Wi-Fi Fingerprint Localization Uniting Spline Interpolation

ZHAO Wanlong; TIAN Xinyuan; CHEN Chao; LIU Gongliang; LI Bo

doi:10.11999/JEIT230116

Volume 46 Issue 9

Sep. 2024

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Article Navigation > Journal of Electronics & Information Technology > 2024 > 46(9): 3563-3570

ZHAO Wanlong, TIAN Xinyuan, CHEN Chao, LIU Gongliang, LI Bo. Wi-Fi Fingerprint Localization Uniting Spline Interpolation[J]. Journal of Electronics & Information Technology, 2024, 46(9): 3563-3570. doi: 10.11999/JEIT230116

Citation:

ZHAO Wanlong, TIAN Xinyuan, CHEN Chao, LIU Gongliang, LI Bo. Wi-Fi Fingerprint Localization Uniting Spline Interpolation[J]. Journal of Electronics & Information Technology, 2024, 46(9): 3563-3570. doi: 10.11999/JEIT230116

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Wi-Fi Fingerprint Localization Uniting Spline Interpolation

doi: 10.11999/JEIT230116

School of Information Science and Engineering, Harbin Institute of technology (Weihai), Weihai 264200, China

Funds: The National Natural Science Foundation of China (62101158, 62171154), The Natural Science Foundation of Shandong (ZR2021QF004)

Received Date: 2023-03-01
Rev Recd Date: 2024-07-20

Available Online: 2024-07-29

Publish Date: 2024-09-26

Abstract

Abstract

In order to reduce the cost of the existing Wi-Fi indoor positioning technology algorithm and ensure the positioning accuracy, a Wi-Fi fingerprint matching positioning algorithm uniting Spline interpolation is proposed in this paper. In terms of constructing the signal strength fingerprint database, the construction of a sparse fingerprint database is proposed, which greatly reduces the workload and hardware requirements of data collection. In addition, the combination of hybrid filtering and spline interpolation method is proposed to enrich the sparse fingerprint database. In terms of interpolation of the signal strength fingerprint database, after the same degree of hybrid filtering, compared with the known Inverse Distance Weighting(IDW) interpolation algorithm, the spline interpolation method can accurately fill the database and achieve higher positioning accuracy. In terms of fingerprint matching and positioning, matching algorithms such as K-Nearest Neighbor(KNN) are used to achieve high-precision positioning. Simulation experiments show that the proposed Wi-Fi fingerprint positioning method uniting spline interpolation can ensure high positioning accuracy under the premise of only building a low-cost sparse fingerprint database.
- Indoor localization,
- Wi-Fi,
- Interpolation

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References(15)

References

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