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http://dx.doi.org/10.14372/IEMEK.2012.7.2.085

Database Investigation Algorithm for High-Accuracy based Indoor Positioning  

Song, Jin-Woo (영남대학교 정보통신공학과)
Hur, Soo-Jung (영남대학교 정보통신공학과)
Park, Yong-Wan (영남대학교 정보통신공학과)
Yoo, Kook-Yeol (영남대학교 정보통신공학과)
Publication Information
IEMEK Journal of Embedded Systems and Applications / v.7, no.2, 2012 , pp. 85-93 More about this Journal
Abstract
In this paper, we proposed Wireless LAN (WLAN) localization method that enhances database construction based on weighting factor and analyse the characteristic of the WLAN received signals. The weighting factor plays a key role as it determines the importance of Received Signal Strength Indication (RSSI) value from number of received signals (frequency). The fingerprint method is the most widely used method in WLAN-based positioning methods because it has high location accuracy compare to other indoor positioning methods. The fingerprint method has different location accuracies which depend on training phase and positioning phase. In training phase, intensity of RSSI is measured under the various. Conventional systems adapt average of RSSI samples in a database construction, which is not quite accurate due to variety of RSSI samples. In this paper, we analyse WLAN RSSI characteristic from anechoic chamber test, and analyze the causes of various distributions of RSSI and its influence on location accuracy in indoor environments. In addition, we proposed enhanced weighting factor algorithm for accurate database construction and compare location accuracy of proposed algorithm with conventional algorithm by computer simulations and tests.
Keywords
WLAN; LBS; Fingerprint; RSSI; Dynamic range; Location; Weighting average;
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