Observed that most setups have limitations in the number of RF nodes due to a limited number of measurements. However, it is well known that the main difficulty in radio tomographic imaging attributes to the uncertainties in the receive signal strength (RSS) measurements of transceivers due to multipath effects, especially, when the environment of interest is much cluttered, and requirements on the larger number of nodes for the performance improvements. However, no study has been conducted to solve the inverse problem and improve the quality of the reconstructed image using a reduced sensor model for Radio tomography system localization. This work focuses on the design and development of a Radio tomography system for human localization that will employ a transceiver sensor arrangement to increase the number of measurements, without making any changes to the hardware design as well as the number of pixels in the sensing domain. An image reconstruction technique namely, Adjacent Criterion Method (ACM) was proposed to enhance the image spatial resolution. A number of experiments were used to evaluate the performance of the system. The results showed that the proposed technique improves the spatial resolution and exhibits more accurate tomograms
