Hybrid Low-Cost Approach for Quadrotor Attitude Estimation

Abstract

This paper presents a new approach to estimate the orientation of a quadrotor using single low-cost inertial measurement unit (IMU) sensor. The proposed hybrid solution uses two extended Kalman filters (EKF) along with a direction cosine matrix (DCM) algorithm. An EKF utilizes the dynamics of the quadrotor to filter the noise on the body-frame (B-frame) angular rates measured by the three-axis gyroscope sensor. Then, a DCM algorithm uses the filtered gyro signal along with the reading from a three-axis accelerometer and a three-axis magnetometer sensor to estimate the Euler angles. Finally, an additional EKF is presented to enhance the final estimates of the Euler angles. The performance of the proposed hybrid approach is tested and compared with other commonly used methods. Results are presented at the end of the paper to verify the performance of the proposed method. The results show an improvement in the estimated quadrotor's state. Monte Carlo tests are performed to ensure sustained high accuracy estimation.