Abstract
This paper presents a novel approach to INS velocity aiding in autonomous pedestrian navigation systems with body-mounted IMU. The proposed solution uses a kinetic model of human gait as a virtual velocity sensor. In this paper we show how an understanding of INS error dynamics and knowledge of human motion help to curb the divergence of INS computed horizontal velocity and tilt errors. Heading and heading gyro drift cannot be corrected with this method and require some additional procedures. This algorithm is based on Kalman filter and can be adapted for implementation on real-time pedestrian navigation systems equipped with 6 DOF IMU. The algorithm accuracy performance was investigated using data from indoor walking tests.
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