Near range microwave 3D imaging algorithm based on L1 optimization in range direction for target feature enhancements

Near range microwave three-dimensional (3D) imaging system, which is based on the principle of synthetic aperture radar, can reconstruct the 3D complex image of observing object and obtain object information including shape, structure and scattering characteristics. The system has advantages of high precision, penetrating, non-ionizing radiation. Therefore, it is widely applied in the fields of hidden items detect under human body, biomedical imaging, and so on. The basic principle of the system can be described as follows. In range direction, it transmits and receives broadband electromagnetic signals to achieve high-resolution. At the same time, it achieves two-dimensional azimuth resolution by constructing mechanical synthetic aperture or array real aperture in two orthogonal directions. In near range observing applications, the observing scene is usually complex target, leading to the non-sparsity in azimuth directions of echo data. However, the echo data is sparse in range direction due to the limited penetration of microwave imaging. By analyzing the signal sparsity in range direction of near range microwave 3D imaging, this paper introduces L1 optimization reconstruction method into near range imaging and focuses on the study of target feature enhancement method based on L1 optimized. In detail, the near range 3D imaging geometry and echo model are established in Section 2 and signal sparsity in range direction is also analyzed in this section. Then, L1 optimization method is applied to 3D imaging and the imaging algorithm is deduced in Section 3, and two-step iterative shrinkage (TwIST) method is adopted to achieve the range reconstruction. In Sections 4 and 5, the target feature enhancement performance based on the imaging algorithm of this paper is verified via numerical simulation and near range microwave 3D imaging experiments.