Improving the visible light communication localization system using Kalman filtering with averaging

Two techniques are proposed for improving the accuracy of localization estimation in indoor visible light communication systems, namely, averaging and Kalman filtering with averaging schemes. In the averaging technique, the receiver position is estimated using the received signal strength (RSS) indication method multiple times (e.g., N samples), and the acquired estimations are averaged over all samples. To further improve the localization, the Kalman filtering algorithm is adopted to estimate the received power over N samples, followed by applying the RSS technique on the average received power. The proposed techniques are analyzed mathematically, considering the effects of both line-of-sight (LOS) and first-reflection from non-LOS propagations. The performance of the proposed techniques is determined by evaluating the positioning errors in a typical room. The results are compared to that of the traditional RSS system. Simulation results reveal that an improvement of about 33.3% in the average positioning error is achievable when using the averaging scheme as compared to that of the traditional RSS scheme. This improvement increases to 72.2% when adopting the proposed Kalman filtering scheme.