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3D imaging by fast deconvolution algorithm in short-range UWB radar for concealed weapon detection

机译:短距离UWB雷达中快速反卷积算法的3D成像用于隐藏武器检测

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摘要

A fast imaging algorithm for real-time use in short-range (ultra-wideband) radar with synthetic or real-array aperture is proposed. The reflected field is presented here as a convolution of the target reflectivity and point spread function (PSF) of the imaging system. To obtain a focused 3D image, the proposed algorithm deconvolves the PSF out from the acquired data volume with high speed due to fast Fourier transform and implementation in frequency-wavenumber domain. Then the result is tested against two numerical criteria for efficiency, namely error and instability, whose optimal values can be obtained iteratively. Since the PSF differs with distance, the algorithm suits mainly applications with relatively small objects such as concealed weapon detection. Using several PSFs allows us to image a certain range of interest by their successive deconvolution from the same data. Performance of the algorithm has been evaluated experimentally and compared with that of Kirchhoff migration. Measurements were carried out by a 5–25 GHz synthetic aperture radar in the lab, and scenarios included a gun and a ceramic knife in free space, on a large metal plate, and a gun concealed on a dummy under a thick raincoat. The results demonstrate sufficient image quality obtained in a fraction of time.
机译:提出了一种实时成像的实时成像算法,该算法可实时用于具有合成或实数阵列孔径的短距离(超宽带)雷达。反射场在这里表示为成像系统的目标反射率和点扩散函数(PSF)的卷积。为了获得聚焦的3D图像,由于快速傅里叶变换和在频率-波数域中的实现,所提出的算法将PSF高速地从获取的数据量中解卷积。然后针对效率的两个数值标准(即误差和不稳定性)测试结果,可以迭代获得其最佳值。由于PSF随距离的不同而不同,因此该算法主要适用于对象相对较小的应用,例如隐藏武器检测。使用多个PSF可使我们通过从相同数据进行连续反卷积来对感兴趣的特定范围成像。该算法的性能已通过实验进行了评估,并与Kirchhoff迁移的性能进行了比较。测量是在实验室中由5–25 GHz合成孔径雷达进行的,场景包括在自由空间中的枪和陶瓷刀在一块大金属板上,以及一把枪藏在厚雨衣下的假人上。结果表明,可以在短时间内获得足够的图像质量。

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