Pedestrian inertial positioning is an effective means when satellites fail. Heading accuracy determines the performance of pedestrian inertial positioning. To realize an accurate positioning, a heading drift correctio...Pedestrian inertial positioning is an effective means when satellites fail. Heading accuracy determines the performance of pedestrian inertial positioning. To realize an accurate positioning, a heading drift correction method was proposed. An in-situ active rotation is performed before autonomous positioning, and the error compensation coefficient of biaxial geomagnetic measurement is obtained by using the ellipse fitting correction method to achieve effective suppression of external environmental geomagnetic interference. The corrected biaxial geomagnetic measurement information is used to directly calculate the heading information and combine it with the peak stride detection method and linear step estimation model to achieve autonomous positioning of pedestrians. To verify the effectiveness and stability of the algorithm, several sets of experiments on the autonomous positioning of pedestrians are carried out in an outdoor environment. The experimental results show that the average deviation between the starting point and the endpoint of the proposed algorithm’s positioning trajectory accounts for 0.95% of the total travel in the 150 m positioning experiments.展开更多
文摘Pedestrian inertial positioning is an effective means when satellites fail. Heading accuracy determines the performance of pedestrian inertial positioning. To realize an accurate positioning, a heading drift correction method was proposed. An in-situ active rotation is performed before autonomous positioning, and the error compensation coefficient of biaxial geomagnetic measurement is obtained by using the ellipse fitting correction method to achieve effective suppression of external environmental geomagnetic interference. The corrected biaxial geomagnetic measurement information is used to directly calculate the heading information and combine it with the peak stride detection method and linear step estimation model to achieve autonomous positioning of pedestrians. To verify the effectiveness and stability of the algorithm, several sets of experiments on the autonomous positioning of pedestrians are carried out in an outdoor environment. The experimental results show that the average deviation between the starting point and the endpoint of the proposed algorithm’s positioning trajectory accounts for 0.95% of the total travel in the 150 m positioning experiments.
