Abstract
In order to improve the efficiency and robustness of device-free
localization (DFL) systems in harsh environments, this letter proposed
an iterative log thresholding algorithm for DFL in subspace. The log
regularizer is taken as the constraint to optimize the object function.
To meet the requirement of real-time performance, the dimensions of
learning dictionary and observed vector are reduced with principal
component analysis (PCA), and the sparse coefficient vector is
iteratively computed with sparse coding algorithm. Eventually, by
projecting the reference points (RPs) index of the coefficient vectors
to the location of objects, the location is estimated. Numerical
experiment verified the effectiveness of the proposed algorithm over the
alternatives.