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The Standing Calibration Method of MEMS Gyro Bias for Autonomous Pedestrian Navigation System

Published online by Cambridge University Press:  19 October 2016

Yanshun Zhang
Affiliation:
(School of Instrumentation Science and Opto-electronics Engineering, Beihang University, Beijing 100191, China)
Xu Yang*
Affiliation:
(School of Instrumentation Science and Opto-electronics Engineering, Beihang University, Beijing 100191, China)
Xiangming Xing
Affiliation:
(Beijing Aerospace Control Instrument Research Institute, Beijing 100854, China)
Zhanqing Wang
Affiliation:
(School of Automation, Beijing Institute of Technology, Beijing 100081, China)
Yunqiang Xiong
Affiliation:
(School of Instrumentation Science and Opto-electronics Engineering, Beihang University, Beijing 100191, China)
*

Abstract

In a waist-worn Pedestrian Navigation System (PNS) based on Dead-Reckoning (DR), heading drift caused by Micro-Electro-Mechanical System (MEMS) gyro bias is an essential factor affecting DR accuracy. Considering the characteristics of pedestrian navigation and the poor bias repeatability of MEMS gyros, this paper presents a standing calibration method for MEMS gyro bias. The current gyro biases for each boot can be calibrated accurately in the initial stage before walking. Since the attitude angles calculated by the output data from magnetic sensor and accelerometers do not drift, this paper applies the reverse algorithm of attitude updating to calculate the angular velocities of human motion. Then the gyro biases at each moment can be acquired by subtraction operation between the measured angular velocities from gyros and the calculated angular velocities of human motion. Finally, in order to restrain the random error caused by sensor noise, the calculated biases in the initial stage are smoothed, and consequently the optimal estimate of current gyro biases after each boot can be obtained. Still and dynamic turntable experiments and a walking experiment are performed to compare and analyse the proposed method and the Zero Angular Rate Update (ZARU) method. Experimental results show that the proposed method can also calibrate the gyro bias accurately in the case of body swaying.

Type
Research Article
Copyright
Copyright © The Royal Institute of Navigation 2016 

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