Abstract
Wireless signal RSSI (Received Signal Strength Indication) is widely used in indoor localization. However, due to severe multipath effect in indoor environment, RSSI measured by the user equipment varies in a large range. Inaccurate RSSI measurement yields large localization error and decreases the performance of indoor localization and navigation. Through extensive tests, we prove that the variance of RSSI in indoor environment does not keep the same all the time, while varies with the mean of RSSI. In this paper, we analyze the relationship between the mean value and variance of RSSI, and propose a novel Weighted Distance Fingerprint (WDF) algorithm, which assigns different weights to different RSSI measurements based on its variance. We apply the proposed WDF algorithm in our indoor localization testbed, and evaluation result shows that WDF reach a 0.8m to 2m improvement on the average localization error.
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