In this paper, we summarize our efforts of using three different radars (impulse radar, swept frequency radar,
and continuous-wave radar) for through-the-wall sensing. The purpose is to understand the pros and cons of each
of the three radars. Through extensive experiments, it was found that the radars are complementary and multiple
radars are needed for different scenarios of through-the-wall target detection and tracking.
In this paper, vehicle-mounted ultra-wide band (UWB) radar is studied for detection of roadside improvised explosive devices (IEDs). Simulations and measurements have been performed to study the radar system set-up, target scattering, and data processing. The challenges of UWB radar for target visibility within the ground clutter, locating with limited angular diversity, and discrimination of buried bomb shells have been encountered and explored. Possible solutions to overcome these challenges are investigated.
The goal of our research is to assess the capability of ultra-wide-band (UWB) radar for detection of roadside improvised
explosive devices (IEDs). Radar scattering signatures of artillery shells over a broadband frequency range, with
different Tx/Rx polarizations, and at various aspect angles have been explored based on simulation and indoor
measurement. Characteristics of IEDs versus clutter, wave penetration at different frequencies are also investigated.
Finally, visibility of IED targets is tested on a moving cart in outdoor settings, with IED targets on ground surface,
recessed, and buried underground at different distances away from the radar.
KEYWORDS: 3D acquisition, 3D image processing, Synthetic aperture radar, 3D modeling, Scattering, Detection and tracking algorithms, Image acquisition, 3D image reconstruction, Radar, Electromagnetic scattering
The performance of ATR systems can potentially be improved by using three-dimensional (3-D) SAR images instead of the traditional two-dimensional SAR images or one-dimensional range profiles. 3-D SAR image formation of targets from radar backscattered data collected on wide angle, sparse apertures has been identified by AFRL as fundamental to building an object detection and recognition capability. A set of data has been released as a challenge problem. This paper describes a technique based on the concept of 3-D target grids aimed at the formation of 3-D SAR images of targets from sparse aperture data. The 3-D target grids capture the 3-D spatial and angular scattering properties of the target and serve as matched filters for SAR formation. The results of 3-D SAR formation using the backhoe public release data are presented.
Based on the point scatterer model, the radar signal can be effectively analyzed using the joint time-frequency (JTF) method. The basis functions of a few primary point scatterers are believed to carry target motion information essential to the ISAR imaging process. One major problem with the JTF method is the computation load associated with the exhaustive search process for motion parameters. In this paper, genetic algorithms (GA) are used to for the parameterization process in the JTF method. Real and binary coded GA are investigated and their performance compared with the exhaustive search. It is shown that a significant amount of time can be saved while achieving almost the same image quality by using real-coded GA.
In this paper, ISAR images generated from measured data are compared to those from computer simulation in order to evaluate the effectiveness of ISAR-based target identification. Three sets of images are generated including: (1) motion compensated images from measured data using a joint time-frequency technique, (2) reference images from measured data and GPS-derived aircraft attitude data, and (3) synthetic images predicted by Xpatch. Visual examination and correlation analysis are undertaken to compare the three sets of images. In addition, two problem areas including JEM line corruption of the measured images and 3D rotation of the target are identified.
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