Please wait a minute...
浙江大学学报(工学版)
JOURNAL OF ZHEJIANG UNIVERSITY (ENGINEERING SCIENCE)
Electrical Engineering     
Three-dimensional indoor positioning technology based on characteristic light source
HUANG Ji yang,MENG Jun,ZHANG Ran
College of Electrical Engineering, Zhejiang University, Hangzhou 310027, China
Download:   PDF(1597KB) HTML
Export: BibTeX | EndNote (RIS)      

Abstract  

A three-dimensional indoor positioning technology based on characteristic light source and spherical lighting device was proposed in order to solve the following problems: low accuracy, lots of limitations, lack of height information and poor anti-jamming capability in indoor position system (IPS). The technology measures the angle of optical signal. Spherical lighting device can receive light in all direction and get height information compared with the flat mode. Pseudo-source interference caused by the wave nature will not be introduced with the use of the particle nature of light. Array layout and optimization algorithm can further improve the positioning accuracy. Both simulation experiment in Matlab and physical experiments were conducted. The experimental results and the analysis of accuracy confirmed that the positioning accuracy can be controlled within 0.03 m in a 3 m high room with conventional LED light source, optical fiber and optical sensor. The three-dimensional indoor positioning technology can achieve high accuracy at low cost．

Published: 23 July 2016
CLC:  TP 391  
Service
E-mail this article
Add to my bookshelf
Add to citation manager
E-mail Alert
RSS
Articles by authors
Cite this article:

HUANG Ji yang,MENG Jun,ZHANG Ran. Three-dimensional indoor positioning technology based on characteristic light source. JOURNAL OF ZHEJIANG UNIVERSITY (ENGINEERING SCIENCE), 2016, 50(7): 1393-1401.

URL:

http://www.zjujournals.com/eng/10.3785/j.issn.1008-973X.2016.07.024     OR     http://www.zjujournals.com/eng/Y2016/V50/I7/1393


基于特征光源的三维室内定位技术

针对当前室内定位技术精度低、局限大、缺乏高度信息和抗干扰性差等问题,以特征光源为固定单元,球形采光装置为移动单元,基于对光信号的角度测定建立模型实现三维室内定位.球面采光模式突破了传统平面采光对光源位置的限制,实现了360°全方位采光,能够获得包含高度在内的三维位置信息|基于光的粒子性的定位方式避免了由于光的波动性引起的伪光源干扰,阵列化布局和优化算法提高了定位精度.Matlab仿真结果、实物实验结果及精度分析证实,利用常规的LED光源、光纤和光传感器,该定位技术能够在3 m高的房间内达到0.03 m左右的定位精度,实现了低成本下的高精度三维室内定位.

