摘要
针对采用指纹库进行可见光室内定位时,离线阶段工作量大的问题,提出一种高精度再生指纹的可见光室内定位算法,离线阶段采集少数位置的光信号强度值,通过光信号传播模型来估算出其他位置的信号强度;在线阶段采用平方弦距离度量的改进的加权K近邻算法。实验仿真结果表明,采集数据的工作量大大降低,定位精度与真实指纹库接近。
In order to solve the problem of heavy work in offline phase when using fingerprint database for visible light indoor location,a high accuracy visible light indoor location algorithm for regenerated fingerprint was proposed in this study.In the offline stage,the intensity of optical signals at a few locations was collected,and the intensity of signals at other locations was estimated by the optical signal propagation model.The improved weighted K-nearest neighbor algorithm of square string distance measurement was adopted in the online stage.Experimental simulation results showed that the workload of data collection is greatly reduced and the positioning accuracy is close to the real fingerprint library.
作者
张旭
姚善化
ZHANG Xu;YAO Shan-hua(School of Electrical and Information Engineering,Anhui University of Science and Technology,Huainan,232001,Anhui)
出处
《蚌埠学院学报》
2021年第2期93-96,共4页
Journal of Bengbu University
基金
安徽省自然科学基金面上基金(1808085MF169)
安徽高校自然科学研究项目(KJ2018A0086)。
关键词
室内定位
可见光
指纹算法
加权K近邻
indoor positioning
visible light
fingerprint algorithm
weighted k nearest neighbor