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1 / 2023-06-30 18:23:01
Through-wall localization based on exponential moving average and distance decay elliptic model
wireless sensor network,received signal strength,radio tomographic imaging,exponential moving average,elliptic model
Special Sessions > SS19 - Artificial Intelligence for Sensor Data analytics
Final Paper
Tierui Liu / Nanjing University of Science and Technology；School of Mechanical Engineering
Manyi Wang / Nanjing University of Science and Technology；School of Mechanical Engineering
Taiyun Cheng / Nanjing University of Science and Technology；School of Mechanical Engineering
As a new and important technology in wireless sensor networks, wireless tomography has been widely concerned by researchers at home and abroad. However, the target positioning accuracy in RTI still has a lot of room for improvement. In indoor environments, signals need to be propagated through the wall and reflected through the wall, which will produce multipath effect and affect the positioning accuracy of the target. In this paper, a data preprocessing method and an improved range-attenuated elliptical weight model are proposed to further improve the target positioning accuracy. The data preprocessing method selects exponential moving average algorithm to process the received signal strength (RSS), which can effectively reduce the multipath effect. The new elliptic model of distance attenuation considers the distance between pixels and sensor nodes. The effects of line-of-sight (LOS) and non-line-of-sight (NLOS) paths are also considered. Experimental results show that the root mean square error of position can be controlled at 0.31m.
Important Date

  • Conference Date

    Nov 02

    2023

    to

    Nov 04

    2023

  • Dec 15 2023

    Draft paper submission deadline

  • Dec 20 2023

    Registration deadline

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IEEE Instrumentation and Measurement Society
Xidian University
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