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Visible light communication (VLC) has become a promising research topic in recent years, and finds its wide applications in indoor environments. Particularly, for location based services (LBS), visible light also provides a practical solution for indoor positioning. Multipath-induced dispersion is one of the major concerns for complex indoor environments. It affects not only the communication performance but also the positioning accuracy. In this paper, we investigate the impact of multipath reflections on the positioning accuracy of indoor VLC positioning systems. Combined Deterministic and Modified Monte Carlo (CDMMC) approach is applied to estimate the channel impulse response considering multipath reflections. Since the received signal strength (RSS) information is used for the positioning algorithm, the power distribution from one transmitter in a typical room configuration is first calculated. Then, the positioning accuracy in terms of root mean square error is obtained and analyzed.
Visible light communication (VLC) using light-emitting-diodes (LEDs) has been a popular research area recently. VLC can provide a practical solution for indoor positioning. In this paper, the impact of multipath reflections on indoor VLC positioning
Visible Light Communication (VLC) technology using light emitting diodes (LEDs) has been gaining increasing attention in recent years as it is appealing for a wide range of applications such as indoor positioning. Orthogonal frequency division multip
This paper presents an approach for visible light communication-based indoor positioning using compressed sensing. We consider a large number of light emitting diodes (LEDs) simultaneously transmitting their positional information and a user device e
Indoor positioning systems using visible light communication (VLC) have potential applications in smart buildings, for instance, in developing economical, easy-to-use, widely accessible positioning system based on light-emitting diodes. Thus using VL
In this paper, we propose a multi-target image tracking algorithm based on continuously apative mean-shift (Cam-shift) and unscented Kalman filter. We improved the single-lamp tracking algorithm proposed in our previous work to multi-target tracking,