Attitude Estimation of Quadrotor UAV Based on QUKF

Abstract

Toward the quadcopter unmanned aerial vehicle (UAV) attitude measurement problem, to improve the accuracy of acquisition of vehicle attitude parameters, and ensure accuracy of subsequent attitude control, the Quaternion-based Unscented Kalman filter (QUKF) data fusion method is presented. This attitude measurement system uses STM32F103 as the central controller, MPU6050 with integrated accelerometer and gyroscope, and magnetometer HMC5883l as the measurement sensor. Coordinate Rotation Relationships for the Attitude Heading Reference System (AHRS) in Quaternions, combining Unscented Kalman Filter (UKF) to Fuse Low-Cost Attitude Measurement Systems, tracking estimation of the genuine attitude of the vehicle. High-precision sensor measurements as real values, by comparing with Extended Kalman Filter (EKF), Complementary Filter (CF), and genuine values to validate and analyze the effectiveness of the algorithm applied to the low-cost attitude measurement system. Experimental results show that the low-cost attitude measurement system using quaternions as state variables combined with UKF can accurately estimate attitude information, providing precise attitude information for subsequent attitude control of UAVs.

Keywords

• Unscented Kalman filter
• quaternion
• quadrotor UAV
• attitude estimation
• data fusion