Precise characterization of concealed person-worn objects will speed up the passenger screening process by reducing the rate of nuisance alarms, while also enhancing the airport security imaging systems. This paper presents an automatic, real-time method for wideband millimeter-wave radar identification of the nominal surface contours of the human body – even with affixed foreign objects or when a segment of the body cross-section is not captured by the radar – without relying on the body's bilateral symmetry. The developed method is verified experimentally when applied to the actual images generated by a laboratory airport scanning prototype developed recently by the US Department of Homeland Security (DHS). Our method uses the noisy collection of radar cross-section reflectivity data to extract the main contours and estimates the nominal body surface cross-sections through fitting a small-term Fourier series of circumferential variation. This is a necessary step for accurate characterizing of concealed terrorist threat objects affixed to the body.

对隐蔽的佩戴对象进行精确表征将通过降低滋扰警报的发生率来加快乘客筛查过程，同时还可以增强机场安全成像系统。本文提出了一种自动、实时的宽带毫米波雷达识别人体标称表面轮廓的方法——即使有附着的异物或当身体横截面的一部分未被雷达捕获时——无需依靠身体的左右对称性。当应用于美国国土安全部 (DHS) 最近开发的实验室机场扫描原型生成的实际图像时，所开发的方法得到了实验验证。我们的方法使用雷达横截面反射率数据的噪声收集来提取主要轮廓，并通过拟合周向变化的小项傅里叶级数来估计标称体表横截面。这是准确表征附着在身体上的隐藏的恐怖威胁物体的必要步骤。