A boosted positioning model for miso VLC system under a shadowing scenario

Abstract

There are various positioning algorithms proposed for Visible Light Communication (VLC) which require at least three “alive” transmitters to locate the object’s position. In terms of indoor scenarios, the shadowing of Line-of-sight (LOS) signal leads to insufficient information for positioning in a VLC system. This work proposes a robust positioning algorithm using the trilateration algorithm for VLC under shadowing situations. This algorithm uses the integration of two models, namely the prediction model and fingerprinting model based on the NLOS beams to determine the object's location. The prediction model applies trilateration algorithm based on LOS beams to achieve the potential positions. Then the fingerprinting model uses coordination of these potential positions as input data to match fingerprints built in advance to determine the position of an object. Simulation result show that the positioning error under shadowing effects is small which is the same positioning error yielded under normal working conditions.