TY - JOUR
T1 - Pedestrian Navigation Method based on PDR/INS KF fusion and Height Update for Three-Dimensional Positioning
AU - Meng, Yujing
AU - Zhao, Liying
AU - Guo, Shuli
AU - Zhang, Lintong
N1 - Publisher Copyright:
© Published under licence by IOP Publishing Ltd.
PY - 2021/5/11
Y1 - 2021/5/11
N2 - Inertial navigation system (INS) and pedestrian dead reckoning (PDR) that use wearable MEMS inertial measurement units (IMUs) can track the location of a pedestrian on two-dimensional (2D) plane. This paper proposes a pedestrian navigation method based on INS/PDR Kalman filter (KF) fusion to calculate the trajectory of a pedestrian in indoor corridors, which can effectively suppress the heading drift. Besides, the height update algorithm is introduced based on the pressure output of a barometer to constrain the height divergence for three-dimensional (3D) positioning. The results of motion experiment show that the navigation accuracy of INS/PDR Kalman filter fusion method is significantly increased compared with the INS. The proposed height update algorithm have better correction effect on the problem of height divergence compared with ZUPT-aided inertial navigation algorithm.
AB - Inertial navigation system (INS) and pedestrian dead reckoning (PDR) that use wearable MEMS inertial measurement units (IMUs) can track the location of a pedestrian on two-dimensional (2D) plane. This paper proposes a pedestrian navigation method based on INS/PDR Kalman filter (KF) fusion to calculate the trajectory of a pedestrian in indoor corridors, which can effectively suppress the heading drift. Besides, the height update algorithm is introduced based on the pressure output of a barometer to constrain the height divergence for three-dimensional (3D) positioning. The results of motion experiment show that the navigation accuracy of INS/PDR Kalman filter fusion method is significantly increased compared with the INS. The proposed height update algorithm have better correction effect on the problem of height divergence compared with ZUPT-aided inertial navigation algorithm.
UR - https://www.scopus.com/pages/publications/85106166383
U2 - 10.1088/1742-6596/1903/1/012064
DO - 10.1088/1742-6596/1903/1/012064
M3 - Conference article
AN - SCOPUS:85106166383
SN - 1742-6588
VL - 1903
JO - Journal of Physics: Conference Series
JF - Journal of Physics: Conference Series
IS - 1
M1 - 012064
T2 - 2021 International Conference on Applied Mathematics, Modelling and Intelligent Computing, CAMMIC 2021
Y2 - 26 March 2021 through 28 March 2021
ER -