Attitude Estimation of Rigid Bodies Using MEMS Inertial Sensors

The attitude estimation of the rigid bodies using MEMS inertial sensors is presented. The bias of gyros and accelerometers are tracked by a state estimation algorithm in real-time. The algorithm uses characteristics of the sensor noise to automatically recognize motionless periods and update the sensor's bias level without any dependency on application specific parameters, frequency separation between the signal of interest and the sensor noise, or a high-level system model. Then the attitude estimation algorithm that fuses data from rate gyros and accelerometers is proposed. Based on the kinematics of the body and the Newton's force law, the modified Rodrigues parameter is represented in place of quaternion. We describe rotation without encountering singularity between the modified Rodrigues parameters and their shadow parameters. And the attitude is estimated by Extended Kalman filter under low acceleration, meanwhile the situation of high acceleration is considered. Finally, the proposed estimation algorithm is tested, the simulation results are provided to show the effectiveness of the proposed algorithm.