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Error Compensation Method for Pedestrian Navigation System Based on Low-Cost Inertial Sensor Array

Authors :
Lijia Cao
Xiao Luo
Lei Liu
Guoqing Wang
Jie Zhou
Source :
Sensors, Vol 24, Iss 7, p 2234 (2024)
Publication Year :
2024
Publisher :
MDPI AG, 2024.

Abstract

In the pedestrian navigation system, researchers have reduced measurement errors and improved system navigation performance by fusing measurements from multiple low-cost inertial measurement unit (IMU) arrays. Unfortunately, the current data fusion methods for inertial sensor arrays ignore the system error compensation of individual IMUs and the correction of position information in the zero-velocity interval. Therefore, these methods cannot effectively reduce errors and improve accuracy. An error compensation method for pedestrian navigation systems based on a low-cost array of IMUs is proposed in this paper. The calibration method for multiple location-free IMUs is improved by using a sliding variance detector to segment the angular velocity magnitude into stationary and motion intervals, and each IMU is calibrated independently. Compensation is then applied to the velocity residuals in the zero-velocity interval after zero-velocity update (ZUPT). The experimental results show a significant improvement in the average noise performance of the calibrated IMU array, with a 3.01-fold increase in static noise performance. In the closed-loop walking experiment, the average horizontal position error of a single calibrated IMU is reduced by 27.52% compared to the uncalibrated IMU, while the calibrated IMU array shows a 2.98-fold reduction in average horizontal position error compared to a single calibrated IMU. After compensating for residual velocity, the average horizontal position error of a single IMU is reduced by 0.73 m, while that of the IMU array is reduced by 64.52%.

Details

Language :
English
ISSN :
14248220
Volume :
24
Issue :
7
Database :
Directory of Open Access Journals
Journal :
Sensors
Publication Type :
Academic Journal
Accession number :
edsdoj.99c6c74d9e5473abf4ff76072543d8e
Document Type :
article
Full Text :
https://doi.org/10.3390/s24072234