Design and Implementation of an AHRS Based on MEMS Sensors and Complementary Filtering

Yangzhu Wang,Xi Chen,Miao Liu,Ning Li

doi:10.1155/2014/214726

Abstract

This paper presents design and implementation of an attitude and heading reference system (AHRS) based on low-cost MEMS sensors and complementary filtering (CF). Different from traditional solutions, information fusion is performed with Euler angles directly, which is more straightforward for understanding; however it proposes many challenges for reaching a stable and accurate estimation as when these angles approach or traverse their range boundaries, estimation may get discontinuous. Thus an effective discontinuity avoiding strategy is suggested in this paper to refine the estimation. Besides, instead of extended Kalman filtering (EKF), CF is utilized for state estimation of AHRS as it features fusion of high-frequency and low-frequency signals. In order to make up for shortcomings of MEMS sensors such as multiple errors, drifts, and bad accuracy, some effective calibration and filtering algorithms are proposed to guarantee agreeable AHRS performance. Also, architecture of the MEMS IMU (inertial measurement unit) and mathematical principles for AHRS solution are explained and implemented in this paper. Meanwhile, experimental comparisons have proved feasibility and acceptable performance of this AHRS design.

Highlights

The attitude and heading reference system (AHRS) provides roll, pitch, and yaw information of carriers with respect to local geographic coordinate frame, which is essentially required for navigation, guidance, state estimation, and control in applications such as UAVs, spacecrafts, tactical missiles, and other commercial or civil fields [1,2,3,4]
With progress of microelectromechanical system (MEMS) technology, AHRS built with low-cost MEMS gyroscopes, accelerometers, and magnetometers [7,8,9,10] have attracted attention of engineers and are replacing traditional attitude estimation systems in many applications as they come more economical, compact, and convenient [5, 11, 12]
Fusing state estimations with Euler angles by an effective antidiscontinuity strategy, this paper presents the design and implementation of an AHRS based on MEMS sensors and complementary filtering (CF)

Summary

Introduction

The attitude and heading reference system (AHRS) provides roll, pitch, and yaw information of carriers with respect to local geographic coordinate frame, which is essentially required for navigation, guidance, state estimation, and control in applications such as UAVs, spacecrafts, tactical missiles, and other commercial or civil fields [1,2,3,4]. Hardware configuration of a MEMS AHRS normally consists of inertial and magnetic sensors, or rather MEMS ICs of rate gyros, accelerometers, and magnetometers [13] of all three Cartesian axes, as well as a data acquisition and processing engine to provide solved attitude and heading solutions [14,15,16,17]. Rotation rate integration of gyroscopes gives good state estimation only in high frequency region, while measurements of MEMS accelerometers and magnetometers only provide good attitude and heading observation in low frequency region. Fusing state estimations with Euler angles by an effective antidiscontinuity strategy, this paper presents the design and implementation of an AHRS based on MEMS sensors and complementary filtering (CF).

General Hardware Architecture of AHRS

Mathematical Background of Attitude Estimation

Design of CF and Attitude Estimation with Euler Angles

Calibration Models of MEMS Sensors

Experiment Result Visualization and Validation

Conclusion