［1］ 庄春华, 赵治华, 张益青, 等. 卫星导航定位技术综述［J］. 导航定位学报, 2014, 2(1): 34-40．
ZHUANG Chunhua, ZHAO Zhihua, ZHANG Yiqing, et al. Overview on seamless positioning technologies of satellite navigation ［J］. Journal of Navigation and Positioning, 2014, 2(1): 34-40．
［2］ 陈忠贵, 帅平, 曲广吉. 现代卫星导航系统技术特点与发展趋势分析［J］. 中国科学(E), 2009, 39(4): 686-695．
CHEN Zhonggui, SHUAI Ping, QU Guangji. Analysis of technical characteristics and development trend of modern satellite navigation systems ［J］. Science in China (Series E) , 2009, 39(4): 686-695．
［3］ 姜西瑞. 基于GPS和GSM/GPRS的定位系统的设计与实现［D］. 北京: 中国科学院计算技术研究所, 2006: 8-12．
JIANG Xirui. The design and implementation of positioning system based on GSM/GPRS and GPS ［D］. Beijing: Institute of Computing Technology, Chinese Academy of Science, 2006: 8-12．
［4］ 陈璋鑫. LOS/NLOS无线定位方法研究［D］. 成都: 电子科技大学, 2009: 1-19．
CHEN Zhangxin. Study of LOS/NLOS wireless positioning method ［D］. Chengdu: University of Electronic Science and Technology of China, 2009: 1-19．
［5］ 张立立, 钟耳顺. 无线室内定位技术［C］∥中国地理信息系统协会第八届年会论文集. 北京: 中国地理信息系统协会出版社, 2004: 966-973．
ZHANG Lili, ZHONG Ershun. Wireless indoor position location technology ［C］∥8th Annual Conference Proceedings of CAGIS. Beijing: CAGIS Press, 2004: 966-973．
［6］ 方震, 赵湛, 郭鹏, 等. 基于RSSI测距分析［J］. 传感技术学报, 2007, 20(11): 2526-2530.
FANG Zhen, ZHAO Zhan, GUO Peng, et al. Analysis of distance measurement based on RSSI ［J］. Chinese Journal of Sensors and Actuators, 2007, 20(11): 2526-2530.
［7］ 汪苑, 林锦国. 几种常用三维室内定位技术的探讨［J］. 中国仪器仪表, 2011, 2(2): 54-57．
WANG Yuan, LIN Jinguo. Indoor location technique based on RFID ［J］. China Instrumentation, 2011, 2(2): 54-57．
［8］ YOSHINO M, HARUYAMA S, NAKAGAWA M. Highaccuracy positioning system using visible LED lights and image sensor ［J］. Radio and Wireless Symposium, 2008,12(1): 439-442.
［9］ RAHMAN M S, HAQUE M M, KIM K D. Indoor positioning by LED visible light communication and image sensors ［J］. International Journal of Electrical and Computer Engineering(IJECE), 2011, 1(2): 161-170．
［10］ RAHMAN M S, HAQUE M M, KIM K D. High precision high precision indoor positioning using lighting LED and image sensor ［C］∥ International Conference on Computer and Information Technology(ICCIT). Dhaka: Dhaka Press, 2011: 22-24．
［11］ 沈芮, 张剑. 基于可见光通信的室内定位方法［J］. 信息工程大学学报, 2014, 15(1): 41-45．
SHEN Rui, ZHANG Jian. Indoor location method based on visible light communication ［J］. Journal of Information Engineering University, 2014, 15(1): 41-45．
［12］ ZHANG W, KAVEHRAD M V. A 2D indoor localization system based on visible light LED ［C］∥Photonics Society Summer Topical Meeting Series. Mexico: Playa del Carmen Press, 2012: 80-81．
［13］CHEOK AD, LI Y. A novel lightsensorbased information transmission system for indoor positioning and navigation ［J］. IEEE Transactions on Instrumentation and Measurement, 2011, 60(1): 290-299．
［14］ 杜志泉, 倪锋, 肖发新. 光纤传感技术的发展与应用［J］. 光电技术应用, 2014(6): 7-12．
DU Zhiquan, NI Feng, XIAO Faxin. Development and application of optical fiber sensing technology ［J］. ElectroOptic Technology Application, 2014(6): 7-12.
[1] HE Xue-jun, WANG Jin, LU Guo-dong, LIU Zhen-yu, CHEN Li, JIN Jing. 3D head portrait sculpture by industrial robot based on triangular mesh slicing and collision detection[J]. JOURNAL OF ZHEJIANG UNIVERSITY (ENGINEERING SCIENCE), 2017, 51(6): 1104-1110.
