Development of Fast Fourier-Compatible Image Reconstruction for 3D Near-Field Bistatic Microwave Imaging With Dynamic Metasurface Antennas

Abstract

Emerging dynamic metasurface antennas (DMAs) technology promises to achieve future wireless communications by reducing hardware costs, physical size and power consumption. Especially in the field of radar imaging, they can be used as an effective alternative platform for modern computational imaging; because they can simplify the physical hardware and increase the data acquisition rate. Fourier transform (FT)-based scene image reconstruction techniques are known as cost-effective computing solutions for the imaging system processing unit. However, due to the physical layer compression in DMAs and the fact that they do not produce uniform radiation patterns, the information provided by them is not compatible with Fourier-based techniques and cannot be applied directly. In this paper, we first introduce a 3D near-field bistatic imaging approach using two one-dimensional (1D) DMAs as a panel-to-panel model in a Mills Cross structure. Then, based on the introduced mathematical model, we derive a Fourier-based algorithm for the image reconstruction problem. The proposed algorithm consists of five main steps: pre-processing (to transfer data provided by the transmitter and receiver DMAs to a set of equivalent spatial measurements), applying FTs to the transferred signal, filtering in the Fourier domain, a simplified interpolation, and applying a 3D inverse FT to retrieve scene information. The results of numerical simulations confirm the satisfactory performance of the proposed approach.

Fourier-Based Near-Field Three-Dimensional Image Reconstruction in a Multistatic Imaging Structure Using Dynamic Metasurface Antennas

“…2; (a) As can be seen in both cases, the proposed approach has been able to successfully reconstruct the image of all point scatterers in their correct positions. The reason that the detected points become smaller with increasing distance from the radar is the propagation loss effect, which is consistent with the analyzes and findings presented in [34,53].…”

“…, ; represent the field over the aperture corresponding to the m -th mask of the l -th Tx and the m′ -th mask of Rx, respectively, and can be expressed as follows [23,33,34]: γ ω = , where Q is the quality factor of the metamaterial elements [33][34][35]. In fact, aperture fields mainly depend on the magnetic dipole moment induced in each element (for more details, refer to [34]). By assuming the creation of a set of aperture modes with some degrees of orthogonality, mathematically we have…”

“…Details of the steps for calculating integrals such as 1 I and 2 I can be found in [34] and [43], respectively. These calculations mainly involve convolution theory, second-order 2D Taylor expansion, and first-and second-order partial derivatives.…”

“…It is clear that in (1), unlike (18), we do not have access to the field corresponding to r′ (the fields corresponding to the positions i x , i y and i y ′ ). The pre-processing presented in this section is an effective way to transform the measurements provided by DMAs into a set equivalent to the spatial measurements emanating from a collection of effective dipole sources [34]. In fact, the operations after the presented pre-processing stage can be generalized and applied to the data collected from conventional antenna arrays.…”

MIMO Coded Generalized Reduced Dimension Fourier Algorithm for 3-D Microwave Imaging

“…According to the geometry of the system in Fig. 1(a), the backscatter frequency response can be written as a spatial-frequency expression in the following form [13,42]: ( ) ( )…”