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Discrimination of Multiple Objects and Expanding Positioning Area for Indoor Positioning Systems Using Ultrasonic Sensors

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Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 7040))

Abstract

This paper describes new concepts and techniques for an indoor positioning system that uses ultrasonic signals to enhance practicability. This indoor positioning system can be applied to the location detection of a moving object such as a person or a goods trolley over a wide indoor area. The proposed system works by means of ultrasonic signals. This makes it easy to avoid multipath effects because the propagation velocity of ultrasonic signals is much slower than that of radio waves. In addition, ultrasonic signals are not restricted by radio regulations that may differ from country to country. The main feature of our system, developed and presented last year, is that it does not require synchronization between the transmitting and receiving units. This paper describes a system for accommodating multiple moving objects and expanding positioning area. Two techniques, the allocation of a specific ID to each positioning object and the use of a virtual receiving point for ultrasonic signals, were investigated in order to realize the required functions and make the proposed system more practical. The effectiveness of these techniques was confirmed by experiments carried out using ultrasonic sensors installed in the ceiling and model railway trains acting as moving objects on the floor below.

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© 2011 Springer-Verlag Berlin Heidelberg

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Sunaga, H., Hada, T., Akiyama, M., Ioroi, S., Tanaka, H. (2011). Discrimination of Multiple Objects and Expanding Positioning Area for Indoor Positioning Systems Using Ultrasonic Sensors. In: Keyson, D.V., et al. Ambient Intelligence. AmI 2011. Lecture Notes in Computer Science, vol 7040. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-25167-2_4

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  • DOI: https://doi.org/10.1007/978-3-642-25167-2_4

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-25166-5

  • Online ISBN: 978-3-642-25167-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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