An improved method to integrate low-cost sensors for the navigation of small UAVs

According to the specific application of small low-cost UAVs (Unmanned Air Vehicles), an improved method integrating MEMS gyro, MEMS accelerometer and magnetometers is proposed. Firstly, according to the sensory measurements, navigation information including two sets of Euler angles and the triad of velocity can be acquired. Subsequently, a simplified state space equation without modeling the body angular motion is established and a standard linear observation model is derived to avoid the nonlinear problems. A Correlated Extended Kalman Filter (CEKF) is adopted to improve the performance. Finally, the proposed method is verified using data collected from a flight test. The results show that the proposed method has significantly improved the performance of this integrated system.