Filtering Visible Light Reflections with a Single-Pixel Photodetector

Conference paper (2020)

Authors

Ander Galisteo Carlos III University of Madrid, IMDEA Networks Institute
Patrizio Marcocci University of Florence
Marco Zuniga Embedded Systems - EEMCS
Lorenzo Mucchi University of Florence
Borja Genoves Guzman IMDEA Networks Institute
Domenico Giustiniano IMDEA Networks Institute
Research Group
Embedded Systems (EEMCS) (TU Delft)
Copyright: © 2020 Ander Galisteo, Patrizio Marcocci, Marco Zuniga, Lorenzo Mucchi, Borja Genoves Guzman, Domenico Giustiniano
DOI
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https://doi.org/10.1109/SECON48991.2020.9158414
Localization Visible Light Communication Experiments Reflections
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Published Date

2020

Language

English

Reuse Rights

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Faculty

Electrical Engineering, Mathematics and Computer Science

Department

Software Technology

Research Group

Embedded Systems

Abstract

Light-based positioning systems (LPS) are gaining significant attention as a means to provide localization with cm accuracy. Many of these systems estimate the object position based on the received light intensity, and work properly in 'ideal' environments such as large open spaces without obstructions around the light-emitting diode (LED) and the receiver, where reflections are negligible. In more dynamic environments, such as indoor spaces with moving people and city roads with moving vehicles, materials cause a wide variety of reflections. This causes variations in the received light intensity and, as a consequence, gross localization errors in LPS. We propose a new multipath detection technique for improving LPS that does not require the knowledge of the channel impulse response and then, it is suited to be implemented in low-cost positioning receivers that use a single-pixel photodetector. To develop our technique, we (i) analyze the statistical properties of non-line-of-sight (NLOS) components, (ii) develop an automated testbed to study the reflections of different types of surfaces and materials, and (iii) design an algorithm to remove the NLOS components affecting the positioning estimate. Our experimental evaluation shows that, in complex environments, our methodology can reduce the localization error using LEDs up to 93%.