In fingerprint-based wireless positioning, a high number of wireless access points solicits feature reduction to obtain a compact radio map for accurate real-time positioning. Although principal component analysis (PCA) can be used to reduce dimensionality, PCA is computationally expensive. Additionally, PCA maps the data to a new space where physical meaning of the original features is lost. Presented is a faster features reduction approach using fast orthogonal search which selects the most informative features in the original space. The algorithm is applied to select the most informative access points in a radio map for accurate real-time wireless positioning. Experiments demonstrate the proposed method's superior performance to PCA in terms of speed and slightly better performance in terms of accuracy.

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Journal Electronics Letters
Atia, M, Korenberg, M.J. (M. J.), & Noureldin, A. (A.). (2011). Fast features reduction of radio maps for real-time fingerprint-based wireless positioning systems. Electronics Letters, 47(20), 1151–1153. doi:10.1049/el.2011.2567