Adaptive Distance Estimation and Localization in WSN using RSSI Measures

Authors:
Abdalkarim Awad;Thorsten Frunzke;Falko Dressler
Affiliations:
University of Erlangen;University of Erlangen;University of Erlangen
Venue:
DSD '07 Proceedings of the 10th Euromicro Conference on Digital System Design Architectures, Methods and Tools
Year:
2007

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Abstract

Localization is one of the most challenging and important issues in wireless sensor networks (WSNs), especially if cost-effective approaches are demanded. In this paper, we present intensively discuss and analyze approaches relying on the received signal strength indicator (RSSI). The advantage of employing the RSSI values is that no extra hardware (e.g. ultrasonic or infra-red) is needed for network-centric localization. We studied different factors that affect the measured RSSI values. Finally, we evaluate two methods to estimate the distance; the first approach is based on statistical methods. For the second one, we use an artificial neural network to estimate the distance.