An Improving Pedestrian Navigation Method Based on Low Cost AHRS

Abstract

Aiming at the problem of the poor observability for the yaw measurement of the foot-mounted attitude heading reference systems (AHRS), this paper presents an indoor pedestrian navigation method using low cost foot-mounted AHRS and waist-mounted compass. Based on this mode, the yaw measured from the waist-mounted compass is used to calculate the attitude transformation matrix for the foot-mounted AHRS, and then the Kalman filter (KF) is used to restrict the error of the inertial sensors when the person is in a stance phase during walk. The experimental results showed that the mean error of the position had been reduced by about 28% when compared with the method without the waist-mounted compass, which demonstrated the effectiveness of the proposed method.