基于单频涡旋电磁波雷达的人体目标步态精细识别

现有基于传统平面电磁波雷达的人体目标识别技术能够实现对步态差异较大的人体目标的分类识别，但在步态精细识别方面面临较大困难。将涡旋电磁波雷达应用于人体步态识别中，尝试通过发射携带有轨道角动量的单频涡旋电磁波来增加雷达回波中的目标信息量，以提高人体步态精细识别能力。首先建立了人体目标的涡旋电磁波雷达回波模型，并仿真生成了3种步态下的回波数据集；然后通过将回波变换到基频，获得目标线多普勒和角多普勒混合信息并用时频图表征，最终将时频图输入到卷积神经网络模型中获得分类结果。仿真实验表明：相比于传统平面电磁波雷达，使用涡旋电磁波可以提升人体步态精细识别能力。

Fine Gait Recognition of Human Target with Single Frequency Vortex Electromagnetic Wave Radar

The existing human target recognition technology based on the traditional planar electromagnetic wave radar is enabled to realize good results in the face of the classification and recognization of human targets with large gait difference, only a great difficulty remains in the fine recognition of human gait. In this paper, the single frequency vortex electromagnetic wave radar (VEMWR) is applied to human gait recognition, and the target information in radar echo is increased by transmitting the vortex electromagnetic wave with orbital angular momentum (OAM), thus improving the ability of human gait fine recognition. A single frequency VEMWR echo model of human target is established, and the echo data sets of three kinds of gait are generated by the simulation. Through transforming the echo into the fundamental frequency, the linear Doppler and angular Doppler mixed information are obtained, and then their time frequency analysis images being input into a convolution neural network model, the classification results are obtained. The simulation results show that compared with the traditional planar electromagnetic wave radar, the use of vortex electromagnetic wave is effective in improving the fine recognition ability of human gait.