Availability and capabilities of ISAR imaging for detection and classification of UAV swarms: An illustrative study based on PREDICS Simulation and analysis

This paper presents a descriptive study on the capabilities of Inverse Synthetic Aperture Radar (ISAR) imaging to detect drone/ Unmanned Aerial Vehicle (UAV) swarms and classify the type and/or class of drone/UAV. The swarm structure consisted of 5 fixed-wing UAVs flying in coordination with each other. The X-band physical electromagnetic simulation of the scenario was carried out with PREDICS (Radar cross section simulator) solver. Full-polarization ISAR images were gathered via PREDICS to further investigate the physical features of the scene. It has been demonstrated that the use of ISAR polarimetry in identifying the key features of the platforms yielded various practices such that linear co-pol ISAR polarimetry could provide more generalized classifying features, whereas linear cross-pol ISAR polarimetry gave different sub-structures as seen from the ISAR images. As demonstrated with the circular ISAR images, the situation becomes reversed as the circular cross-pol ISAR images represent more key dominant scattering regions from the drone platforms. The Pauli ISAR image of the UAV swarm scenario provided abundant physical features of the UAV platform for fast and correct prediction of the model of the UAV that can be easily integrated into automatic target recognition schemes.