Improving Coverage and Accuracy in Visible Light Positioning through Ceiling Reflection Modeling

Shota Shimada, Hiroaki Murakami, Ryo Tabata, Kota Tsubouchi, Takuya Sasatani, Yoshihiro Kawahara, Masanori Sugimoto

Abstract: We present a visible light positioning (VLP) method that allows indoor positioning using a smartphone camera with a narrow field of view (FoV). Our method employs omni-directional LEDs, each modulated at a unique frequency, mounted on the ceiling. The system calculates the 2-D position and azimuth of the smartphone by analyzing the brightness of ceiling reflection captured by the user’s smartphone front camera. This approach does not necessitate a direct line-of-sight to the LEDs, effectively overcomes the FoV limitations, and enables positioning over a wider space. We model the ceiling reflection as a transmission path between the LEDs and the ceiling, improving coverage and accuracy of estimation for the user’s position and azimuth compared to previous work. In experiments with two LEDs placed 2.6 m apart, our method covered a space over ten times larger than traditional methods, achieving coverage of $50 \mathbf{m}^{2}$ with a mean absolute error (MAE) in the positioning of 0.46 m and an MAE in azimuth estimation of 13.0°.