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山东大学学报 (工学版) ›› 2019, Vol. 49 ›› Issue (5): 112-118.doi: 10.6040/j.issn.1672-3961.0.2018.356

• 机器学习与数据挖掘 • 上一篇    下一篇

基于CSI的轻量级自适应井下定位算法

岳俊梅1(),张冬梅2   

  1. 1. 山西工程技术学院信息工程与自动化系, 山西 阳泉 045000
    2. 太原理工大学信息与计算机学院, 山西 晋中 030600
  • 收稿日期:2018-08-24 出版日期:2019-10-20 发布日期:2019-10-18
  • 作者简介:岳俊梅(1971—),女,山西平定人,硕士研究生,副教授,主要研究方向为无线传感器网络. E-mail:212435689@qq.com
  • 基金资助:
    国家自然科学基金项目(61401300);山西省应用基础研究项目(201601D021074);山西工程技术学院校级课题(201706003)

Lightweight self-adaptive CSI-based positioning algorithm in underground mine

Junmei YUE1(),Dongmei ZHANG2   

  1. 1. Department of Information Engineering and Automation, Shanxi Institute of Technology, Yangquan 045000, Shanxi, China
    2. College of Information and Computer Science, Taiyuan University of Technology, Jinzhong 030600, Shanxi, China
  • Received:2018-08-24 Online:2019-10-20 Published:2019-10-18
  • Supported by:
    国家自然科学基金项目(61401300);山西省应用基础研究项目(201601D021074);山西工程技术学院校级课题(201706003)

摘要:

针对传统井下定位成本高、工作危险系数大的问题,提出一种基于信道状态信息(channel state information, CSI)的轻量级自适应井下定位(lightweight self-adaptive underground positioning algorithm, LSA)方法。LSA方法以细粒度的CSI替代粗粒度的接收信号强度(received signal strength indicator, RSSI)来获得更高的定位精度,采用逆傅里叶变换将原始CSI数据转换为信道脉冲响应,以此选取视距信号,并通过构建CSI视距信号衰减模型实现轻量级的精确测距;基于井下现有WiFi网络中的访问接入点(access points, APs)位置和井下巷道特征,计算目标相对AP的方向,根据方向和测距结果完成定位。该方法能够自适应于AP在巷道中的任意位置部署,并利用拐角识别优化算法进一步提高定位的精度。试验结果表明,该方法能够使得定位中位数误差达到0.53 m,且无需在井下单独部署任何定位系统,性能明显优于已提出的CDPF、FILA等其他定位算法。

关键词: 信道状态信息, 信号衰减模型, 井下定位

Abstract:

To solve the problem of high cost and working hazard factor of traditional downhole positioning methods, a lightweight self-adaptive CSI-based positioning algorithm in underground mine was proposed. The fine-grained CSI was used to obtain higher positioning accuracy rather than coarse-grained RSSI, inverse fast Fourier transform was adopted to transform CSI data to channel impulse response so as to get the line-of-sight signal, an attenuation model of line-of-sight signal of CSI was built to implement accurate ranging, position features of existing point access points (APs) in wireless fidelity and characteristics of rock roadways was utilized to calculate orientation of target relative to AP, which finally completed location according to orientation and distance. LSA was adaptive to arbitrary deployment modes, and the corner recognition optimization algorithm was used to improve positioning accuracy. The experimental results showed that LSA method median error could reach 0.53 m and eliminate the need to deploy any positioning system in the well alone, the performance was superrior to CDPF and FILA.

Key words: channel state information, signal attenuation model, underground positioning

中图分类号: 

  • TP391

图1

定位算法框架"

图2

原始CSI数据"

图3

不同时延的信号强度变化"

图4

不同路径下的功率二次变化率随时间变化情况"

图5

巷道环境及AP部署场景"

图6

测距结果"

图7

不同采样次数的方向识别准确度"

图8

不同采样次数的拐点识别准确度"

图9

不同方法距离误差的累积分布图"

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