Adaptive Attitude Estimation for Low-Cost MEMS IMU Using Ellipsoidal Method

In this article, the attitude estimation for low-cost MEMS inertial measurement units in a smartphone is proposed using adaptive ellipsoidal methods. Accelerometer and magnetometer measurements in an attitude heading reference system (AHRS) are ideally applicable when there is no acceleration and magnetic disturbance. However, when the AHRS is applied to the smartphone, acceleration is frequently occurred by hand movement, and it causes significant attitude errors. Besides, magnetic disturbance from the surrounding environment degrades the heading estimation. In order to improve the attitude accuracy, the acceleration from movement, in addition to the magnetic disturbance is considered in adaptive logic using measurement residuals in this article. The performance of the proposed algorithm is simulated by the computer and tested using the rate table and optical motion capture system compared with the conventional algorithms.