TY - GEN
T1 - Research on Pedestrian Inertial Navigation Assisted by Geomagnetic Matching Positioning
AU - Xuan, Ma
AU - Ping, Zhang
AU - Haodong, Li
AU - Zhihong, Deng
N1 - Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - Pedestrian Inertial Navigation System is of great significance in the fields of smart city services, emergency assistance, home health supervision, etc. However, the wearable Micro Inertial Measurement Unit (MIMU) contains relatively high noise and the error of MIMU accumulates with time. This paper proposes a method of pedestrian inertial navigation assisted by geomagnetic matching positioning. According to the measurement of pedestrian inertial navigation based on zero velocity update (PINS-ZUPT) and the geomagnetic matching positioning, the system model of the PINS-ZUPT/Geomagnetic matching navigation with the Kalman Filtering (KF) working in the zero-velocity interval is established in this paper. The positioning errors and velocity errors are gained from the Iterative Closet Contour Point (ICCP) algorithm of the geomagnetic matching positioning and the zero-velocity information respectively, which can be used as the observation values of KF to obtain the optimal pedestrian trajectory and correct accumulated errors. The experiment shows that the average positioning error of integrated navigation is within 1m under the mileage of 140m, reduced by more than 50% relative to PINS-ZUPT, which verifies the effectiveness of the integrated navigation.
AB - Pedestrian Inertial Navigation System is of great significance in the fields of smart city services, emergency assistance, home health supervision, etc. However, the wearable Micro Inertial Measurement Unit (MIMU) contains relatively high noise and the error of MIMU accumulates with time. This paper proposes a method of pedestrian inertial navigation assisted by geomagnetic matching positioning. According to the measurement of pedestrian inertial navigation based on zero velocity update (PINS-ZUPT) and the geomagnetic matching positioning, the system model of the PINS-ZUPT/Geomagnetic matching navigation with the Kalman Filtering (KF) working in the zero-velocity interval is established in this paper. The positioning errors and velocity errors are gained from the Iterative Closet Contour Point (ICCP) algorithm of the geomagnetic matching positioning and the zero-velocity information respectively, which can be used as the observation values of KF to obtain the optimal pedestrian trajectory and correct accumulated errors. The experiment shows that the average positioning error of integrated navigation is within 1m under the mileage of 140m, reduced by more than 50% relative to PINS-ZUPT, which verifies the effectiveness of the integrated navigation.
KW - Geomagnetic Matching Positioning
KW - PINS
KW - PINS-ZUPT/Geomagnetic Matching Navigation
KW - ZUPT
UR - http://www.scopus.com/inward/record.url?scp=85151293491&partnerID=8YFLogxK
U2 - 10.1109/CAC57257.2022.10054774
DO - 10.1109/CAC57257.2022.10054774
M3 - Conference contribution
AN - SCOPUS:85151293491
T3 - Proceedings - 2022 Chinese Automation Congress, CAC 2022
SP - 3065
EP - 3070
BT - Proceedings - 2022 Chinese Automation Congress, CAC 2022
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2022 Chinese Automation Congress, CAC 2022
Y2 - 25 November 2022 through 27 November 2022
ER -
