Sensor Fusion Algorithm by Complementary Filter for Attitude Estimation of Quadrotor with Low-Cost IMU

This paper proposes a sensor fusion algorithm by complementary filter technique for attitude estimation of quadrotor UAV using low-cost MEMS IMU. Angular rate from gyroscope tend to drift over a time while accelerometer data is commonly effected with environmental noise. Therefore, high frequency gyroscope signal and low frequency accelerometer signal is fused using complementary filter algorithm. The complementary filter scaling factor K1=0.98 and K2=0.02 are used to merge both gyro and accelerometer. The results show that the smooth roll, pitch and yaw attitude angle can be obtained from the low cost IMU by using proposed sensor fusion algorithm.