In recent years, radio tomographic imaging (RTI) is an emerging device-free localization (DFL) technology enabling the localization of people and other objects without requiring them to carry any electronic device. Different from other DFL techniques, the RTI method makes use of the changes of received signal strength (RSS) measured on links of the network to estimate the radio frequency (RF) attenuation field and forms an image of the changed field. This image is then used to infer the locations of targets within the deployed network. However, there still lacks an efficient scheme which can achieve robust location estimation performance with low computational cost. To solve this problem, we propose a lightweight robust RTI approach in this paper. The proposed method not only can reduce the algorithm's storage and computational resource requirements, but also exploits the location information of wireless measurement nodes to improve the accuracy of the localization result, which ensures its robust performance. The effectiveness and robustness of the proposed scheme are demonstrated by experimental results where the proposed algorithm yields substantial improvement for localization performance and complexity.
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