The Integration of Photodiode and Camera for Visible Light Positioning by Using Fixed-Lag Ensemble Kalman Smoother

Abstract

Visible Light Positioning (VLP) has become one of the most popular positioning and navigation systems in this decade. Filter-based VLP systems can provide real-time solutions but have limited accuracy. On the contrary, fixed-interval smoothers can help VLP achieve higher accuracy but require post-processing. In this article, a trade-off solution, Fixed-Lag Ensemble Kalman Smoother (FLEnKS), is proposed for VLP to achieve a semi-real-time and accurate positioning solution. The forward part of the FLEnKS is based on the Ensemble Kalman Filter (EnKF), which uses stochastic sampling with ensemble members and enables a better reflection of the features of nonlinear systems. The backward filter in the FLEnKS compensates for the estimation error from the forward filter using the linearization based on error states and further reduces the estimation error. Furthermore, multiple data from both photodiode (PD) and camera are fused in the proposed FLEnKS for VLP, which further improves the accuracy of conventional VLP with a single data source. Preliminary field test results show that the proposed FLEnKS provides a semi-real-time positioning solution with the average 3D positioning accuracy of 15.63 cm in dynamic tests.

Keywords

• Fixed-lag ensemble Kalman smoother
• visible light positioning
• navigation
• tracking
• data fusion