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International Journal of Antennas and Propagation
Volume 2017 (2017), Article ID 1480623, 11 pages
Research Article

Three-Dimensional Microwave Imaging for Concealed Weapon Detection Using Range Stacking Technique

1School of Information Engineering, Inner Mongolia University of Technology, Hohhot 010051, China
2Inner Mongolia Key Laboratory of Radar Technology and Application, Hohhot 010051, China
3School of Electronics and Information Engineering, Beihang University, Beijing 100191, China
4School of Communication and Information Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China

Correspondence should be addressed to Weixian Tan

Received 12 April 2017; Accepted 12 June 2017; Published 7 August 2017

Academic Editor: Matteo Pastorino

Copyright © 2017 Weixian Tan et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Three-dimensional (3D) microwave imaging has been proven to be well suited for concealed weapon detection application. For the 3D image reconstruction under two-dimensional (2D) planar aperture condition, most of current imaging algorithms focus on decomposing the 3D free space Green function by exploiting the stationary phase and, consequently, the accuracy of the final imagery is obtained at a sacrifice of computational complexity due to the need of interpolation. In this paper, from an alternative viewpoint, we propose a novel interpolation-free imaging algorithm based on wavefront reconstruction theory. The algorithm is an extension of the 2D range stacking algorithm (RSA) with the advantages of low computational cost and high precision. The algorithm uses different reference signal spectrums at different range bins and then forms the target functions at desired range bin by a concise coherent summation. Several practical issues such as the propagation loss compensation, wavefront reconstruction, and aliasing mitigating are also considered. The sampling criterion and the achievable resolutions for the proposed algorithm are also derived. Finally, the proposed method is validated through extensive computer simulations and real-field experiments. The results show that accurate 3D image can be generated at a very high speed by utilizing the proposed algorithm.