基于高斯过程回归与硬件优化的可见光室内定位设计

为了使可见光室内定位操作更加简单，不依赖于视线视图和位置登记，在硬件方面，使用光电二极管作为接收器，通过组装兼容的光电二极管和紧凑型LED完成硬件方面的优化。在软件算法方面，基于指纹技术，使用高斯过程回归（GPR）算法进行定位。首先对GPR环境进行建模，构建一个强度分布模型。然后，使用贝叶斯理论获得定位的表达形式。实验在3m×3m的平台区域上进行，对25个目标进行测试。与类似的室内定位系统相比，所提系统定位精度更高，实现了厘米级定位。且可以长时间精确定位运动目标，鲁棒性较好。

Design of VLC Indoor Positioning System based on Gauss Process Regression and Hardware Optimization

To make the operation of visible indoor positioning simpler and independent of line-of-sight view and position registration, photodiodes are used as the receivers, and the system is optimized in the hardware by assembling compatible photodiodes and compact LED. In the algorithm part, based on fingerprint technology, the Gauss Process Regression (GPR) algorithm is used for location. Firstly, the GPR environment is modeled and a strength distribution model is constructed. Then, Bayesian theory is used to obtain the expression of location. The experiment is carried out in a 3m×3 m platform area and 25 targets are tested. Compared with similar indoor positioning systems, the proposed system has higher positioning accuracy and achieves centimeter-level positioning. The proposed system can accurately locate moving targets for a long time and has good robustness.