RSS-Based Localization via Bayesian Ranging and Iterative Least Squares Positioning

Angelo Coluccia, Fabio Ricciato

    Research output: Contribution to journalArticlepeer-review

    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.
    Original languageEnglish
    Pages (from-to)873-876
    Number of pages4
    JournalIEEE Communications Letters
    DOIs
    Publication statusPublished - 2014

    Research Field

    • Former Research Field - Mobility Systems

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