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Automatic Calibration of Magnetic Tracking.

Authors :
Mingke Wang
Qing Luo
Iravantchi, Yasha
Xiaomeng Chen
Sample, Alanson
Shin, Kang G.
Xiaohua Tian
Xinbing Wang
Dongyao Chen
Source :
MobiCom: International Conference on Mobile Computing & Networking; 2022, p391-404, 14p
Publication Year :
2022

Abstract

Magnetic sensing is emerging as an enabling technology for various engaging applications. Representative use cases include highaccuracy posture tracking, human-machine interaction, and haptic sensing. This technology uses multiple MEMS magnetometers to capture the changing magnetic field at a close distance. However, magnetometers are susceptible to real-world disturbances, such as hard- and soft-iron effects. As a result, users need to perform a cumbersome and lengthy calibration process frequently, severely limiting the usability of magnetic tracking. To remove/mitigate this limitation,we propose MAGIC (MAGnetometer automatIc Calibration), a systematic framework to automatically calibrate both soft- and hard-iron disturbances for a MEMS magnetometer array. To minimize the need for user intervention, we introduce a novel auto-triggering module. Unlike the legacy manual calibration method, MAGIC achieves superior calibration performance (e.g., for tracking applications) with minimal user attention. Via empirical studies, we show MAGIC also incurs marginal overhead and cost, such as a total energy cost of 0.108 J. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
15435679
Database :
Complementary Index
Journal :
MobiCom: International Conference on Mobile Computing & Networking
Publication Type :
Conference
Accession number :
174776745
Full Text :
https://doi.org/10.1145/3495243.3558760