2021•SensorsOpen access

A New Perspective on Low-Cost MEMS-Based AHRS Determination

Néda Navidi, Rene Jr. Landry

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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%.

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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%.

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Available 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%.

Key concepts: Attitude and heading reference system, Accelerometer, Initialization, Kalman filter, Orientation (vector space), Control theory (sociology), Gyroscope, Computer science

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