系统仿真学报 ›› 2018, Vol. 30 ›› Issue (9): 3586-3595.doi: 10.16182/j.issn1004731x.joss.201809046

• 短文 • 上一篇    

一种基于BP神经网络的VIRE改进算法研究

孔红山, 郁滨   

  1. 信息工程大学,郑州 450001
  • 收稿日期:2017-01-09 出版日期:2018-09-10 发布日期:2019-01-08
  • 作者简介:孔红山(1981-),男,河南濮阳,博士生,副教授,研究方向为室内定位; 郁滨(1964-),男,河南郑州,博士,教授,博导,研究方向为信息安全、无线网络安全技术、视觉密码等。

An Improved Algorithm of VIRE Based on BP Neural Network

Kong Hongshan, Yu Bin   

  1. Information Engineering University, Zhengzhou 450001, China
  • Received:2017-01-09 Online:2018-09-10 Published:2019-01-08

摘要: 针对VIRE算法中阈值选择影响定位精度的问题,提出一种BP神经网络与VIRE相结合的射频识别定位方法(简称BP-VIRE)。BP-VIRE采用与VIRE算法相同的阅读器配置与部署,以参考标签的RSSI值和坐标值作为训练样本,采用误差反传训练的BP算法构建基于神经网络的定位模型。仿真结果表明,与VIRE相比,本算法在平均误差、最大误差、边界区域误差等定位性能方面得到较大提升,更适合于室内定位系统中的应用。

关键词: 室内定位, BP神经网络, VIRE, 射频识别, RSSI

Abstract: Aimed at the problem that the proper threshold affects the accuracy of positioning in VIRE algorithm, a RFID positioning method combining BP neural networks with VIRE algorithm is presented and is named BP-VIRE. BP-VIRE utilizes the same reader’s configuration and deployment as that of VIRE, and regards referenced tag RSSI and coordinate values as training samples, and constructs the positioning model based on neural networks with the help of BP algorithm which uses the method of error back propagation. According to the simulation results, compared with VIRE, BP-VIRE performance is better in the capability of positioning, esp. in the aspects of average deviation, maximum deviation, and boundary area deviation, so the improved method is more suitable for indoor positioning application in comparison with VIRE.

Key words: indoor positioning, BP neural networks, virtual reference, radio frequency identification, received signal strength indicator

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