TY - GEN
T1 - A pedestrian navigation system based on MEMS inertial measurement unit
AU - Tian, Xiaochun
AU - Chen, Jiabin
AU - Han, Yongqiang
AU - Shang, Jianyu
AU - Li, Nan
N1 - Publisher Copyright:
© 2016 TCCT.
PY - 2016/8/26
Y1 - 2016/8/26
N2 - According to the application requirements of pedestrian navigation, this paper designed a pedestrian navigation system based on micro inertial measurement unit and studied the pedestrian navigation algorithm. The method uses micro inertial measurement unit installed on the foot to measure the pedestrian movement parameters, and then calculate attitude, velocity and position information, meanwhile, multi conditions method is used to detect the zero velocity interval in walking, which trigged the kalman filter and then estimating the system state error parameters and the navigation parameter can be corrected, so that the navigation accuracy can be improved. Finally, rectangular closed loop path experiment by installing the MIMU in pedestrian foot was carried out, the end position error is 1.1% of the total walking distance. Therefore, the experimental results verify the feasibility and effectiveness of the system algorithm, which laid a foundation for furt her pedestrian navigation under complex conditions.
AB - According to the application requirements of pedestrian navigation, this paper designed a pedestrian navigation system based on micro inertial measurement unit and studied the pedestrian navigation algorithm. The method uses micro inertial measurement unit installed on the foot to measure the pedestrian movement parameters, and then calculate attitude, velocity and position information, meanwhile, multi conditions method is used to detect the zero velocity interval in walking, which trigged the kalman filter and then estimating the system state error parameters and the navigation parameter can be corrected, so that the navigation accuracy can be improved. Finally, rectangular closed loop path experiment by installing the MIMU in pedestrian foot was carried out, the end position error is 1.1% of the total walking distance. Therefore, the experimental results verify the feasibility and effectiveness of the system algorithm, which laid a foundation for furt her pedestrian navigation under complex conditions.
KW - Kalman filter
KW - MEMS
KW - Pedestrian navigation
KW - Strapdown inertial navigation
KW - ZUPT
UR - http://www.scopus.com/inward/record.url?scp=84987875886&partnerID=8YFLogxK
U2 - 10.1109/ChiCC.2016.7554183
DO - 10.1109/ChiCC.2016.7554183
M3 - Conference contribution
AN - SCOPUS:84987875886
T3 - Chinese Control Conference, CCC
SP - 5325
EP - 5328
BT - Proceedings of the 35th Chinese Control Conference, CCC 2016
A2 - Chen, Jie
A2 - Zhao, Qianchuan
A2 - Chen, Jie
PB - IEEE Computer Society
T2 - 35th Chinese Control Conference, CCC 2016
Y2 - 27 July 2016 through 29 July 2016
ER -