Indoor Visible Light Localization Based on Finite State Markov Chain

In the study of indoor visible light localization, the variance of the RSS(Received Signal Strength) distribution will be affected by environmental noise, resulting in a larger range of RSS value fluctuations. A method is proposed to decompose the RSS value into the disturbance component caused by the target and the noise component caused by the environment, and then a linear transfer model based on the finite state Markov chain is used to extract the disturbance component in RSS value. Finally, the DTW(Dynamic Time Warping) algorithm is used to match the real-time disturbance component with the fingerprint database to achieve target positioning.