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作 者:涂兴华[1] 赵海洋[1] TU Xinghua;ZHAO Haiyang(College of Electronic and Optical Engineering&College of Flexible Electronics(Future Technology),Nanjing University of Posts and Telecommunications,Nanjing 210023,China)
机构地区:[1]南京邮电大学电子与光学工程学院、柔性电子(未来技术)学院,南京210023
出 处:《光子学报》2025年第3期32-42,共11页Acta Photonica Sinica
基 金:国家自然科学基金(Nos.11547031,GZ216003);南京邮电大学科研基金(No.NY217111)。
摘 要:针对室内可见光通信定位精度不足的问题,提出一种基于注意力机制进行信息融合的可见光定位方法(Multi-Information Fusion-Visible Light Positioning,MIF-VLP)。信息融合指MIF-VLP算法通过注意力机制的方式融合图像信息和接收信号强度(Received Signal Strength,RSS)且以图像信息为主。MIF-VLP算法减少了单一信息源下的特征不足,提高了定位精度。同时图像信息通过18层残差网络(Residual Network with 18 layers,ResNet18)提取图像特征并降维,RSS通过词嵌入(wordembedding)提取光强特征并升维。经维度转换后的图像信息和光强信息维度相同,并通过注意力机制进行信息融合。实验结果表明,在2 m×2 m×1.8 m的环境,MIF-VLP算法的平均定位误差达到5mm,相比基于RSS信息的RSS-BP算法提升了80.7%,相比基于图像信息的卷积神经网络(Convolutional Neural Network,CNN)算法提升了87.5%。Positioning algorithms based on visible light communication can help solve the problem of insufficient positioning accuracy in some special occasions such as indoors,basements,and underground.However,the accuracy of existing visible light positioning algorithms is difficult to improve further,and most of them remain in the simulation stage without experimental verification.In the previous visible light positioning algorithms based on deep learning,such algorithms can be divided into positioning algorithms based on received light signal intensity and positioning algorithms based on light source images according to the source of data.The positioning algorithm based on received light signal intensity receives the light signal intensity from each LED light source in turn,and obtains the positioning result based on the characteristics of the light signal intensity.Similarly,the positioning algorithm based on light source image receives the LED light source image and obtains the positioning result by analyzing the characteristics of the light source.This article proposes a positioning algorithm(MIF-VLP)based on the attention mechanism to fuse light Signal Intensity Information(RSS)and image information.The MIF-VLP algorithm uses ResNet-18 as the backbone network of the image,and maps RSS into a vector through word embedding,and then adjusts the output of ResNet-18 to make them have the same dimension.The fusion method of the attention mechanism is based on the image,so the input of the attention layer is multiple vectors,and the output is only one vector.The advantages of the algorithm are that,firstly,the algorithm uses both the light signal intensity information and the image information,which makes up for the overfitting problem caused by the single data,improves the generalization ability of the model and the final positioning accuracy.Secondly,the algorithm performs a permutation and combination preprocessing on the received light signal intensity,treats the input light signal intensity as a sequence,ignores the o
关 键 词:室内定位 深度学习 信息融合 可见光通信 神经网络
分 类 号:TN929.1[电子电信—通信与信息系统]
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