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http://dx.doi.org/10.9766/KIMST.2018.21.2.147

Experimental Study of Drone Detection and Classification through FMCW ISAR and CW Micro-Doppler Analysis  

Song, Kyoungmin (Korea Aerospace University, Dept. of Electronics and Information Eng.)
Moon, Minjung (Korea Aerospace University, Dept. of Electronics and Information Eng.)
Lee, Wookyung (Korea Aerospace University, Dept. of Electronics and Information Eng.)
Publication Information
Journal of the Korea Institute of Military Science and Technology / v.21, no.2, 2018 , pp. 147-157 More about this Journal
Abstract
There are increasing demands to provide early warning against intruding drones and cope with potential threats. Commercial anti-drone systems are mostly based on simple target detection by radar reflections. In real scenario, however, it becomes essential to obtain drone radar signatures so that hostile targets are recognized in advance. We present experimental test results that micro-Doppler radar signature delivers partial information on multi-rotor platforms and exhibits limited performance in drone recognition and classification. Afterward, we attempt to generate high resolution profile of flying drone targets. To this purpose, wide bands radar signals are employed to carry out inverse synthetic aperture radar(ISAR) imaging against moving drones. Following theoretical analysis, experimental field tests are carried out to acquire real target signals. Our preliminary tests demonstrate that high resolution ISAR imaging provides effective measures to detect and classify multiple drone targets in air.
Keywords
ISAR; micro-Doppler; Drone Detection;
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