Indoor RFID localization algorithm based on adaptive bat algorithm

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

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

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Indoor RFID localization algorithm based on adaptive bat algorithm

Papers | 更新时间：2024-06-05

- Indoor RFID localization algorithm based on adaptive bat algorithm
- Journal on Communications Vol. 43, Issue 8, Pages: 90-99(2022)
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- DOI：10.11959/j.issn.1000-436x.2022159
  CLC： TN99
- Online First：2022-08，
  
  Published：25 August 2022
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Liangbo XIE, Yuyang LI, Yong WANG, et al. Indoor RFID localization algorithm based on adaptive bat algorithm[J]. Journal on Communications, 2022, 43(8): 90-99.
DOI：

Liangbo XIE, Yuyang LI, Yong WANG, et al. Indoor RFID localization algorithm based on adaptive bat algorithm[J]. Journal on Communications, 2022, 43(8): 90-99. DOI： 10.11959/j.issn.1000-436x.2022159.

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。

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).

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references

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TAN Xi1

CHANG Ruo-ting2

HUANG Chen-ling1

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State Key Laboratory of ASIC ＆ System,Fudan University,Shanghai 201203,China 2.State Radio Regulatory Committee,Ministry of Idustry and Information Technology of the People’s Republic of China

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