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Regularization Methods for Radio Tomographic Imaging

Radio Tomographic Imaging (RTI) is an emerging technology that uses received signal strength measurements to image the attenuation of objects within a wireless network area. RTI is by nature an ill-posed inverse problem, therefore, regularization techniques must be utilized to obtain accurate images. This paper discusses some common regularization techniques, including Tikhonov, truncated singular value decomposition, and total variation, and presents the results of applying them to RTI.