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An Algorithm on Gyro Drift Elimination in Personal Navigation System for Firefighter Localization with a Waist-Worn MEMS IMU Sensor System
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- Authors
- Jihye Moon, Hoesung Yang, Kangbok Lee, Seungil Myong
- Issue Date
- 2019-01
- Citation
- 제어로봇시스템학회논문지, v.25, no.1, pp.88-97
- ISSN
- 1976-5622
- Publisher
- 제어로봇시스템학회
- Language
- English
- Type
- Journal Article
- Abstract
- In this paper, we propose five techniques applying the Teager-Kaiser energy operator (TKEO) to eliminate gyro drifts with a waist-worn IMU sensor for infra-less pedestrian dead reckoning (PDR). For providing the service to firefighters in a variety of environments, in this research, we selected a low-cost IMU sensor and used acceleration and gyro. The PDR consists of walking distance and direction estimation processes; in the distance estimation process, the peak and zero crossing detection algorithms were used to detect the steps, and the walking distance was calculated using a fuzzy interface system. For estimating the correct direction, the roll and pitch drifts were eliminated by using an extended Kalman filter. In the process, we developed a yaw drift reduction algorithm that consists of two filters and devised three techniques with TKEO. The drift was modeled as a linear function and reduced with the three techniques, and the extra noises were eliminated by the filters. To compare the existing work, the heuristic drift reduction (HDR) was implemented. In the experiments, after each walk along 580 m and 234 m, the proposed algorithm reported position errors of 0.37% and 0.29%, which exceeded the 2.31% and 6.14% of the HDR.
- KSP Keywords
- Detection algorithm, Direction estimation, Distance and direction, Drift elimination, Drift reduction, Fuzzy interface system(FIS), Gyro drift, IMU sensor, Linear function, Low-cost, MEMS IMU