A Sparse Aperture MIMO-Based IR-UWB Radar Imaging System for Concealed Weapon Detection

Abstract

In this thesis, we propose a high-resolution imaging algorithm for concealed weapon detection based on multiple-input-multiple-output (MIMO) impulse radio ultra-wideband (IR-UWB) radar in luggage. From security point of view at the airports and other similar vicinities, it is very important to quickly and accurately identify whether the human body or the luggage has concealed weapons that may endanger public safety. Some existing detection and identification solutions have been applied on a large scale, but they have some limitations such as users-privacy concerns and radiation hazards, that cannot be ignored. Therefore, we are committed to solving problems that can minimize radiation and privacy related issues, while looking for solutions that can quickly and accurately identify concealed weapons. Our proposed the radar imaging system consists of four transmitter and five receiver antennas array which covers the entire area of the storage box to be tested. Based on the delay-and-sum (DAS) algorithm, we added the idea of clustering and loopback filtering method to form a reconstructed image of concealed weapons. In order to reduce the influence of clutter after reconstruction, we adopt the mean clustering de-noising algorithm in the threshold processing stage. As a showcase experimental scenario, we tested our algorithm against four groups of common weapons which are pistol, grenade, scissors and knife. The experimental results of this thesis show the usefulness our proposed algorithm to detect concealed weapons inside luggage. Considering these results, this method would be of great importance in the field of object detection and recognition.