Title :
RSS-Based Localization via Bayesian Ranging and Iterative Least Squares Positioning
Author :
Coluccia, Angelo ; Ricciato, Fabio
Author_Institution :
Dipt. di Ing. dell´Innovazione, Univ. of Salento, Lecce, Italy
Abstract :
In the framework of range-based localization from {Received Signal Strength} (RSS) measurements, we propose a novel Bayesian formulation of the ranging problem alternative to the common approach of inverting the Path-Loss formula. Additionally, we consider an alternative to the conventional lateration stage based on an Iterative Least Squares (ILS). Numerical results show that the combination of the proposed approaches improves considerably the accuracy of range-based localization with only a slight increase of computational complexity, thus reducing the gap with the more complex range-free methods.
Keywords :
Bayes methods; computational complexity; iterative methods; least mean squares methods; radionavigation; sensor placement; Bayesian ranging; RSS measurement; RSS-based localization; complex range free method; computational complexity; iterative least square positioning; path loss formula; range-based localization; received signal strength; Accuracy; Bayes methods; Distance measurement; Maximum likelihood estimation; Robustness; Topology; Bayesian estimation; Localization; least squares; maximum likelihood; positioning; wireless;
Journal_Title :
Communications Letters, IEEE
DOI :
10.1109/LCOMM.2014.040214.132781