A Multimode Fusion Visible Light Localization Algorithm using Ambient Lights

With the booming development of green lighting technologies, ubiquitous lighting infrastructures make visible light positioning (VLP) become a promising technology for indoor localization and navigation. However, most existing VLP systems use modulated LEDs as anchors for target localization. LEDs with its customized hardware and modulated information greatly prevent VLP systems from large-scale deployment and limit their widespread applications. Moreover, some VLP systems have the disadvantage of imposing strong restrictions on smartphone such as fixed phone orientation, which is not practical for real-life use. In this paper, we propose a ubiquitous visible light localization (LiLoc) algorithm using ambient lights based on augmented particle filter algorithm. LiLoc directly uses the light intensity fingerprint of ambient light sources (e.g., fluorescent, incandescent, and LEDs) to estimate target location without obtaining modulation information of light sources in buildings. To improve localization accuracy, we introduce a light-intensity trajectory fingerprint matching scheme to calibrate target position. We also develop a beacon identification algorithm based on the inherent visual features of light sources, which are determined by specific manufacturing variations. We combine beacon identification algorithm with PDR to estimate target position in terrible illumination environment (e.g., sunlight interference, beacons sparse deployment, individual beacon damaged/closed, or training fingerprint missing).To reduce power consumption, we design adaptive scheduling mechanism to invoke corresponding algorithms based on the detection result of sunlight interference. The experimental results demonstrate that LiLoc can achieve medium localization errors of 2.2 m in a complex lighting environment with various light sources and sunlight interference.