Visible Light Positioning and Navigation Using Noise Measurement and Mitigation

Visible light positioning (VLP) has become an essential candidate for high-accurate positioning; however, its positioning accuracy is usually degraded by the noise in the VLP system. To solve this problem, a novel scheme of noise measurement and mitigation is proposed for VLP based on the noise measurement from Allan Variance and the noise mitigation from positioning algorithms such as Adaptive Least Squares (ALSQ) and Extended Kalman Filter (EKF). In this scheme, Allan Variance is introduced for noise analysis in VLP for the first time, which provides an efficient method for measuring the white noise in the VLP systems. Meanwhile, we evaluate our noise reduction method under static test using ALSQ and dynamic test using EKF. Furthermore, this article carefully discusses the relationship between positioning accuracy and dilution of precision (DOP) values. The preliminary field static tests demonstrate that the proposed scheme improves the positioning accuracy by 16.5% and achieves the accuracy of 137 mm while dynamic tests show an improvement of 60.4% and achieve the mean positioning accuracy of 153 mm.