A zero velocity intervals detection algorithm based on sensor fusion for indoor pedestrian navigation

The Zero-velocity Update (ZUPT) algorithm is commonly used to suppress the error growth of foot-mounted indoor pedestrian navigation system. To use the ZUPT, it is necessary to detect zero velocity intervals reliably. The traditional zero velocity intervals detection algorithms cannot provides good performance at high gait speeds. In this paper, we propose a novel zero velocity intervals detection approach based on sensors fusion. In this method, the measurements of accelerometer, gyroscope and pressure sensor are combined together to detect the zero velocity intervals. Then the adaptive threshold is developed to improve the accuracy of detection under various motion modes. The performance of the proposed method is examined in real indoor scenarios. The results show that the proposed method can correctly detect the zero velocity intervals and improve the accuracy of positioning.