Abstract:Aiming at the problem of pedestrian trajectory tracking in an unknown environment, to achieve accurate tracking in the magnetic field, we propose an improved trajectory tracking algorithm based on pedestrian dead reckoning. We use a double threshold binarization algorithm to analyze the acceleration data in step estimation, and an adaptive fusion algorithm is proposed in course estimation. This fusion algorithm fuses the angular velocity and acceleration to obtain a heading angle based on the updating differential equation, and then determines the weight of the heading angle and the magnetometer to measure the heading fusion through the magnetic induction intensity threshold. The effectiveness and superiority of the proposed algorithm are validated by an experiment. The experimental results show that the trajectory error obtained by the proposed tracking algorithm is less than 1.1% when the total walk distance is 32 m, and the probability that the positioning error is less than 0.75 m and 1 m is 59% and 80%, which effectively verifies its excellence.