| Citation: | DAI Hongde, ZHANG Xiaoyu, ZHENG Baidong, et al. Inertial pedestrian navigation algorithm based on zero velocity update and attitude self-observation[J]. Journal of Beijing University of Aeronautics and Astronautics, 2022, 48(7): 1135-1144. doi: 10.13700/j.bh.1001-5965.2021.0037(in Chinese)
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Aiming at the problem of reduced navigation accuracy caused by the divergence of the heading angle in inertial pedestrian navigation, an inertial pedestrian navigation algorithm based on zero velocity correction and attitude self-observation is proposed. A four-condition zero velocity detection algorithm is used to detect the zero velocity interval in the walking gait. In the detected zero velocity interval, the principle of the zero velocity update is used to construct the observation of the velocity error; the characteristic that only gravity acts and the heading angle remains unchanged in the zero velocity intervals is used to construct the observation of the attitude angle error. Then, the attitude angle, velocity and position error in the zero velocity interval are estimated by Kalman filtering. The error correction of pedestrian navigation is carried out using the obtained state estimation to further improve the accuracy of inertial pedestrian navigation. Actual walking experiments show that in the rectangular path, the average value of navigation trajectory relative error of this algorithm is only 0.98%, which is reduced by 78.11% compared with the zero velocity update algorithm and the standard deviation of navigation trajectory error of this algorithm is only 0.14 m, which is reduced by 88.62% compared with the zero velocity update algorithm. In the closed loop path of the classical 400 m playground, the relative position error of the solution end point is only 1.18%. The solved trajectory has a high degree of matching with the actual trajectory, which has good application value.
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