Indoor Localization Method Based on Adaptive Wavelet Threshold Analysis

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.