Accuracy Improvement of Attitude Determination Systems Using EKF-Based Error Prediction Filter and PI Controller

Abstract

Accurate attitude and heading reference system (AHRS) play an essential role in navigation applications and human body tracking systems. Using low-cost microelectromechanical system (MEMS) inertial sensors and having accurate orientation estimation, simultaneously, needs optimum orientation methods and algorithms. The error of attitude estimation may lead to imprecise navigation and motion capture results. This paper proposed a novel intermittent calibration technique for MEMS-based AHRS using error prediction and compensation filter. The method, inspired from the recognition of gyroscope’s error and by a proportional integral (PI) controller, can be regulated to increase the accuracy of the prediction. The experimentation of this study for the AHRS algorithm, aided by the proposed prediction filter, was tested with real low-cost MEMS sensors consists of accelerometer, gyroscope, and magnetometer. Eventually, the error compensation was performed by post-processing the measurements of static and dynamic tests. The experimental results present about 35% accuracy improvement in attitude estimation and demonstrate the explicit performance of proposed method.

A Kalman Filter for Nonlinear Attitude Estimation Using Time Variable Matrices and Quaternions

“…Therefore, these idle intervals can be used as a reference. Similar orientation tests were performed by Farhangian and Landry [17] for probing an intermittent calibration technique of an EKF-based attitude determination algorithm.…”

Online Measuring of Robot Positions Using Inertial Measurement Units, Sensor Fusion and Artificial Intelligence

“…Despite the little use of robot calibration methods online, the development of Micro Electromechanical Systems (MEMs) [20]- [22], which has risen the interest of researchers in various areas over time [23], has now encouraged research in robot calibration with IMUs with gyroscopes and accelerometers coupled to measure the robot's TCP orientation at the programmed points [24], [25]. These inertial devices, which used to be large and expensive and were used mostly in the aerospace industry, are already available at prices below one hundred dollars and weighing around twenty grams.…”

Applying a ToF/IMU-Based Multi-Sensor Fusion Architecture in Pedestrian Indoor Navigation Methods

“…Some articles attempted to compensate the heading drift by designing a novel AHRS model. Designing an EKF-based attitude error estimation system [ 16 ], attitude accuracy improvement using decision tree [ 17 ], and RF signals [ 18 ] are discussed and experimented with. In these works, the heading drift compensation is based on the proper antenna and receiver design; however, the methods have been performed in short-term experiments in which their robustness and stability were not proved.…”