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The accurate Attitude Heading Reference System(AHRS) is an important apart ofthe UAV reliable flight system. Aiming at the application scenarios of nearground navigation of small-UAV, this paper establishes a loose couple errormodel of the gyroscope/accelerometer/magnetometer, and presents an improvedFastEuler Double-Layer Kalman Filter algorithm. Using low-cost devices whichinclude MEMS Inertial Measurement Units(IMU) and magnetometers, this paperconstructs the AHRS hardware and software systems of UAV, and designs theoffline and real-time verification platforms. Moreover, the attitude changes ofUAV is analyzed by the simulation and flight test, respectively. In addition,an adaptive factor is used to adjust the measurement noise covariance in orderto eliminate the harmful effects of linear acceleration in the accelerometer,which is solved the roll and ptich angle. The experimental comparison with theComplementary Filter shows that the proposed algorithm can provide accurateattitude information when UAV is flying, which improves the accuracy andreliability of attitude solution, and removes the influence the gyro bias forthe attitude estimation.

An improved FastEuler-DLKF small-UAV AHRS algorithm