发表机构
Interuniversity Micro-Electronics Center (IMEC); Vrije Universiteit Brussel (VUB)（互大学微电子中心; 布鲁塞尔自由大学）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
针对无人机天底视角的三维雷达成像问题，本文提出基于低成本MIMO毫米波雷达的InSAR框架及PGA相位误差补偿方法，经仿真与实验验证了算法的有效性。
AI 中文摘要
雷达可在恶劣光照、天气条件下工作并穿透植被等遮挡物，提升无人机的感知鲁棒性，但存在角分辨率差的问题，可通过合成孔径雷达（SAR）算法解决。当前最先进的无人机SAR方法以俯角工作，不适用于从无人机正下方区域（即无人机天底）采集数据的传感器融合应用。本文提出一种干涉合成孔径雷达（InSAR）框架，用于使用低成本多输入多输出（MIMO）毫米波雷达从无人机天底重建三维图像；还提出一种基于相位梯度自聚焦（PGA）的有效方法，用于补偿虚拟接收天线间的相位误差。我们在仿真和实验场景中验证了所提三维成像算法的有效性。
英文摘要
Radars improve the sensing robustness of UAVs by operating under poor lighting and weather conditions and seeing through occlusions such as vegetation. However, they suffer from poor angular resolution, which can be addressed using synthetic aperture radar (SAR) algorithms. State-of-the-art UAV SAR methods operate at a depression angle and are not suitable for sensor fusion applications where the data are collected from areas directly below the UAV (i.e., the UAV nadir). In this paper, we present an interferometric SAR (InSAR) framework for reconstructing 3D images from the UAV nadir using a low-cost multi-input-multi-output (MIMO) mm-wave radar. Additionally, an effective method based on the phase gradient autofocus (PGA) is presented for compensating the phase error across the virtual receive antennas. We demonstrate the effectiveness of our 3D imaging algorithm in both simulation and experimental scenarios.
CommentsAccepted for publication in IEEE Transactions on Radar Systems
