By Shuo Liu, George Shaker, Safieddin Safavi-Naeini, and Michael Chong
The integration of digital signal processing (DSP) algorithms and machine learning in radar systems has enabled exploration of radar’s uses in new applications.
Detecting explosives has become a necessary inspection process at airports and border controls as an active safety measure for counterterrorism. Current methods of explosive detection, while generally effective, have their limitations. Colorimetric and spectrometry techniques, for example, are expensive and require time to confirm the presence of explosives.
Here, we demonstrate utilizing mm-Wave radars coupled with carbon nanotube-based gas-sensing films for trace detection of explosives. The proposed method is low-cost, compact, highly accurate, and offers continuous real-time detection.