Experimental Millimeter Wave ISAR Imaging of Unmanned Aerial Systems

Detection and classification of unmanned aerial systems (UASs) among a plethora of other low, slow, small moving objects remains an ongoing challenge. In this paper, we apply inverse synthetic aperture radar (ISAR) techniques to image small UASs using a low-power millimeter wave radar to demonstrate its potential for target classification. We present laboratory experiment results demonstrating radar images formed both using turntable and in-flight radar measurements. Unlike radar classification methods which exploit weak and ambiguous micro-Doppler signatures from a UAS [1], ISAR images the body of the object using its larger radar backscatter cross-section (RCS). In this paper, we study image quality as a function of mmW bandwidth and employ slow-time extrapolation techniques to improve cross-range resolution with limited angular observation extent data.