基于多径指纹的概率匹配室内定位方法

删除或更新信息，请邮件至freekaoyan#163.com(#换成@)

清华大学辅仁网/2017-07-07

基于多径指纹的概率匹配室内定位方法

李佳徽¹, 张焱², 栾凤宇¹, 李雪茹¹, 周来¹, 周世东¹

1. 清华大学电子工程系, 北京 100084;
2. 北京理工大学信息与电子学院, 北京 100081

Multipath-based probabilistic fingerprinting method for indoor positioning

LI Jiahui¹, ZHANG Yan², LUAN Fengyu¹, LI Xueru¹, ZHOU Lai¹, ZHOU Shidong¹

1. Department of Electronic Engineering, Tsinghua University, Beijing 100084, China;
2. School of Information and Electronics, Beijing Institute of Technology, Beijing 100081, China

摘要:

输出: BibTeX | EndNote (RIS)

摘要空间交替广义期望最大化(SAGE)算法可以高效地实现室内信道多径参数的估计,同时提供相对较高的精度。该文提出一种基于多径指纹的概率匹配室内定位方法,将SAGE算法得到的信道多径参数作为指纹数据进行定位,以求获得更好的定位精度和鲁棒性。通过分析典型场景下的定位实验测量结果,并与同类型的传统室内定位方法进行比较,验证了该方法的有效性。

关键词 ：信道多径估计,指纹,室内定位,多径参数

Abstract：The space-alternating generalized expectation-maximization (SAGE) algorithm provides efficient, accurate indoor channel multipath estimation. This paper describes a multipath-based probabilistic fingerprinting method for indoor positioning that utilizes the channel multipath parameters obtained by the SAGE algorithm as fingerprinting data to achieve better positioning accuracy and robustness. Tests of measurements in a typical indoor environment show that this method is more accurate than traditional indoor positioning methods.

Key words：channel multipath estimation fingerprinting indoor positioning multipath parameters

收稿日期: 2014-08-03 出版日期: 2015-08-04

ZTFLH:

TN929.5

通讯作者:周世东,教授,E-mail:zhousd@tsinghua.edu.cnE-mail: zhousd@tsinghua.edu.cn

引用本文:

李佳徽, 张焱, 栾凤宇, 李雪茹, 周来, 周世东. 基于多径指纹的概率匹配室内定位方法[J]. 清华大学学报（自然科学版）, 2015, 55(5): 514-519,525.
LI Jiahui, ZHANG Yan, LUAN Fengyu, LI Xueru, ZHOU Lai, ZHOU Shidong. Multipath-based probabilistic fingerprinting method for indoor positioning. Journal of Tsinghua University(Science and Technology), 2015, 55(5): 514-519,525.

链接本文:

http://jst.tsinghuajournals.com/CN/或 http://jst.tsinghuajournals.com/CN/Y2015/V55/I5/514

图表:

图１　定位流程图

表１　指纹数据库结构

图２　在线阶段多径传输示例

图３　实验场景平面图

表２　信道测量设备参数

表３　不同多径数目性能比较

图４　不同σ_τ和σ_α 下MPFM 定位误差均值和标准差

图５　不同σ_τ和σ_α 下WMPFM 定位误差均值和标准差

图６　MPFM 误差累计概率

图７　WMPFM 误差累计概率

图８　不同定位方法误差累计概率比较

表４　不同定位算法性能比较

参考文献:

[1]	Google. Indoor positioning [Z/OL]. [2014-07-01]. http://www.google.com/mobile/maps/.
[2]	Qualcomm. Gimbal [Z/OL]. [2014-07-01]. http://www.qualcomm.com/media/releases/2013/12/09/qualcomm-announces-availability-its-gimbal-proximity-beacons-enable.
[3]	Priyantha N B, Chakraborty A, Balakrishnan H. The cricket location-support system [C]//Proceedings of the 6th Annual International Conference on Mobile Computing and Networking. New York, NY, USA: ACM, 2000: 32-43.
[4]	Pan J J, Yang Q, Pan S J. Online co-localization in indoor wireless networks by dimension reduction [C]//Proceedings of the National Conference on Artificial Intelligence. Menlo Park, CA, USA: AAAI Press, 2007: 1102-1107.
[5]	Pan S J, Kwok J T, Yang Q, et al. Adaptive localization in a dynamic WiFi environment through multi-view learning [C]//Proceedings of the National Conference on Artificial Intelligence. Menlo Park, CA, USA: AAAI Press, 2007: 1108-1113.
[6]	Ubisense. My world inside [Z/OL]. [2014-07-01].http://www.ubisense.net/.
[7]	Liu H, Darabi H, Banerjee P, et al. Survey of wireless indoor positioning techniques and systems [J]. Systems, Man, and Cybernetics, Part C: Applications and Reviews, IEEE Transactions on, 2007, 37(6): 1067-1080.
[8]	Xu Y, Sun Y. Neural network-based accuracy enhancement method for WLAN indoor positioning [C]//Vehicular Technology Conference(VTC Fall), 2012 IEEE. Piscataway, NJ, USA: IEEE, 2012: 1-5.
[9]	Hara S, Yabu T, Takizawa K. Introduction of MAP estimation to UWB-IR TOA localization [C]//Wireless Communication Systems (ISWCS), 2010 7th International Symposium on. Piscataway, NJ, USA: IEEE, 2010: 31-35.
[10]	Luo Y, Law C L. Indoor positioning using UWB-IR signals in the presence of dense multipath with path overlapping [J].Wireless Communications, IEEE Transactions on, 2012, 11(10): 3734-3743.
[11]	Bahl P, Padmanabhan V N. RADAR: An in-building RF-based user location and tracking system [C]//IEEE INFOCOM 2000. Piscataway, NJ, USA: IEEE, 2000: 775-784.
[12]	Li B, Salter J, Dempster A G, et al. Indoor positioning techniques based on wireless LAN [C]//The 1st IEEE International Conference on Wireless Broadband and Ultra Wideband Communications. Piscataway, NJ, USA: IEEE, 2006: 113-119.
[13]	Fleury B H, Tschudin M, Heddergott R, et al. Channel parameter estimation in mobile radio environments using the SAGE algorithm [J]. Selected Areas in Communications, IEEE Journal on, 1999, 17(3): 434-450.
[14]	Fleury B H, Jourdan P, Stucki A. High-resolution channel parameter estimation for MIMO applications using the SAGE algorithm [C]//2002 International Zurich Seminar on Broadband Communications. Piscataway, NJ, USA: IEEE, 2002: 1-9.
[15]	Mostofi Y, Gonzalez-Ruiz A, Gaffarkhah A, et al. Characterization and modeling of wireless channels for networked robotic and control systems-a comprehensive overview [C]//IEEE/RSJ International Conference on Intelligent Robots and Systems. Piscataway, NJ, USA: IEEE, 2009: 4849-4854.
[16]	Rui Y, Zhang Y, Liu S, et al. 3.52-GHz MIMO radio channel sounder [C]//IEEE International Conference on Communications, Circuits and Systems 2008. Piscataway, NJ, USA: IEEE, 2008: 79-83.

[1]	何强, 张秀军, 肖立民, 周世东. 大规模MIMO系统中多小区导频重用对上行可达速率的影响[J]. 清华大学学报（自然科学版）, 2015, 55(5): 526-531.