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Ultrasonic localization method based on receiver array optimization schemes

Author

Listed:
  • Xiaonan Luo
  • Hucheng Wang
  • Suqing Yan
  • Jianming Liu
  • Yanru Zhong
  • Rushi Lan

Abstract

Ultrasonic localization system using trilateration has been adopted in various types of full-enclosed and semi-enclosed space. For small-scale or enclosed scenarios, there is an important phenomenon, that is, the ultrasonic wave may rapidly reflect back and forth between the walls to form different normal waves during the process of propagation, which may break the inverse square law of sound intensity (the sound intensity in free space is inversely proportional to the square of the distance). The other problem is that the sound intensity of some local corner points are obviously stronger than those points near the acoustic source, which may confuse the ultrasonic receivers and bring significant differences in measurement errors. To avoid excessive errors influence for the positioning accuracy, in this article, a novel ultrasonic localization method based on receiver array optimization schemes is reported. The main purpose is to activate the ultrasonic receiver in the area as well as shield the ultrasonic receiver outside the area. The system error will be reduced based on this method, and most of the redundant data will be eliminated. The simulation results are visualized and compared with the existing methods. The positioning accuracy measured by our method is increased significantly.

Suggested Citation

  • Xiaonan Luo & Hucheng Wang & Suqing Yan & Jianming Liu & Yanru Zhong & Rushi Lan, 2018. "Ultrasonic localization method based on receiver array optimization schemes," International Journal of Distributed Sensor Networks, , vol. 14(11), pages 15501477188, November.
    • Handle: RePEc:sae:intdis:v:14:y:2018:i:11:p:1550147718812017
    DOI: 10.1177/1550147718812017
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    References listed on IDEAS

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    1. Yan Wang & Min Li & Lin Bai & Tielian Fu & Fengyue Gao, 2018. "Normalized amplitude of channel state information: The robust parameter for indoor localization in wireless sensor networks," International Journal of Distributed Sensor Networks, , vol. 14(2), pages 15501477187, February.
    2. Qu Wang & Haiyong Luo & Aidong Men & Fang Zhao & Xile Gao & Jie Wei & Yuexia Zhang & Yan Huang, 2018. "Light positioning: A high-accuracy visible light indoor positioning system based on attitude identification and propagation model," International Journal of Distributed Sensor Networks, , vol. 14(2), pages 15501477187, February.
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