Availability and capabilities of ISAR imaging for detection and classification of UAV swarms: An illustrative study based on PREDICS Simulation and analysis
Abstract
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.
Keywords
References
- M. M., Arafat, M. Y., Moh, S., & Shen, J. (2022). Topology control algorithms in multi-unmanned aerial vehicle networks: An extensive survey. Journal of Network and Computer Applications, 207, 103495. https://doi.org/10.1016/j.jnca.2022.103495
- Baumgartner, S.V. (2018). Circular and polarimetric ISAR imaging of ships using airborne SAR sensors. Proceeding Book of EUSAR 2018; 12th European Conference on Synthetic Aperture Radar, Aachen, Germany, pp. 1–6.
- Boerner, W.M., Yan, W.L., Xi, A.Q., and Yamaguchi, Y. (1992). Basic concepts of radar polarimetry. Direct and inverse methods in radar polarimetry. Springer. https://doi.org/10.1007/978-94-010-9243-2_8
- Cameron, W.L., Youssef, N.N., and Leung, L.K. (1996). Simulated polarimetric signatures of primitive geometrical shapes. IEEE Transactions on Geoscience and Remote Sensing, 34, 793–803. https://doi.org/10.1109/36.499784
- Çoruk, R. B., Kara, A. & Aydın, E. (2024). Drone swarm classification from ISAR Imaging. Journal of Scientific Technology and Engineering Research, 5. 127 -134. https://doi.org/10.53525/jster.1529575
- Dallmann, T. (2017). Polarimetric radar cross-section imaging [PhD thesis, Aachen University]. https://doi.org/10.18154/RWTH-2017-10216.
- Demirci, S., Kırık, Ö. & Ozdemir, C. (2020). Interpretation and analysis of target scattering from fully-polarized ISAR images using pauli decomposition scheme for target recognition. IEEE Access, 8, 155926–155938. https://doi.org/10.1109/ACCESS.2020.3018868
- Duchon, C. (1979). Lanczos filtering in one and two dimensions. Journal of Applied Meteorology, 18. 1016-1022.
Details
Primary Language
English
Subjects
Image Processing , Remote Sensing
Journal Section
Research Article
Publication Date
March 25, 2026
Submission Date
July 5, 2025
Acceptance Date
October 14, 2025
Published in Issue
Year 2026 Volume: 8