Abstract
To solve the problem of time-varying in wireless local area network (WLAN) indoor positioning, an adaptive wavelet threshold analysis (AWTA) method was proposed in this paper. The received signal strength (RSS) can be analyzed by wavelet multiresolution analysis, and the position of mutation signal can be found according to the decomposed signal. The wavelet coefficient thresholds can be dynamically adjusted due to the complex indoor environment, and the mutation signal can be filtered by dynamic thresholds. Experimental results show that the localization error with the proposed method, median filter and mean filter can be reduced by 1.18, 1.01, and 1.05 m respectively compared with such without processing. The proposed method of this paper has good localization results.
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Funding
This work was supported by National Natural Science Fund Projects of China (project nos. 61572366 and 61702375), Anhui Natural Science Foundation of China (project no. 1908085MF213), the Natural Science Foundation of Anhui Higher Education Institutions of China (project no. KJ2021ZD0116), Anhui University provincial natural science research project of China (project nos. KJ2019A0631 and KJ2021A0937), The Chinese Ministry of Education collaborative education projects (project nos. 201802027037, 20180202023, and 201802302021), Top-Notch Talent Academic Funding Project of University Discipline (Professional) (project no. gxbjZD2020084), and Youth projects of West Anhui University (project nos. WXXY2021076 and WXZR201907).
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For research articles with several authors, Xuemei Zhu and Shirong Li conceived and designed the research. Xiancun Zhou, Zusong Li and Xuemei Zhu performed the experiments and analyzed the result. Xuemei Zhu and Shirong Li wrote the paper.
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Xuemei Zhu, Li, Z., Li, S. et al. Indoor Localization Method Based on Adaptive Wavelet Threshold Analysis. Aut. Control Comp. Sci. 57, 523–533 (2023). https://doi.org/10.3103/S0146411623050127
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DOI: https://doi.org/10.3103/S0146411623050127