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Symmetric Position Drift of Integration Approach in Pedestrian Dead Reckoning with Dual Foot-mounted IMU

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초록

In this paper, the symmetric position drift of the integration approach in pedestrian dead reckoning (PDR) system with dual foot-mounted IMU is analyzed. The PDR system that uses the inertial sensor attached to the shoe is called the IA-based PDR system. Since this system is designed based on the inertial navigation system (INS), it has the same characteristics as the error of the INS, then zero-velocity update (ZUPT) is used to correct this error. However, an error that cannot be compensated perfectly by ZUPT exists, and the trend of the position error is the symmetric direction along the side of the shoe(left, right foot) with the IMU attached. The symmetric position error along the side of the shoe gradually increases with walking. In this paper, we analyze the causes of symmetric position drift and show the results. It suggests the possibility of factors other than the error factors that are generally considered in the PDR system based on the integration approach.

Abstract

In this paper, the symmetric position drift of the integration approach in pedestrian dead reckoning (PDR) system with dual foot-mounted IMU is analyzed. The PDR system that uses the inertial sensor attached to the shoe is called the IA-based PDR system. Since this system is designed based on the inertial navigation system (INS), it has the same characteristics as the error of the INS, then zero-velocity update (ZUPT) is used to correct this error. However, an error that cannot be compensated perfectly by ZUPT exists, and the trend of the position error is the symmetric direction along the side of the shoe(left, right foot) with the IMU attached. The symmetric position error along the side of the shoe gradually increases with walking. In this paper, we analyze the causes of symmetric position drift and show the results. It suggests the possibility of factors other than the error factors that are generally considered in the PDR system based on the integration approach.

참고문헌 (13)

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  2. Chistiakov, I. A., "Pedestrian dead-reckoning algorithms for dual footmounted inertial sensors", Saint Petersburg International Conference on Integrated Navigation Systems (ICINS), pp.1~8 (2019)
  3. 조성윤, "Gyro Signal Processing-based Stance Phase Detection Method in Foot Mounted PDR", Journal of Positioning, Navigation, and Timing, 8(2), pp.49~58 (2019), 사단법인 항법시스템학회[DOI]
  4. Diaz, E. M., "Optimal sampling frequency and bias error modeling for foot-mounted IMUs", 2013 Int. Conf. on Indoor Positioning and Indoor Navigation, pp.1~9 (2013)
  5. Wanda Forczek, "An Evaluation of Symmetry in the Lower Limb Joints During the Able-Bodied Gait of Women and Men", Journal of Human Kinetics, 35(1), pp.47~57 (2012), Walter de Gruyter GmbH[DOI]
  6. E. Foxlin, "Pedestrian Tracking with Shoe-Mounted Inertial Sensors", IEEE Computer Graphics and Applications, 25(6), pp.38~46 (2005), Institute of Electrical and Electronics Engineers (IEEE)[DOI]
  7. Hojin Ju, "A pedestrian dead reckoning system using a foot kinematic constraint and shoe modeling for various motions", Sensors and Actuators A: Physical, 284, pp.135~144 (2018), Elsevier BV[DOI]
  8. Wonho Kang, "SmartPDR: Smartphone-Based Pedestrian Dead Reckoning for Indoor Localization", IEEE Sensors Journal, 15(5), pp.2906~2916 (2015), Institute of Electrical and Electronics Engineers (IEEE)[DOI]
  9. Nilsson, J., "A note on the limitations of ZUPTs and the implications on sensor error modeling", Int. Conf. on Indoor Positioning and Indoor Navigation (2012)
  10. Xiaoji Niu, "Data Fusion of Dual Foot-Mounted IMU for Pedestrian Navigation", IEEE Sensors Journal, 19(12), pp.4577~4584 (2019), Institute of Electrical and Electronics Engineers (IEEE)[DOI]
  11. Prateek, G. V., "Data fusion of dual foot-mounted INS to reduce the systematic heading drift", 2013 4th International Conference on Intelligent Systems, Modelling and Simulation, pp.208~213 (2013)
  12. Wei Shi, "Dual MIMU Pedestrian Navigation by Inequality Constraint Kalman Filtering", Sensors, 17(2), pp.427~ (2017), MDPI AG[DOI]
  13. Hongyu Zhao, "Heading Drift Reduction for Foot-Mounted Inertial Navigation System via Multi-Sensor Fusion and Dual-Gait Analysis", IEEE Sensors Journal, 19(19), pp.8514~8521 (2019), Institute of Electrical and Electronics Engineers (IEEE)[DOI]

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