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Enhancing Positioning Accuracy Through Direct Position Estimators Based on Hybrid RSS Data Fusion

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Executive Summary

In this paper, localization based on Received Signal Strength (RSS) is investigated assuming a path loss log normal shadowing model. On the one hand, indirect RSS-based estimation schemes are investigated; these schemes are based on two steps of estimation: estimation of ranges from RSS and then estimation of position using weighted least square approximation. The authors show that the performances of this type of schemes depend on the used estimator in the first step. They suggest that typical median estimator must be replaced by maximum likelihood estimator (mode) to enhance the positioning accuracy.

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