光通信技术2025，Vol.49Issue(1)：1-5,5.DOI:10.13921/j.cnki.issn1002-5561.2025.01.001
基于SCSSA-RF算法的室内可见光定位算法
Indoor visible light positioning algorithm based on SCSSA-RF algorithm
摘要
Abstract
To address the issues of low positioning accuracy and the risk of overfitting when the random forest(RF)algorithm is used for indoor visible light positioning,a sparrow search algorithm(SS A)optimized RF algorithm for indoor visible light position-ing based on sine population mapping(SPM)and Cauchy distribution(hereinafter referred to as SCSSA-RF algorithm)is proposed.Firstly,this algorithm establishes a fingerprint database using the received signal strength values and position coordinates.Then,it uses the global search capability of SCSSA to optimize key parameters of the RF algorithm,inputs the data into the optimal model for training,and averages the prediction results from the decision trees to obtain the predicted value for the target location point.The experimental results show that SCSSA-RF algorithm converges faster than the unimproved SSA-RF algorithm,the average posi-tioning error of SCSSA-RF algorithm is 0.08 meters,with errors mainly concentrated between 0.05 to 0.1 meters.At a positioning error of 0.2 meters,the prediction accuracy of SCSSA-RF algorithm reaches 93％.关键词
可见光定位/正弦人口映射/柯西分布/麻雀搜索算法/随机森林Key words
visible light positioning/sine population mapping/Cauchy distribution/sparrow search algorithm/random forest分类
电子信息工程引用本文复制引用
陈耀,张烈平,高小淋,张翠..基于SCSSA-RF算法的室内可见光定位算法[J].光通信技术,2025,49(1):1-5,5.基金项目
国家自然科学基金项目(61741303)资助 （61741303）
广西空间信息与测绘重点实验室基金项目(21-238-21-16)资助 （21-238-21-16）
梧州市2022年中央引导地方科技发展资金项目(202201001)资助. （202201001）
