Towards real‐time through‐obstacle imaging based on compressed sensing for sparse objects. Issue 13 (22nd July 2019)

• Record Type: Journal Article
• Authors: Zhou, Tianyi; Shen, Fazhong; Meng, Qingyang; Li, Huan; Xu, Kuiwen; Ye, Dexin; Huangfu, Jiangtao; Dong, Shiwei; Denidni, Tayeb Ahmed; Ran, Lixin
• Is Part Of: IET microwaves, antennas & propagation. Volume 13:Issue 13(2019)
• Page Start: 2290
• Page End: 2296
• Publication Date: 2019-07-22
• Subjects: optimisation -- compressed sensing -- microwave imaging -- image reconstruction -- transmitting antennas -- antenna arrays; closed obstacle -- imaging equations -- inverse‐scattering problem -- spatial sparsity -- compressed imaging -- time‐division multiantenna setup -- reduced transmitting antennas -- spatial compressed sensing -- sparse imaging region -- imaging time -- conventional twofold subspace‐based optimisation method -- comparable imaging quality -- entire imaging area -- microwave imaging systems -- through‐obstacle imaging -- sparse objects -- real‐time imaging -- complex‐structured objects; Microwaves -- Periodicals; Microwave antennas -- Periodicals; Antennas (Electronics) -- Periodicals; Radio wave propagation -- Periodicals; Microwave communication systems -- Periodicals; 621.381305
• DOI: 10.1049/iet-map.2019.0238
• Languages: English
• ISSNs: 1751-8725

Abstract

Abstract : Although significant progress has been made in microwave imaging, real‐time imaging, especially for objects behind walls or closed obstacles, remains a technical challenge. In this work, highly efficient imaging for complex‐structured objects surrounded by a closed obstacle was experimentally demonstrated. The imaging equations are derived based on a combination of the inverse‐scattering problem and the concept of compressed sensing. Making use of the spatial sparsity of objects and obstacles, the compressed imaging can be implemented using a time‐division multi‐antenna setup with reduced transmitting antennas. Owing to the spatial compressed sensing applied to the sparse imaging region and objects, the imaging time can be reduced by two orders of magnitude compared with the conventional twofold subspace‐based optimisation method with a comparable imaging quality. Taking advantage of the sparsity of the entire imaging area, objects with larger relative permittivity can also be reconstructed. The proposed method can be potentially used in applications such as security examination through boxes. It also provides a new clue for solving the practicability difficulty faced by existing microwave imaging systems.