论文标题
雷达基于范围超分辨率方法的无人机群的精确定位
Radar Accurate Localization of UAV Swarms Based on Range Super-Resolution Method
论文作者
论文摘要
在无人驾驶飞机（UAV）群的雷达精确定位中，高密度，相似的运动参数，小雷达横截面（RCS），强噪声和远距离范围提出了对雷达分辨率和传输功率的高需求。在本文中，通过使用长期集成（LTI）技术和无网稀疏方法的优势，我们构建了一个超分辨率框架，用于雷达精确定位无人机群，而无需更改雷达硬件和系统参数。此后，基于此框架，提出了一种范围的超分辨率方法来实现无人机群的准确定位。进行了数学分析和数值模拟，并证明，与基于Keystone Transform（KT）基于音乐的LTI方法，基于音乐的方法和重新获得的原子 - 符号最小化（RAM）方法相比，范围的超分辨率方法更可靠，并且实用性地用于Noisisy环境下的UAV胎盘的雷达精确定位。此外，还进行了X波段雷达的实际实验，以验证范围超分辨率方法的有效性。
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.
