Abstract

In order to improve the speed of passenger screening while preserving the effective capability to detect more sophisticated threats, airport security imaging systems must be able to accurately characterize concealed body-worn objects. In addition to improving the passenger experience, this system capability will enhance airport security for the traveling public. This article presents a real-time, fully automatic algorithm for the wideband millimeter-wave (mm-wave) radar reconstruction of the nominal human body contours, even in the presence of an affixed weak dielectric object or when a portion of the body cross section is not captured by the imaging scanner. The algorithm extracts the main contours from a noisy collection of 3-D reconstructed reflectivity and approximates the nominal human body cross section via fitting a low-order angular Fourier series. This important step is essential for precise characterization of concealed body-worn explosives. A ranking algorithm is developed as a metric for the nominal body reconstruction accuracy. We verify the developed algorithm by applying it to the actual images of the high definition–advanced imaging technology (HD-AIT) system, a laboratory prototype mm-wave scanning system developed recently by the U.S. Department of Homeland Security (DHS). The reconstructed body contours may be used to estimate the electric permittivity of the concealed person-worn objects.

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