基于自适应蝙蝠算法的室内RFID定位算法

doi:10.11959/j.issn.1000-436x.2022159

通信学报 ›› 2022, Vol. 43 ›› Issue (8): 90-99.doi: 10.11959/j.issn.1000-436x.2022159

基于自适应蝙蝠算法的室内RFID定位算法

谢良波, 李宇洋, 王勇, 周牧, 聂伟

重庆邮电大学通信与信息工程学院，重庆 400065

修回日期:2022-08-03 出版日期:2022-08-25 发布日期:2022-08-01
作者简介:谢良波（1986- ），男，四川成都人，博士，重庆邮电大学副教授、硕士生导师，主要研究方向为射频识别技术、室内定位技术等
李宇洋（1997- ），男，四川宜宾人，重庆邮电大学硕士生，主要研究方向为室内射频识别定位技术
王勇（1987- ），男，云南邵通人，博士，重庆邮电大学讲师、硕士生导师，主要研究方向为室内定位、深度学习等
周牧（1984- ），男，重庆人，博士，重庆邮电大学教授、博士生导师，主要研究方向为无线定位、参数估计、机器学习等
聂伟（1987- ），男，重庆人，博士，重庆邮电大学讲师、硕士生导师，主要研究方向为射频识别技术、室内定位技术、电磁场与微波技术等
基金资助:
国家自然科学基金资助项目(62101085);重庆市教委科学技术研究基金资助项目(KJZD-K202000605);重庆市研究生科研创新基金资助项目(CYS22473);重邮信通青创团队支持计划基金资助项目(SCIE-QN-2022-06)

Indoor RFID localization algorithm based on adaptive bat algorithm

Liangbo XIE, Yuyang LI, Yong WANG, Mu ZHOU, Wei NIE

School of Communication and Information Engineering, Chongqing University of Posts and Telecommunications, Chongqing 400065, China

Revised:2022-08-03 Online:2022-08-25 Published:2022-08-01
Supported by:
The National Natural Science Foundation of China(62101085);Science and Technology Research Program of Chongqing Municipal Education Commission(KJZD-K202000605);Chongqing Graduate Scientific Research Innovation Project(CYS22473);Youth Innovation Group Support Program of ICE Discipline of CQUPT(SCIE-QN-2022-06)

摘要/Abstract

摘要：

针对传统超高频射频识别室内定位算法中利用几何方法定位耗时较长且定位精度较差的问题，提出了一种基于自适应蝙蝠算法（ABA）的室内 RFID 定位算法。首先，利用跳频技术获取多频率相位，基于多重信号分类（MUSIC）算法的角度信息和聚类的距离信息建立蝙蝠算法位置评估函数；其次，利用 Tent 反向学习初始化蝙蝠位置增加种群的多样性，并引入自适应权重因子更新蝙蝠位置；最后，基于位置评估函数对目标位置进行迭代搜索，实现快速厘米级定位。实验结果表明，所提算法的中值定位误差为 7.74 cm，且实时性比基于中国剩余定理（CRT）的传统定位算法提升了12倍。

关键词: 射频识别, 室内定位算法, 帐篷反向学习, 自适应蝙蝠算法

Abstract:

Aiming at the problem that long time-consuming and poor positioning accuracy using geometric method in the traditional UHF RFID indoor localization algorithm, an RFID indoor positioning algorithm based on adaptive bat algorithm (ABA) was proposed.Firstly, the phase of multiple frequency points was obtained by frequency hopping technology, and the location evaluation function of bat algorithm was established based on the angle information of multiple signal classification (MUSIC) algorithm and the distance information of clustering.Secondly, the bat location was initialized by tent reverse learning to increase the diversity of the population, and the adaptive weight factor was introduced to update the bat location.Finally, the target position was searched iteratively based on the position evaluation function to achieve fast centimeter level positioning.Experimental results show that the median localization error of the proposed algorithm is 7.74 cm, and the real-time performance is improved by 12 times compared with the traditional positioning algorithm based on the Chinese remainder theorem (CRT).

Key words: radio frequency identification, indoor location algorithm, tent reverse learning, adaptive bat algorithm

中图分类号:

TN99

谢良波, 李宇洋, 王勇, 周牧, 聂伟. 基于自适应蝙蝠算法的室内RFID定位算法[J]. 通信学报, 2022, 43(8): 90-99.

Liangbo XIE, Yuyang LI, Yong WANG, Mu ZHOU, Wei NIE. Indoor RFID localization algorithm based on adaptive bat algorithm[J]. Journal on Communications, 2022, 43(8): 90-99.

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蝙蝠数/个	X轴平均误差/cm	Y轴平均误差/cm	平均定位误差/cm	平均耗时/s
50	6.01	15.73	17.75	0.11
100	3.34	9.08	10.23	0.23
150	3.41	7.40	8.73	0.36
200	2.78	7.29	8.23	0.48
300	2.61	6.38	7.37	0.74
500	2.59	5.52	6.54	1.19

设备	用途
无源标签H47	定位目标
全向天线VERT900	发射信号
Impinj R420	与标签建立通信，频率为924.125 MHz
USRP N210	共4台，一台用于发射跳频信号，3台用于
	接收经标签发射的信号
PC	控制收发设备，处理数据
时钟源	型号为OctoClock-G CDA-2990，用于控制
	接收机和发射机时钟同步

定位算法	部署需求	定位范围	中位数误差/cm
文献[10]	定向三天线	4 m×4 m	9.35
文献[11]	移动单天线	室外操场8 m×8 m	6
文献[12]	移动双天线	1.2 m×2.2 m	9
文献[13]	定向双天线	2.4 m×8 m	5.01
本文算法	单站三天线	4 m×4 m	7.74

基于自适应蝙蝠算法的室内RFID定位算法

Indoor RFID localization algorithm based on adaptive bat algorithm

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