基于CSI相位差值矫正的室内定位算法

doi:10.19678/j.issn.1000-3428.0050455

计算机工程 ›› 2019, Vol. 45 ›› Issue (2): 18-25. doi: 10.19678/j.issn.1000-3428.0050455

所属专题：物联网专题；

基于CSI相位差值矫正的室内定位算法

党小超^1,2,任家驹¹,郝占军^1,2

1.西北师范大学计算机科学与工程学院,兰州 730070; 2.甘肃省物联网工程研究中心,兰州 730070

收稿日期:2018-02-08 出版日期:2019-02-15 发布日期:2019-02-15
作者简介:党小超(1963—),男,教授,主研方向为物联网、无线传感器网络;任家驹,硕士研究生;郝占军(通信作者),副教授、硕士。
基金资助:
国家自然科学基金(61762079,61662070);甘肃省科技重点研发项目(1604FKCA097,17YF1GA015);甘肃省科技创新项目(17CX2JA037,17CX2JA039)

Indoor Location Algorithm Based on CSI Phase Difference Correction

DANG Xiaochao^1,2,REN Jiaju ¹,HAO Zhanjun^1,2

1.College of Computer Science and Engineering,Northwest Normal University,Lanzhou 730070,China; 2.Gansu Province Internet of Things Engineering Research Center,Lanzhou 730070,China

Received:2018-02-08 Online:2019-02-15 Published:2019-02-15

摘要/Abstract

摘要：

针对现有基于信道状态信息的室内无源指纹定位方法在复杂场景中多数存在相位误差偏移、指纹噪声大、样本分类精度低的问题,提出一种基于相位差值矫正的室内指纹定位算法。在离线阶段通过计算相位差值矫正通信链路中的相位误差和偏移,建立鲁棒的指纹数据库,使用BP神经网络对指纹特征数据进行训练,得到指纹特征信息与物理位置的映射关系模型。在线阶段相位采样值经过差值矫正后作为模型的输入,计算得到最终的精确定位结果。实验结果表明,与现有基于指纹的定位方法相比,该方法具有去噪效果显著、定位精度高的优点。

关键词: 信道状态信息, 室内定位, 相位差值, 指纹数据库, BP神经网络

Abstract:

Aiming at the problems of phase error offset,high fingerprint noise and low accuracy of sample classification in most of the existing indoor passive fingerprint location methods based on Channel State Information(CSI) in complex scenes,an indoor fingerprint location algorithm based on Phase Difference(PD) value correction is proposed.In the offline period,the phase error and offset in the communication link are corrected by calculating the phase difference,and a robust fingerprint database is established.The BP neural network is used to train the fingerprint feature data to obtain the mapping relationship between fingerprint feature information and physical location.Online phase,this algorithm sets the phase difference filtering of CSI real time sampling value as the model,carries out positioning computing and finally gets the accurate location result.Experimental results show that compared with the existing fingerprint-based location method,this method has the advantages of significant denoising effect and high positioning accuracy.

Key words: Channel State Information(CSI), indoor location, Phase Difference(PD), fingerprint database, BP neural network

中图分类号:

TP393

党小超,任家驹,郝占军. 基于CSI相位差值矫正的室内定位算法[J]. 计算机工程, 2019, 45(2): 18-25.

DANG Xiaochao,REN Jiaju,HAO Zhanjun. Indoor Location Algorithm Based on CSI Phase Difference Correction[J]. Computer Engineering, 2019, 45(2): 18-25.

http://www.ecice06.com/CN/Y2019/V45/I2/18

参考文献

［1］石高涛,王伯远,吴斌.基于 WiFi 与移动智能终端的室内定位方法综述［J］.计算机工程,2015,41(9):39-44,50.
［2］CHEN C,CHEN Y,HAN Y,et al.Achieving centimeter-accuracy indoor localization on WiFi platforms:a multi-antenna approach［J］.IEEE Internet of Things Journal,2017,4(1):122-134.
［3］SHI S,SIGG S,JI Y.Probabilistic fingerprinting based passive device-free localization from channel state information［C］//Proceedings of VTC’16.Washington D.C.,USA:IEEE Press,2016:1-5.
［4］蔡文学,邱珠成,黄晓宇,等.基于WiFi指纹的室内轨迹定位模型［J］.计算机工程,2015,41(6):76-82.
［5］WU K,XIAO J,YI Y,et al.CSI-based indoor localization［J］.IEEE Transactions on Parallel and Distributed Systems,2013,24(7):1300-1309.
［6］XIE H,LIN L,JIANG Z,et al.Accelerating crowd sourcing based indoor localization using CSI［C］//Proceedings of the 21st International Conference on Parallel and Distributed Systems.Washington D.C.,USA:IEEE Press,2015:274-281.
［7］KOTARU M,JOSHI K,BHARADIA D,et al.SpotFi:decimeter level localization using WiFi［C］//Proceedings of 2015 ACM Conference on Special Interest Group on Data Communication.New York,USA:ACM Press,2015:269-282.
［8］WANG X,GAO L,MAO S,et al.deepFi:Deep learning for indoor fingerprinting using channel state informa-tion［C］//Proceedings of IEEE Wireless Communica-tions and Networking Conference.Washington D.C.,USA:IEEE Press,2015:1666-1671.
［9］SEN S,RADUNOVIC B,CHOUDHURY R R,et al.You are facing the Mona Lisa:spot localization using PHY layer information［C］//Proceedings of the 10th International Conference on Mobile Systems,Applications,and Services.Washington D.C.,USA:IEEE Press,2012:183-196.
［10］刘小康,郭杭.基于 Zigbee 室内定位系统的指纹库优化算法［J］.计算机工程,2014,40(2):193-198.
［11］JIANG Weipeng.For better CSI fingerprinting based localization:a novel phase sanitization method and a distance metric［C］//Proceedings of the 85th IEEE Vehicular Technology Conference.Washington D.C.,USA:IEEE Press,2017:1-7.
［12］张会清,石晓伟,邓贵华,等.基于BP神经网络和泰勒级数的室内定位算法研究［J］.电子学报,2012,40(9):1876-1879.
［13］LI J,LI Y,JI X.A novel method of Wi-Fi indoor localization based on channel state information［C］//Proceedings of International Conference on Wireless Communications and Signal Processing.Washington D.C.,USA:IEEE Press,2016:1-5.
［14］XIE Y,LI Z,LI M.Precise power delay profiling with commodity Wi-Fi ［C］//Proceedings of the 21st Annual International Conference on Mobile Computing and Networking.New York,USA:ACM Press,2015:53-64.
［15］ZHUO Y,ZHU H,XUE H.Identifying a new non-linear CSI phase measurement error with commodity WiFi devices［C］//Proceedings of IEEE International Conference on Parallel and Distributed Systems.Washington D.C.,USA:IEEE Press,2014:72-79.
［16］CHENG Y C,CHAWATHE Y,LAMARCA A,et al.Accuracy characterization for metropolitan-scale Wi-Fi localization［C］//Proceedings of the 3rd International Conference on Mobile Systems,Applications,and Services.New York,USA:ACM Press,2005:233-245.

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