A nonlinear attitude estimator for attitude and heading reference systems based on mems sensors

Abstract

In this paper, a nonlinear attitude estimator is designed for an Attitude Heading and Reference System (AHRS) based on Micro Electro-Mechanical Systems (MEMS) sensors. The design process of the attitude estimator is stated with detail, and the equilibrium point of the estimator error model is proved to be asymptotically stable using LaSalle's invariance set theorem through limitation of the range of scalar element of quaternion without affecting practical use. Also, a new Lyapunov candidate function, satisfying continuously differentiable positive definite requirement, is presented to avoid the problems in previous research works. Moreover, the estimation of MEMS gyroscope bias is also inclueded in this estimator. The designed nonlinear attitude estimator is firstly tested in simulation environment and then implemented in an AHRS hardware for further experiments. Finally, the attitude estimation results from the designed AHRS are compared with a high-precision commercial AHRS to validate its estimation performance.

Experimental study of a novel filter structure designed for MEMS‐based sensors in electric vehicles

“…The Coriolis's effect thus causes the mass to move according to a perpendicular trajectory with amplitude proportional to angular rate Ω [6]. MEMS suffer a number of shortcomings such as large measurement noise, null bias and low accuracy [9, 10].…”