MODELING OF AN INDOOR OBJECT POSITIONING SYSTEM USING VISIBLE LIGHT AND DETERMINING ITS EFFICIENCY

Abstract

This article examines a visible light communication (VLC)–based indoor positioning system designed to overcome the limitations of satellite navigation technologies in enclosed environments. The aim of the study is to analyze VLC-based positioning algorithms, develop their mathematical models, and evaluate coordinate estimation accuracy. The work classifies key algorithms—triangulation, trilateration, fingerprinting, and motion-based methods—and formulates an optical channel model that incorporates both LOS and NLOS components. AOA and RSS methods were simulated in MATLAB, and the influence of noise and SNR on positioning accuracy was investigated, as well as the sensitivity of triangulation to angular measurement errors. Results show that when using three light sources, the RSS algorithm provides an accuracy of 0.15–0.25 m, while AOA demonstrates higher robustness to noise and lower positional deviation. The study offers practical recommendations for integrating VLC positioning with IoT devices and Smart Lighting platforms, emphasizing its applicability in office and industrial indoor environments.