Visible Light Communication (VLC)-Based Vehicle Positioning Using Optical Retroreflection

Abstract

This thesis proposes a Visible Light Communication (VLC)-based positioning system for urban vehicles, exploiting optical retroreflection to overcome the limitations of Global Nav igation Satellite Systems (GNSS) in dense urban canyons. The system leverages existing retroreflective elements on road vehicles—such as bumper reflectors and license plate hous ings—as passive optical landmarks, thereby eliminating the need for an active transmitter on the target vehicle. A monostatic Angle Diversity Receiver (ADR) onboard the transmit ting vehicle captures the retroreflected echo, enabling simultaneous ranging and channel estimation from a single LED signal. A comprehensive mathematical framework is developed, combining a Lambertian prop agation model with a Corner-Cube Retroreflector (CCR) gain function to yield a 1/𝑑4 round-trip channel law. The vehicle’s position is estimated by formulating a weighted non linear least-squares problem solved via the Levenberg–Marquardt algorithm. The resulting estimates directly feed a Zero-Forcing (ZF) precoder without introducing pilot overhead. Monte Carlo simulations demonstrate sub-decimeter longitudinal accuracy at ranges up to 30 m under nighttime conditions and 10 to 15 m during daytime conditions. These results confirm that the proposed system offers a low-cost, scalable, and GNSS-complementary solution for next-generation Intelligent Transportation Systems (ITS).