A knowledge-based step length estimation method based on fuzzy logic and multi-sensor fusion algorithms for a pedestrian dead reckoning system

Ying-Chih Lai, Chin Chia Chang, Chia Ming Tsai, Shih Ching Huang, Kai-Wei Chiang

Research output: Contribution to journalArticle

5 Citations (Scopus)

Abstract

The demand for pedestrian navigation has increased along with the rapid progress in mobile and wearable devices. This study develops an accurate and usable Step Length Estimation (SLE) method for a Pedestrian Dead Reckoning (PDR) system with features including a wide range of step lengths, a self-contained system, and real-Time computing, based on the multi-sensor fusion and Fuzzy Logic (FL) algorithms. The wide-range SLE developed in this study was achieved by using a knowledge-based method to model the walking patterns of the user. The input variables of the FL are step strength and frequency, and the output is the estimated step length. Moreover, a waist-mounted sensor module has been developed using low-cost inertial sensors. Since low-cost sensors suffer from various errors, a calibration procedure has been utilized to improve accuracy. The proposed PDR scheme in this study demonstrates its ability to be implemented on waist-mounted devices in real time and is suitable for the indoor and outdoor environments considered in this study without the need for map information or any pre-installed infrastructure. The experiment results show that the maximum distance error was within 1.2% of 116.51 m in an indoor environment and was 1.78% of 385.2 m in an outdoor environment.

Original languageEnglish
Article number70
JournalISPRS International Journal of Geo-Information
Volume5
Issue number5
DOIs
Publication statusPublished - 2016 May 1

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Sensor data fusion
pedestrian
fuzzy mathematics
estimation method
logic
Fuzzy logic
sensor
Sensors
knowledge
costs
Costs
Navigation
walking
cost
Calibration
infrastructure
navigation
demand
experiment
ability

All Science Journal Classification (ASJC) codes

  • Geography, Planning and Development
  • Computers in Earth Sciences
  • Earth and Planetary Sciences (miscellaneous)

Cite this

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title = "A knowledge-based step length estimation method based on fuzzy logic and multi-sensor fusion algorithms for a pedestrian dead reckoning system",
abstract = "The demand for pedestrian navigation has increased along with the rapid progress in mobile and wearable devices. This study develops an accurate and usable Step Length Estimation (SLE) method for a Pedestrian Dead Reckoning (PDR) system with features including a wide range of step lengths, a self-contained system, and real-Time computing, based on the multi-sensor fusion and Fuzzy Logic (FL) algorithms. The wide-range SLE developed in this study was achieved by using a knowledge-based method to model the walking patterns of the user. The input variables of the FL are step strength and frequency, and the output is the estimated step length. Moreover, a waist-mounted sensor module has been developed using low-cost inertial sensors. Since low-cost sensors suffer from various errors, a calibration procedure has been utilized to improve accuracy. The proposed PDR scheme in this study demonstrates its ability to be implemented on waist-mounted devices in real time and is suitable for the indoor and outdoor environments considered in this study without the need for map information or any pre-installed infrastructure. The experiment results show that the maximum distance error was within 1.2{\%} of 116.51 m in an indoor environment and was 1.78{\%} of 385.2 m in an outdoor environment.",
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A knowledge-based step length estimation method based on fuzzy logic and multi-sensor fusion algorithms for a pedestrian dead reckoning system. / Lai, Ying-Chih; Chang, Chin Chia; Tsai, Chia Ming; Huang, Shih Ching; Chiang, Kai-Wei.

In: ISPRS International Journal of Geo-Information, Vol. 5, No. 5, 70, 01.05.2016.

Research output: Contribution to journalArticle

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