Pitch and Roll Estimation Using Inertial Measurement Unit for Flight Simulator

The flight simulators are required to measure the pitch and roll in real-time under dynamic conditions. This paper designs a roll and pitch measurement system based on an inertial measurement unit composed of a tri-axis accelerometer and a tri-axis gyroscope and proposes an extended Kalman filter-based attitude (roll and pitch) estimation algorithm. The proposed algorithm estimates the external acceleration using a first-order low-pass filtering model and subtracts the estimated external acceleration from the accelerometer measurements. Two different tests were conducted depending on the magnitude of the external acceleration to verify the performance of the proposed algorithm under various dynamic conditions. Besides, three commonly used algorithms, Mahony, Madgwick, and extended Kalman filter, were compared with the proposed algorithm. The Root-Mean-Square error of the algorithm is about 1
^◦
at higher external acceleration conditions, which is smaller than other algorithms, concluding that the algorithm can obtain a more accurate attitude at high acceleration periods.