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Research
Jianhua Shao
Nanjing Normal University
Corresponding Author
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In the study of indoor visible light localization, the variance of the RSS(Received Signal Strength) distribution will be affected by environmental noise, resulting in a larger range of RSS value fluctuations. A method is proposed to decompose the RSS value into the disturbance component caused by the target and the noise component caused by the environment, and then a linear transfer model based on the finite state Markov chain is used to extract the disturbance component in RSS value. Finally, the DTW(Dynamic Time Warping) algorithm is used to match the real-time disturbance component with the fingerprint database to achieve target positioning.
Keywords
Indoor visible light localization, Finite Markov chain, Disturbance component
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This is a preprint, a preliminary version of a manuscript that has not completed peer review at a journal. Research Square does not conduct peer review prior to posting preprints. The posting of a preprint on this server should not be interpreted as an endorsement of its validity or suitability for dissemination as established information or for guiding clinical practice.
Research
Jianhua Shao
Nanjing Normal University
Corresponding Author
Badges
Prescreen
This manuscript passed our Prescreen assessment
Complete author information
Appropriate declaration statements
Potential risks to human health
Prescreen
History
CURRENT STATUS: Posted
Version 1
Posted 12 Jan, 2021
No community comments so far
Metrics
Comments: 0
PDF Downloads: ...
HTML Views: ...
License:
This work is licensed under a CC BY 4.0 License. Read Full License
In the study of indoor visible light localization, the variance of the RSS(Received Signal Strength) distribution will be affected by environmental noise, resulting in a larger range of RSS value fluctuations. A method is proposed to decompose the RSS value into the disturbance component caused by the target and the noise component caused by the environment, and then a linear transfer model based on the finite state Markov chain is used to extract the disturbance component in RSS value. Finally, the DTW(Dynamic Time Warping) algorithm is used to match the real-time disturbance component with the fingerprint database to achieve target positioning.
Figure 1
Figure 2
Figure 3
Figure 4
Figure 5
Figure 6
Figure 7
Figure 8
Figure 9
Figure 10
Figure 11
Figure 12
The full text of this article is available to read as a PDF.
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