基于时频检测与极化匹配的雷达无人机检测方法

针对雷达检测无人机这一难题，该文提出了一种时频检测与极化匹配相结合的双极化雷达无人机检测方法。首先，雷达降低检测门限，各极化通道分别采用常规的时频2维单元平均恒虚警率检测方法，检测出无人机与杂波虚警；接着，各极化通道分别针对多帧检测结果进行积累，进行2次检测，剔除部分杂波虚警；最后，对两个极化通道双门限检测结果进行匹配，进一步剔除杂波虚警。对两型无人机的外场试验数据处理结果表明：该方法能够有效检测出无人机，消除杂波虚警。

Radar Detection of Unmanned Aerial Vehicles Based on Time-frequency Detection and Polarization Matching

Radar detection of Unmanned Aerial Vehicle (UAV) is a big problem. To address this problem, a detection method with dual polarization radar is proposed. First, radar reduces the detection threshold to make the UAV be detected by using the traditional two dimensional cell averaging constant false alarm probability detector in two polarization channels respectively. However, some false targets caused by clutter are also detected by radar at the same time. To eliminate these false targets, the detection results are integrated and the second detection is carried out for the integrated results in two polarization channels respectively. Then, the second detection results in two polarization channels are matched to further eliminate the false targets. Outdoor experiment is carried out. The processing results for the real data demonstrate that the second types of UAV can be effectively detected and the false targets caused by clutter can be eliminated at the same time with the proposed method.