• DocumentCode
    3763345
  • Title

    Real-time PDR based on resource-constrained embedded platform

  • Author

    Mohd Nazrin Muhammad;Zoran Salcic;Kevin I-Kai Wang

  • Author_Institution
    Department of Electrical and Computer Engineering, University of Auckland, New Zealand
  • fYear
    2015
  • Firstpage
    779
  • Lastpage
    784
  • Abstract
    Standalone inertial navigation system (INS) in indoor pedestrian positioning is becoming imminent as the researchers exploit its small form factor and low power requirement. This will result in small-size, low-power wearable devices that are not obtrusive to the users and yet provide sufficiently accurate pedestrian localization and tracking within. At this stage, most of the recent INS-based indoor pedestrian positioning systems still have to interface with other computing machines such as a laptop or smartphone to perform computationally demanding algorithms. Most of the existing techniques operate in off-line and not real-time mode. In this paper, we propose a real-time indoor pedestrian dead-reckoning system based on embedded INS. The results show that our system successfully track the distance travelled by pedestrians up to an error of three percent with a position update interval less than a second.
  • Keywords
    "Acceleration","Sensors","Real-time systems","Gravity","Computers","Inertial navigation","Performance evaluation"
  • Publisher
    ieee
  • Conference_Titel
    Sensing Technology (ICST), 2015 9th International Conference on
  • Electronic_ISBN
    2156-8073
  • Type

    conf

  • DOI
    10.1109/ICSensT.2015.7438502
  • Filename
    7438502