光通信技术2024，Vol.48Issue(2)：30-35,6.DOI:10.13921/j.cnki.issn1002-5561.2024.02.006
基于多源信息融合的RBF神经网络室内可见光定位算法
RBF neural network indoor visible light positioning algorithm based on multi-source information fusion
摘要
Abstract
Aiming at the problem of low positioning accuracy and poor stability caused by the environmental interference of the positioning technology based on received signal strength(RSS),an radial basis function(RBF)neural network indoor visible light positioning algorithm based on multi-source information fusion is proposed.By fusing the color moment feature of the im-age with the RSS moment feature,a fingerprint database is constructed,and the RBF neural network is used for prediction to achieve complementary advantages between the image and RSS.Finally,the positioning algorithm is verified.The experimental results show that the optimized multi-source information fusion positioning algorithm improves the positioning accuracy by 9.4%compared with the single RSS positioning algorithm.关键词
可见光/室内定位/多源信息融合/颜色矩/神经网络/径向基函数/特征提取Key words
visible light/indoor position/multi-source information fusion/color momentn/neural networks/radial basis function/feature extraction分类
信息技术与安全科学引用本文复制引用
王琪,孟祥艳,赵黎..基于多源信息融合的RBF神经网络室内可见光定位算法[J].光通信技术,2024,48(2):30-35,6.基金项目
陕西省科技厅一般项目-工业领域(No.2020GY-054)资助. （No.2020GY-054）
