Through-the-Wall Image Reconstruction via Reweighted Total Variation and Prior Information in Radio Tomographic Imaging

This paper focuses on the application of radio tomographic imaging in through-the-wall image reconstruction. By using the simple wireless communication devices, e.g., Wi-Fi cards, the whole building layout can be reconstructed with only the received signal strength (RSS). For the reconstruction algo...

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Bibliographic Details
Published inIEEE access Vol. 8; pp. 40057 - 40066
Main Authors Guo, Qichang, Li, Yanlei, Liang, Xingdong, Dong, Jiawei, Cheng, Ruichang
Format Journal Article
LanguageEnglish
Published Piscataway IEEE 2020
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects
Algorithms
Buildings
Electronic devices
Image reconstruction
Layout
Minimization
Optimization
Prior information
radio tomographic imaging
Receiving antennas
Regularization
Root-mean-square errors
Signal strength
through-the-wall
total variation (TV) minimization
Transmitting antennas
Wi-Fi
Wireless communications
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Summary:This paper focuses on the application of radio tomographic imaging in through-the-wall image reconstruction. By using the simple wireless communication devices, e.g., Wi-Fi cards, the whole building layout can be reconstructed with only the received signal strength (RSS). For the reconstruction algorithms, the total variation (TV) minimization algorithm has been used to reconstruct the image. However, some false artifacts may exist in the image results due to the inherent defects of the algorithm. The artifacts can be misestimated as wall structures. In this paper, a reweighted total variation and prior information regularization algorithm named as RTV-PIR is proposed to reconstruct the image. This algorithm is based on the TV minimization of the image. And the prior information that the wall is only oriented horizontally or vertically is also considered simultaneously, which is used to keep the wall orientation. To verify the performance of the proposed algorithm, the simulations and experiments based on real data are conducted. It is shown that the RTV-PIR algorithm can get a better result with respect to the root mean square error (RMSE) and the structural similarity (SSIM), in comparison with the state-of-the-art algorithms.
ISSN:2169-3536
2169-3536
DOI:10.1109/ACCESS.2020.2976769