物联网中基于扩展卡尔曼滤波的移动群体定位

doi:10.13190/j.jbupt.2018-216

北京邮电大学学报 ›› 2019, Vol. 42 ›› Issue (2): 95-100.doi: 10.13190/j.jbupt.2018-216

物联网中基于扩展卡尔曼滤波的移动群体定位

梁玉珠¹, 沈雪微¹, 邱磊¹, 陈柏生¹, 王田^1,2

1. 华侨大学计算机科学与技术学院, 福建厦门 361021;
2. 澳门大学智能城市物联网国家重点实验室, 澳门 999078

收稿日期:2018-09-09 出版日期:2019-04-28 发布日期:2019-04-09
通讯作者: 王田(1982-),男,教授,硕士生导师,E-mail:cs_tianwang@163.com. E-mail:cs_tianwang@163.com
作者简介:梁玉珠(1994-),男,硕士生.
基金资助:
福建省社会科学规划基金项目（FJ2018B038）；福建省自然科学基金项目（2018J01092）；福建省教育厅中青年教师教育科研基金项目（JAT170040）；华侨大学研究生科研创新基金项目（17013083005）

Extended Kalman Filter for Mobile Groups Users Localization in Internet of Things

LIANG Yu-zhu¹, SHEN Xue-wei¹, QIU Lei¹, CHEN Bai-sheng¹, WANG Tian^1,2

1. College of Computer Science and Technology, Huaqiao University, Fujian Xiamen 361021, China;
2. The State Key Laboratory of Internet of Things for Smart City, University of Macau, Macao 999078, China

Received:2018-09-09 Online:2019-04-28 Published:2019-04-09

摘要/Abstract

摘要： 为了满足高精度和高可靠性定位的需求，提出了一种基于扩展卡尔曼滤波的移动群体定位算法，把待定位的用户节点当成一个群组，利用他们之间的距离信息得到更好的定位性能，以减小环境噪声和无线信号不稳定造成的影响.此外，开发出一个实际的系统，并在大学校园里进行了大量实验.实验结果和理论分析验证了所提出方法的有效性.

关键词: 协作式定位, 卡尔曼滤波, 定位效率, 移动群体

Abstract: In order to meet the requirement of high localization accuracy and the high reliable localization in some scenarios, the user nodes to be located were taken as a group to get better localization performance by utilizing the mutual distance information among them. A mobile group localization method was designed based on extended Kalman filter, which can alleviate the influence caused by environmental noisy and unstable wireless signals. Besides, a real system was implemented and experiments were performed on the campus of University. The experimental evaluations prove that the performance of the proposed method can effectively improve the localization accuracy.

Key words: cooperative localization, Kalman filter, localization performance, mobile groups

中图分类号:

TN929.53

梁玉珠, 沈雪微, 邱磊, 陈柏生, 王田. 物联网中基于扩展卡尔曼滤波的移动群体定位[J]. 北京邮电大学学报, 2019, 42(2): 95-100.

LIANG Yu-zhu, SHEN Xue-wei, QIU Lei, CHEN Bai-sheng, WANG Tian. Extended Kalman Filter for Mobile Groups Users Localization in Internet of Things[J]. JOURNAL OF BEIJING UNIVERSITY OF POSTS AND TELECOM, 2019, 42(2): 95-100.

参考文献

[1] Wang T, Peng Z, Liang J, et al. Following targets for mobile tracking in wireless sensor networks[J]. ACM Transactions on Sensor Networks (TOSN), 2016, 12(4):31-55.
[2] Tsai M F, Wang P C, Shieh C K, et al. Improving positioning accuracy for VANET in real city environments[J]. The Journal of Supercomputing, 2015, 71(6):1975-1995.
[3] 王文华, 王田, 吴群, 等. 传感网中时延受限的移动式数据收集方法综述[J]. 计算机研究与发展, 2017, 54(3):474-492. Wang Wenhua, Wang Tian, Wu Qun, et al. Survey of delay-constrained data collection with mobile elements in WSNs[J]. Journal of Computer Research and Development, 2017, 54(3):474-492.
[4] Wu C, Yang Z, Xu Y, et al. Human mobility enhances global positioning accuracy for mobile phone localization[J]. IEEE Transactions on Parallel and Distributed Systems, 2015, 26(1):131-141.
[5] Villalpando-Hernández R, Muñoz-Rodríguez D, Vargas-Rosales C, et al. 3-D position location in Ad Hoc networks:a manhattanized space[J]. IEEE Communications Letters, 2017, 21(1):124-127.
[6] Dang Xiaochao, Hei Yilin, Hao Zhanjun. An improved indoor localization based on RSSI and feedback correction of anchor node for WSN[C]//2016 International Conference on Computer, Information and Telecommunication Systems (CITS). Yunnan China:IEEE, 2016:1-5.
[7] 王田, 梁玉珠, 彭臻, 等. 无线传感器网络中移动目标探测跟踪研究进展[J]. 软件学报, 2017, 28(s1):115-128. Wang Tian, Liang Yuzhu, Peng Zhen, et al. Research advance of detection-centric target tracking with mobile elements in wireless sensor networks[J]. Journal of Software, 2017, 28(s1):115-128.
[8] Deng Z A, Hu Y, Yu J, et al. Extended Kalman filter for real time indoor localization by fusing WiFi and smartphone inertial sensors[J]. Micromachines, 2015, 6(4):523-543.
[9] Wang T, Wang W, Cao J, et al. Interoperable localization for mobile group users[J]. Computer Communications, 2017(105):53-65.
[10] 王国军, 王田, 贾维嘉. 无线传感器网络中一种基于行进启发的地理位置路由[J]. 传感技术学报, 2007, 20(2):382-386. Wang Guojun, Wang Tian, Jia Weijia. March inspired geographic routing protocol in wireless sensor networks[J]. Chinese Journal of Sensors and Actuators, 2007, 20(2):382-386.
[11] 王田, 张广学, 蔡绍滨, 等. 传感云中的信任评价机制研究进展[J]. 通信学报, 2018, 39(6):37-51. Wang Tian, Zhang Guangxue, Cai Shaobin, et al. Survey on trust evaluation mechanism in sensor-cloud[J]. Journal on Communications, 2018, 39(6):37-51.
[12] 何异舟, 崔高峰, 李鹏旭, 等. 卫星移动终端增强型卡尔曼滤波协同自主定位算法[J]. 北京邮电大学学报, 2015, 38(3):94-98. He Yizhou, Cui Gaofeng, Li Pengxu, et al. A satellite mobile terminals cooperative autonomous positioning algorithm based on enhanced kalman filter[J]. Journal of Beijing University of Posts and Telecommunications, 2015, 38(3):94-98.
[13] Wang Tian, Xing Guoliang, Li Minming, et al. Efficient wifi deployment algorithms based on realistic mobility characteristics[C]//The 7^th IEEE International Conference on Mobile Ad-hoc and Sensor Systems (IEEE MASS 2010). San Francisco:IEEE, 2010:422-431.

物联网中基于扩展卡尔曼滤波的移动群体定位

Extended Kalman Filter for Mobile Groups Users Localization in Internet of Things

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