A Research on Algorithm of Building Wi-Fi Location Fingerprint Database

Zeng Bi; Mao Qin

doi:10.3969/j.issn.1007-7162.2016.02.010

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A Research on Algorithm of Building Wi-Fi Location Fingerprint Database

更新时间：2026-05-27

- A Research on Algorithm of Building Wi-Fi Location Fingerprint Database
- Vol. 33, Issue 2, Pages: 51-56(2016)
- 作者机构：
- 作者简介：
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- DOI：10.3969/j.issn.1007-7162.2016.02.010
  CLC：
- Online First：23 March 2016，
  
  Published：2016
- 稿件说明：
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曾碧, 毛勤. 改进的构建Wi-Fi位置指纹库算法研究[J]. 广东工业大学学报, 2016, 33(2): 51-56.

Zeng Bi, Mao Qin. A Research on Algorithm of Building Wi-Fi Location Fingerprint Database[J]. 2016, 33(2): 51-56.
曾碧, 毛勤. 改进的构建Wi-Fi位置指纹库算法研究[J]. 广东工业大学学报, 2016, 33(2): 51-56. DOI： 10.3969/j.issn.1007-7162.2016.02.010.

Zeng Bi, Mao Qin. A Research on Algorithm of Building Wi-Fi Location Fingerprint Database[J]. 2016, 33(2): 51-56. DOI： 10.3969/j.issn.1007-7162.2016.02.010.

摘要

针对传统的位置指纹算法在更新位置指纹库时人力和物力巨大耗费的问题，提出利用压缩传感理论和重心拉格朗日插值算法来更新位置指纹库.压缩传感理论将指纹向量的重构过程转换为一个最小

范数的优化问题，并通过最小全变分方法求解原始指纹向量.重心拉格朗日插值算法利用样本节点间的空间相关性，使得在离线阶段通过测量少量指纹就可重建位置指纹库.在真实室内环境的实验验证了压缩传感恢复算法比重心拉格朗日插值算法具有更好的定位性能.

Abstract

To solve the problem of high cost in updating the fingerprint database in terms of time and effort

the theory of compressed sensing and focus Lagrange interpolation algorithm are proposed in the offline phase. The process of fingerprint vector refactoring is transformed into the problem of minimum

norm optimization by compressed sensing

and total variation is used to recover the original fingerprint vector. Focus Lagrange interpolation algorithm takes the advantage of spatial correlation of sample nodes

by which the fingerprint database can be rebuilt through measuring a small amount of fingerprints. Finally a practical experiment in real indoor environment shows that the theory of compressed sensing achieves higher accuracy than focus Lagrange interpolation algorithm.

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