  In radar accurate localization of unmanned aerial vehicle (UAV) swarms, the
high density, similar motion parameters, small radar cross-section (RCS),
strong noise and far range put forward high requirements on radar resolution
and transmitting power. In this paper, by using advantages of the long-time
integration (LTI) technique and gridless sparse method, we construct a
super-resolution framework for radar accurate localization of UAV swarms
without changing radar hardware and system parameters. Thereafter, based on
this framework, a range super-resolution method is proposed to realize the
radar accurate localization of UAV swarms. Mathematical analyses and numerical
simulations are performed and demonstrate that, compared to the keystone
transform (KT)-based LTI method, MUSIC-based method and reweighted atomic-norm
minimization (RAM)-based method, the range super-resolution method is more
robust and practical for radar accurate localization of UAV swarms under the
noisy environment. Additionally, the real experiment with X-band radar is also
conducted to verify the effectiveness of the range super-resolution method.
