TY - GEN
T1 - A Multi-Constraint Saturated Acceleration Compensation Method for Pedestrian Inertial Navigation Under High-Dynamic Gaits
AU - Meng, Zhidong
AU - Deng, Zhihong
AU - Wang, Lijuan
AU - Li, Zhe
AU - Zhang, Ping
N1 - Publisher Copyright:
© The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.
PY - 2025
Y1 - 2025
N2 - The pedestrian inertial navigation system (PINS) based on zero-velocity updates (ZUPT) and foot-mounted MIMU could face the problem that the actual acceleration input could exceed the full scale range (FSR) of some commercial MIMU, causing saturation in its readings and loss of accurate measurements when pedestrians proceed with high dynamic gaits such as fast walking and running. Considering the cost and performance of the MIMU, this paper proposes a Multi-Constraint Saturated Acceleration Compensation (MCSAC) method to compensate for the immeasurable values of saturations of the accelerometer. MCSAC constructs the saturated immeasurable values as unknown vectors, establishes an optimization model based on the constraints of step length difference, velocity deviation, and terminal displacement, and uses the interior-point method for optimization. With the optimal values compensated to the raw inertial data, the PINS solutions are corrected. Experiments validating the effectiveness of MCSAC in suppressing errors caused by insufficient FSR under high-dynamic gaits.
AB - The pedestrian inertial navigation system (PINS) based on zero-velocity updates (ZUPT) and foot-mounted MIMU could face the problem that the actual acceleration input could exceed the full scale range (FSR) of some commercial MIMU, causing saturation in its readings and loss of accurate measurements when pedestrians proceed with high dynamic gaits such as fast walking and running. Considering the cost and performance of the MIMU, this paper proposes a Multi-Constraint Saturated Acceleration Compensation (MCSAC) method to compensate for the immeasurable values of saturations of the accelerometer. MCSAC constructs the saturated immeasurable values as unknown vectors, establishes an optimization model based on the constraints of step length difference, velocity deviation, and terminal displacement, and uses the interior-point method for optimization. With the optimal values compensated to the raw inertial data, the PINS solutions are corrected. Experiments validating the effectiveness of MCSAC in suppressing errors caused by insufficient FSR under high-dynamic gaits.
KW - High-Dynamic Gaits
KW - Optimization
KW - Pedestrian Inertial Navigation System
KW - Saturated Acceleration Compensation
UR - http://www.scopus.com/inward/record.url?scp=105006410490&partnerID=8YFLogxK
U2 - 10.1007/978-981-96-2200-9_45
DO - 10.1007/978-981-96-2200-9_45
M3 - Conference contribution
AN - SCOPUS:105006410490
SN - 9789819621996
T3 - Lecture Notes in Electrical Engineering
SP - 463
EP - 474
BT - Advances in Guidance, Navigation and Control - Proceedings of 2024 International Conference on Guidance, Navigation and Control Volume 1
A2 - Yan, Liang
A2 - Duan, Haibin
A2 - Deng, Yimin
PB - Springer Science and Business Media Deutschland GmbH
T2 - International Conference on Guidance, Navigation and Control, ICGNC 2024
Y2 - 9 August 2024 through 11 August 2024
ER -