Journal of Software:2018.29(S1):63-72

(西南大学 电子信息工程学院, 重庆 400715;网络与云计算安全重庆市高校重点实验室(西南大学), 重庆 400715;西南大学 计算机与信息科学学院, 重庆 400715)
Indoor Fingerprint Location Algorithm Based on Convolutional Neural Network
WANG Ying,HUANG Xu-Dong,GUO Song-Tao
(College of Electronic and Information Engineering, Southwest University, Chongqing 400715, China;Key Laboratory of Networks and Cloud Computing Security of Universities in Chongqing(Southwest University), Chongqing 400715, China;College of Computer and Information Science, Southwest University, Chongqing 400715, China)
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Received:May 01, 2018    
> 中文摘要: 随着无线网络和智能设备的普及,室内定位得到了迅速发展.在室内定位中,基于指纹的定位方法因为无需外部设施、抗干扰性强等优点逐渐成为研究热点.近几年深度学习的发展为提高指纹定位算法的精度带来了新的机遇.因此提出了一种基于CNN的指纹定位算法,使用卷积神经网络(convolutional neural network,简称CNN)来改进指纹库的构建.首先,在收集了CSI与磁场数据后,通过CNN对这些数据进行处理,将每个参考点处的CNN模型参数值用作为指纹.然后使用一种概率方法来进行最后的指纹匹配.实验结果表明,该定位算法比传统的指纹定位算法具有更好的鲁棒性和更高的定位精度.
Abstract:With the popularity of wireless networks and smart devices, indoor positioning has been rapidly developed. In indoor positioning, the fingerprint-based positioning method has gradually become a research hotspot because it does not require external facilities and strong anti-interference. The development of deep learning in recent years has brought new opportunities for improving the accuracy of fingerprint positioning algorithms. This paper proposes a convolutional neural network (CNN)-based fingerprint location algorithm to improve the construction of the fingerprint database. First, the collected CSI and magnetic field data is processed through CNN, and the CNN model parameter values are used at each reference point as fingerprint. Then a probabilistic method is utilized for the final fingerprint matching. Experimental results show that the proposed positioning algorithm has better robustness and higher positioning accuracy than the traditional fingerprint positioning algorithm.
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基金项目:国家自然科学基金(61772432,61772433);重庆市自然科学重点基金(cstc2015jcyjBX0094);西南大学基本科研业务费专项资金(XDJK2016C040) 国家自然科学基金(61772432,61772433);重庆市自然科学重点基金(cstc2015jcyjBX0094);西南大学基本科研业务费专项资金(XDJK2016C040)
Foundation items:National Natural Science Foundation of China (61772432, 61772433); Natural Science Key Foundation of Chongqing (cstc2015jcyjBX0094); Fundamental Research Funds for the Central Universities of Southwest University (XDJK2016C040)
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WANG Ying,HUANG Xu-Dong,GUO Song-Tao.Indoor Fingerprint Location Algorithm Based on Convolutional Neural Network.Journal of Software,2018,29(S1):63-72