Modelling inertial measurement unit error parameters for an unmanned air vehicle

Abstract

This paper demonstrates a study that focuses on the modeling, design, and realization of an Inertial Measurement Unit (IMU) component for the use of Unmanned Aerial Vehicles (UAV). The experimental data is obtained by multiple flights conducted by the realized UAV (Teknofest–SEMRUK team UAV). The structure is remodeled for increasing the accuracy, and performance of the UAV after the conducted flights. Noise parameters are estimated throughout the Allan variance analysis. MEMS technology-based capacitive-type accelerometers and gyroscopes are preferred. This paper also discusses the error types and compares the real data with the modeled simulation data. Systematic errors of the inertial sensors are simulated according to their datasheet parameters. Sensor filters and noise are modeled and they are also implemented in the simulation. Simulation results and UAV measurements are compared to observe the efficiency of modeling. A complementary filter is presented and combined with a magnetometer, accelerometer, and gyroscope to obtain the ultimate design. The comparison showed a satisfactory agreement among the complementary filter measurements and UAV measurements in the stable position and the results presented.