High accuracy and error analysis of indoor visible light positioning algorithm based on image sensor

In recent years, with the increasing demand for indoor positioning service, visible light indoor positioning based on image sensors has been widely studied. However, many researches only put forward the relevant localization algorithm and did not make a deep discussion on the principle of the visible light localization. In this paper, we make a deep discussion on the principle of the two-light positioning algorithm and the three-light positioning algorithm based on the image sensor, which includes how these positioning algorithms work and the errors analysis. Based on the discussion above, we propose two methods to improve the positioning accuracy, which is rotation method and dispersion circle method respectively. In our experiment, we have numerically and experimentally verified the two optimization methods and we obtained good positioning results. Especially, the positioning accuracy of the dual-lamp positioning algorithm based on dispersion circle optimization is up to 1.93cm, while the average positioning error is only 0.82cm, which is state-of-the-art of the same type of positioning system at present.Comment: This paper presents a centimeter-level precise positioning system based on image sensor and visible light LED. In this paper, the principle of dual-light positioning algorithm and three-lamp positioning algorithm based on image sensor is deeply and respectively analyzed. And the error generation in the algorithm is discusse

High Accuracy VLP based on Image Sensor using Error Calibration Method

In this paper, visible light positioning (VLP) where the receiver adopts a commercial image sensor is considered. We firstly analyze the theoretical limits and error source of the VLP system using image sensor. And then, we develop a VLP positioning model on the receiver movement and further propose two novel error calibration algorithms, namely Rotation Calibration Method and dispersion circle calibration method. The rotation algorithm estimates the rotation center in the image instead of treating the image center as the rotation center, leading to reduced positioning error. For the dispersion circle, it can offset the shift error created by the conversation between different coordinate during the positioning calculation. According to the experimental results, the average positioning error of the proposed methods can be reduced to 0.82cm, which achieve state-of-the-art in the VLP field.Comment: 16Pages, 10 figure