This paper proposes a novel approach to 3-D microwave imaging using dynamic metasurface antennas in a multistatic configuration. By introducing a panel-to-panel model and a preprocessing technique, raw measurements are converted into the space-frequency domain for efficient data acquisition and reconstruction. Adapting the range migration algorithm in this work enables fast Fourier-based image reconstruction. Simulation results showcase the effectiveness of the proposed method, highlighting its potential for real-world applications.
The simplicity and cost factor of millimeter-wave hardware restrict the implementation of near-field radar imaging systems in many applications. These drawbacks are exacerbated when using multiple antennas, each being connected to a dedicated sampling chain. To significantly alleviate these constraints, the use of analog multiplexing techniques appears inevitable. The choice of a suitable solution for a given application can be challenging. Among the available technologies, this study focuses on frequency beamsteering and space-frequency random scanning, comparing the characteristics and performances of these techniques in a radar imaging scenario in the 92-96GHz frequency band.
In this paper, we describe the recent development of new algorithms applied to short-range radar imaging. Facing the limitations of classical backpropagation algorithms, the use of techniques based on Fast Fourier Transforms has led to substantial image computation accelerations, especially for Multiple-Input Multiple-Output systems. The necessary spatial interpolation and zero-padding steps are still particularly limiting in this context, so it is proposed to replace it by a more efficient matrix technique, showing improvements in memory consumption, image computation speed and reconstruction quality.
Microwave imaging systems allowing the real-time scanning of short-range objects are difficult to implement on a large scale due to their complexity and cost. In this paper we introduce a new ultra-wideband multiple-input multiple-output radar using microwave photonic components in reception. These components permit ultra-fast time division multiplexing of all receiving signals and hence their measurement with a single acquisition channel. This architecture makes possible to decrease the time of acquisition compare to architecture with a sequential reception.
In this paper, we review modern advances in microwave and millimeter-wave computational frequency-diverse imaging, and submillimeter-wave radar systems. We first present a frequency-diverse computational imaging system developed by Duke University for security-screening applications at K-band (17.5-26.5 GHz) frequencies. Following, we show a millimeter-wave spotlight imaging concept and its conceptual integration with the K-band system as interesting example of sensor fusion. We also demonstrate the application of computational frequency-diverse imaging for polarimetric imaging and phase retrieval problems. We show that using the concept of computational frequency-diverse imaging and quasi-random measurement bases, high-fidelity images of objects can be retrieved without the need for any mechanical scanning apparatus and phase shifting circuits. Increasing the frequency-band of operation, we also demonstrate a 340 GHz radar developed by the Jet Propulsion Laboratory and its application for standoff detection. We demonstrate a new technique to characterize the point-spread-function (PSF) of radars operating at submillimeter-wave frequencies.
Dynamic metasurface antennas are planar structures that exhibit remarkable capabilities in controlling electromagnetic wave-fronts, advantages which are particularly attractive for microwave imaging. These antennas exhibit strong frequency dispersion and produce diverse radiation patterns. Such behavior presents unique challenges for integration with conventional imaging algorithms. We analyze an adapted version of the range migration algorithm (RMA) for use with dynamic metasurfaces in image reconstruction. Focusing on the the proposed pre-processing step, that ultimately allows a fast processing of the backscattered signal in the spatial frequency domain from which the fast Fourier transform can efficiently reconstruct the scene. Numerical studies illustrate imaging performance using both conventional methods and the adapted RMA, demonstrating that the RMA can reconstruct images with comparable quality in a fraction of the time. In this paper, we demonstrate the capabilities of the algorithm as a fast reconstruction tool, and we analyze the limitations of the presented technique in terms of image quality.
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