Background & Objective: MEMS sensors are rapidly growing as a sensing technology in
all spheres of science and engineering. MEMS technology is playing an important role in avionics for
miniaturization of systems and MEMS based Inertial Navigation System (INS) is one of the example.
The situational awareness and performance of an aerial vehicle is computed with the help of an INS.
This paper describes the case study for design of MEMS based low cost rugged INS for aerial vehicles.
The 9 Degrees of Freedom (DOF) that are obtained from the sensors provide an inaccurate attitude
information of aerial vehicles due to presence of external accelerations and the gyroscopic drifts
in MEMS sensors. In order to overcome such problems and for the precise and reliable computation
of orientation information, the error characteristics of accelerometers, magnetometers and gyroscopes
have been combined into a sensor fusion algorithm with ‘Kalman Filter’ to compute the accurate orientation
information. The processing has been done on STM32F407VGT6 microcontroller board. An
accuracy of ± 0.1 degrees is achieved for Roll and Pitch and ± 1.0 degrees for Yaw have been obtained.
The experimental results have been obtained in statically (keeping the device in a static position)
and dynamically (rotating the device at different angles along roll, pitch and yaw axis) at room
temperature of 22°C.
Methods: The design is different in a way that it has used a unique combination of trio MEMS sensors
network consisting of FXOS8700CQ Accelerometer, FXAS21000 Gyroscope, FXOS8700CQ
Results: The attitude estimation algorithm has been implemented on the 32-bit microcontroller. The information
data is processed and displayed on 88.9 mm TFT-LCD through Graphical User Interface (GUI).