Abstract
Aiming at the divergence of heading angle in inertial pedestrian navigation, this paper presents an inertial visual combination pedestrian navigation algorithm based on zero-speed update and binocular vision. Firstly, the position and posture information of the pedestrian in the process of moving is obtained through the binocular visual odometry. Then gait intervals are divided by the generalized Likelihood Ratio Test (GLRT). The position and posture of pedestrians are obtained from a binocular visual odometry in the whole gait interval, and a speed error observation is added in the zero speed interval according to the pedestrian gait characteristics. The Kalman filter is used to estimate the pedestrian speed, position and attitude errors. Finally, the estimation error is used to correct the inertial pedestrian navigation system to improve the navigation positioning accuracy.
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