo
Publication year - 2018
Publication title -
international journal of engineering and technology
Language(s) - English
Resource type - Journals
ISSN - 2227-524X
DOI - 10.14419/ijet.v7i2.3.9959
Subject(s) - gyroscope , kalman filter , autopilot , gimbal , flight test , sensor fusion , calibration , avionics , control theory (sociology) , computer science , ring laser gyroscope , extended kalman filter , quadcopter , simulation , engineering , artificial intelligence , control engineering , aerospace engineering , physics , control (management) , quantum mechanics
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.