Image Sensor Based Visible Light Positioning System With Improved Positioning Algorithm

We optimize an image sensor-based indoor visible light positioning (VLP) system by improving the positioning algorithm. Specifically, we derive a close-form expression to determine the receiver’s position and orientation using the singular value decomposition (SVD) technique, which speeds up the positioning process and enhances the robustness. Simulation results show that the proposed SVD-based noniterative positioning algorithm is 50–80 times faster than the conventional iterative Levenberg–Marquardt-based algorithm and avoids the possible failures caused by the bad initial guesses. Meanwhile, we theoretically investigate the VLP system by deriving the Cramer–Rao lower bound and the root mean square error bound as the positioning accuracy limit and study the impact of system parameters on the positioning error. Finally, we experimentally evaluate the performance of the improved VLP system. It achieves highly robust and fast 3-D positioning with centimeter-level accuracy.