This paper presents a novel system to obtain images from the underground based on ground penetrating radar (GPR). The proposed system is composed by a radar module mounted on board an unmanned aerial vehicle (UAV), which allows the safe inspection of difficult-to-access areas without being in direct contact with the soil. Therefore, it can be used to detect dangerous buried objects, such as landmines. The radar measurements are coherently combined using a synthetic aperture radar (SAR) algorithm, which requires cm-level accuracy positioning system. In addition, a clutter removal technique is applied to mitigate the reflection at the air-soil interface (which is caused by impedance mismatching). Besides the aforementioned advantages, the system can detect both metallic and dielectric targets (due to the use of a radar instead of a metal detector) and it allows to obtain high-resolution underground images (due to the SAR processing). The algorithms and the UAV payload are validated with measurements in both controlled and real scenarios, showing the feasibility of the proposed system.

This paper presents a compact, low-cost unmanned aerial system for antenna measurement. The proposed system overcomes existing limitations in terms of unmanned aerial vehicle positioning and data geo-referring accuracy using a real-time kinematic positioning system to achieve centimeter-level accuracy. Amplitude-only measurements acquired using a low-cost power sensor are processed by means of the phaseless sources reconstruction method. This is an iterative phase retrieval technique that allows recovering an equivalent currents distribution, which characterizes the antenna under test (AUT). From these equivalent currents, near-field to far-field transformation is applied to calculate the AUT radiation pattern. This contribution also analyzes probe antenna characterization and the impact of positioning and geo-referring accuracy on the radiation pattern. Two application examples of antenna measurement at S- and C-bands using the implemented system are presented.

We have developed a 3-D high-resolution radar at 300 GHz with a cell resolution of 1×1.6×1.6 cm ³ at a standoff distance of 8 m for security applications. The selection of an operating frequency of 300 GHz, a bandwidth of 27 GHz, and a field of view of 50×90 cm ² improves the through-clothes imaging of person-borne concealed objects. The radar's antenna design allows single-pixel imaging at a frame rate of two frames per second. A reduction in cost and power consumption and improvements in image quality are additional requirements taken into account in the design of this radar system.

Active millimeter-wave radar can be used for imaging concealed objects and detecting contraband at security checkpoints. Current state-of-the-art systems are based on monostatic or quasimonostatic configurations that can misrepresent areas of the target when the specular reflection is oriented away from the incident direction. This article presents a fully multistatic millimeter-wave imaging architecture for human-body screening. Transmitters placed off the receiving aperture panel allow for maximizing the surface of the human body that can be reconstructed. A reduced number of transmitters allows for fast imaging, which minimizes the target motion effects. Multiple three-dimensional (3-D) simulation-based examples are presented to validate the proposed system.

Fourier-based methods for monostatic and bistatic setups have been widely used for high-accuracy radar imaging. However, the multistatic configuration has several characteristics that make Fourier processing more challenging: 1) a nonuniform grid in k-space, which requires multidimensional interpolation methods, and 2) image distortion when the incident spherical wave is approximated by a plane wave. This contribution presents a Fourier-based imaging method for multistatic systems, solving the aforementioned limitations: the first, by using k-space partitioning and applying interpolation in each domain; the second, by approximating the spherical wave with multiple plane waves. Both solutions are fully parallelizable, thus allowing calculation time savings. Validation and benchmarking with a synthetic aperture radar backpropagation algorithm have been performed through 2-D and 3-D simulation-based examples. Imaging results from radar measurements have been assessed.

The optimization and use of a sparse array configuration for an active three dimensional (3D) millimeter wave imaging system for personnel security screening is presented in this work. The combination of the optimization procedure with the use of Compressed Sensing techniques allows drastic reduction in the number of sensors, thereby simplifying the system design and fabrication and reducing its cost. Representative simulation results showing good performance of the proposed system are provided and supported by sample measurements.