电信科学 ›› 2017, Vol. 33 ›› Issue (1): 9-15.doi: 10.11959/j.issn.1000-0801.2017020

• 研究与开发 • 上一篇    下一篇

基于线性内插法改进的室内定位算法

张梦丹,卢光跃,王宏刚,刘继明   

  1. 西安邮电大学,陕西 西安710121
  • 修回日期:2017-01-10 出版日期:2017-01-01 发布日期:2017-06-04
  • 作者简介:张梦丹(1990-),女,西安邮电大学硕士生,主要研究方向为通信网技术。|卢光跃(1971-),男,博士,西安邮电大学通信工程学院教授,主要研究方向为现代移动通信中信号处理。|王宏刚(1977-),男,博士,西安邮电大学讲师,主要研究方向为物理层能源效率和通信协议的设计、RFID和无线定位。|刘继明(1964-),男,博士,西安邮电大学教授,主要研究方向为下一代软交换核心技术。
  • 基金资助:
    陕西省工业科技攻关项目(2014K05-09);陕西省教育厅科学研究计划项目(14JK1660)

An improved indoor location algorithm based on linear interpolation

Mengdan ZHANG,Guangyue LU,Honggang WANG,Jiming LIU   

  1. Xi'an University of Posts and Telecommunications,Xi'an 710121,China
  • Revised:2017-01-10 Online:2017-01-01 Published:2017-06-04
  • Supported by:
    Shaanxi Industrial Science and Technology Project(2014K05-09);Shaanxi Science Research Program of Education Department(14JK1660)

摘要:

针对室内位置指纹定位技术存在的离线阶段工作量大、定位精度有限、顽健性较差的缺点,提出了一种基于线性内插法改进的指纹定位匹配算法。与传统位置指纹定位技术相比,该算法不仅降低了整体工作量,而且降低了多径效应造成的不利影响。最后搭建实验场景对该算法定位性能进行测试。实验数据显示,该算法与WKNN法相比,平均定位精度大约提高了34.25%,绝大部分待测点的定位误差在0.4 m 以内,验证了所提算法在定位精度、顽健性和适应环境变化方面的优势。

关键词: 室内定位, 位置指纹, WKNN, PCA, 线性内插法

Abstract:

Aiming at the shortcomings of heavy workload in the off-line phase,limited positioning accuracy and poor robustness of indoor location fingerprint positioning technology,an improved fingerprint matching algorithm based on linear interpolation was proposed.Compared with the traditional location fingerprint positioning technology,it reduced the overall workload as well as the bad effects caused by muti-path effect.At last,a lab scene was set up to test the positioning performance of this algorithm.It is shown by the test that the average positioning accuracy of this algorithm has been improved by 34.25% compared with that of WKNN method,and the positioning accuracy error ratio of most points to be test is within 0.4 m,the positioning accuracy,robustness and adaptability in environment change were demonstrated.

Key words: indoor location, location fingerprint, weighted K-nearest neighbor, principal component analysis, linear interpolation

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