[2] WANG Hua, HAN Tong-yang, ZHOU Ke. KeyGraph-based community detection algorithm for public security intelligence[J]. JOURNAL OF ZHEJIANG UNIVERSITY (ENGINEERING SCIENCE), 2017, 51(6): 1173-1180.
[3] YOU Hai-hui, MA Zeng-yi, TANG Yi-jun, WANG Yue-lan, ZHENG Lin, YU Zhong, JI Cheng-jun. Soft measurement of heating value of burning municipal solid waste for circulating fluidized bed[J]. JOURNAL OF ZHEJIANG UNIVERSITY (ENGINEERING SCIENCE), 2017, 51(6): 1163-1172.
[4] BI Xiao-jun, WANG Jia-hui. Teaching-learning-based optimization algorithm with hybrid learning strategy[J]. JOURNAL OF ZHEJIANG UNIVERSITY (ENGINEERING SCIENCE), 2017, 51(5): 1024-1031.
[5] MU Jing-jing, ZHAO Xin-yue, HE Zai-xing, ZHANG Shu-you. Contour reconstruction of overlapped bubbles based on concave-convex transformation and circle fitting[J]. JOURNAL OF ZHEJIANG UNIVERSITY (ENGINEERING SCIENCE), 2017, 51(4): 714-721.
[6] HUANG Zheng-yu, JIANG Xin-long, LIU Jun-fa, CHEN Yi-qiang, GU Yang. Fusion feature based semi-supervised manifold localization method[J]. JOURNAL OF ZHEJIANG UNIVERSITY (ENGINEERING SCIENCE), 2017, 51(4): 655-662.
[7] JIANG Xin-long, CHEN Yi-qiang, LIU Jun-fa, HU Li-sha, SHEN Jian-fei. Wearable system to support proximity awareness for people with autism[J]. JOURNAL OF ZHEJIANG UNIVERSITY (ENGINEERING SCIENCE), 2017, 51(4): 637-647.
[8] WANG Liang, YU Zhi-wen, GUO Bin. Moving trajectory prediction model based on double layer multi-granularity knowledge discovery[J]. JOURNAL OF ZHEJIANG UNIVERSITY (ENGINEERING SCIENCE), 2017, 51(4): 669-674.
[9] LIAO Miao, ZHAO Yu-qian, ZENG Ye-zhan, HUANG Zhong-chao, ZHANG Bing-kui, ZOU Bei-ji. Automatic segmentation for cell images based on support vector machine and ellipse fitting[J]. JOURNAL OF ZHEJIANG UNIVERSITY (ENGINEERING SCIENCE), 2017, 51(4): 722-728.
[10] DAI Cai-yan, CHEN Ling, LI Bin, CHEN Bo-lun. Sampling-based link prediction in complex networks[J]. JOURNAL OF ZHEJIANG UNIVERSITY (ENGINEERING SCIENCE), 2017, 51(3): 554-561.
[11] LIU Lei, YANG Peng, LIU Zuo-jun. Locomotion-Mode recognition using multiple kernel relevance vector machine[J]. JOURNAL OF ZHEJIANG UNIVERSITY (ENGINEERING SCIENCE), 2017, 51(3): 562-571.
[12] GUO Meng-li, DA Fei-peng, DENG Xing, GAI Shao-yan. 3D face recognition based on keypoints and local feature[J]. JOURNAL OF ZHEJIANG UNIVERSITY (ENGINEERING SCIENCE), 2017, 51(3): 584-589.
[13] WANG Hai jun, GE Hong juan, ZHANG Sheng yan. Fast object tracking algorithm via kernel collaborative presentation[J]. JOURNAL OF ZHEJIANG UNIVERSITY (ENGINEERING SCIENCE), 2017, 51(2): 399-407.
[14] ZHANG Ya nan, CHEN De yun, WANG Ying jie, LIU Yu peng. Incremental graph pattern matching based dynamic recommendation method for cold-start user[J]. JOURNAL OF ZHEJIANG UNIVERSITY (ENGINEERING SCIENCE), 2017, 51(2): 408-415.
[15] LIU Yu peng, QIAO Xiu ming, ZHAO Shi lei, MA Chun guang. Deep combination of large-scale features in statistical machine translation[J]. JOURNAL OF ZHEJIANG UNIVERSITY (ENGINEERING SCIENCE), 2017, 51(1): 46-56.