Abstract
Attitude and heading reference system (AHRS) is the term used to describe a rigid body’s angular orientation in three-dimensional space. This paper describes an AHRS determination and control system developed for navigation systems by integrating gyroscopes, accelerometers, and magnetometers signals from low-cost MEMS-based sensors in a complementary adaptive Kalman filter. AHRS estimation based on the iterative Kalman filtering process is required to be initialized first. A new method for AHRS initialization is proposed to improve the accuracy of the initial attitude estimates. Attitude estimates derived from the initialization and iterative adaptive filtering processes are compared with the orientation obtained from a high-end reference system. The improvement in the accuracy of the initial orientation as significant as 45% is obtained from the proposed method as compared with other selected techniques. Additionally, the computational process is reduced by 96%.
Highlights
A New Perspective on Low-CostThe determination of Attitude and Heading Reference System (AHRS) involves several fields like navigation, control, motion tracking [1,2,3], personal navigation [4,5], robotics [6], and virtual reality systems [7]
This paper proposes a new method for AHRS determination and control system using Micro-Electro-Mechanical System (MEMS)-based low-cost and small-scale sensors for tracking and monitoring moving object-related applications
The extended versionorientation of the Kalman filter (EKF)-based attitude estimation process is used for the initialization under stationary conditions
Summary
A New Perspective on Low-CostThe determination of Attitude and Heading Reference System (AHRS) involves several fields like navigation, control, motion tracking [1,2,3], personal navigation [4,5], robotics [6], and virtual reality systems [7]. Several AHRS determination and control technologies in use need an external source to obtain orientation information [1]. The inertial system computes the attitude using self-contained sensors that only respond to inertial forces. The attitude is derived from the integration of rate gyroscope data in an inertial system. Rate gyroscopes are prone to bias and random drifts and this leads to unbounded attitude errors. The rapid development of Micro-Electro-Mechanical System (MEMS) inertial sensors in precision, accuracy, size, weight, and cost make it ideal for developing a small-scale and lowcost AHRS determination and control system. Inexpensive MEMS gyroscopes are low-performance, and using these gyroscopes may result in unbounded attitude errors
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