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摘要: 高效率目标探测需要借助探测信号的低相关性空间调制，调制数量大且具有时间独立性。携带轨道角动量(OAM)的涡旋波束具有无穷多种模态且不同模态之间相互正交，借助强色散材料可以实现频率域的多模态OAM波束产生。该文首先对OAM的传播特性进行推导，给出了符合探测需求的多模态OAM波束源特征；在此基础上，研究了不同模态的OAM波束在3种不同应用场景下目标反射回波信号特性，采用卷积神经网络对不同反射场景下的数据特征进行提取，实现了对未知场景的判断及场景内的目标识别，并进行了抗噪性能分析。实验结果表明：理想状态下，网络对目标场景判断的准确率可达
$97.5\% $ ；各反射场景中的两个相邻目标的间隔大于某一阈值时，网络对目标位置的识别准确率均高于$80\% $ 。但目标识别效果有环境依赖性，当${\rm{SNR}} < 20\;{\rm{dB}}$ 时，3种场景内的目标识别准确率均大幅降低。Abstract: Target detection based on space modulation requires a large number of test modes with space-time independence. The Orbital Angular Momentum (OAM) beams are orthogonal to each other and have infinite modes. Due to the strong dispersive materials, multi-mode OAM beams with the same scattering angle can be generated in the frequency domain. In this manuscript, the propagation characteristics of multi-mode OAM beams are analyzed, which can be utilized to improve detection efficiency. The echoes from the target illuminated by the multi-mode OAM beams are then investigated in three different application scenarios. A convolution neural network is employed to extract the relationship between the echo data and the target image based on prior knowledge. The target and the imaging scenarios can be distinguished with a high probability. Finally, the proposed method’s anti-noise performance is analyzed. The experimental results show that in the ideal state, the accuracy of target scene judgment can reach 97.5%. The accuracy of the target location recognition is higher than 80% when the interval between two adjacent targets in a scene is larger than a threshold. The accuracy of the target location recognition in three scenes is greatly reduced when SNR is less than 20 dB, depending on the scene. -
图 1 均匀圆形阵列产生OAM波束的示意图
Figure 1. Structure diagram of OAM beam generated by uniform circular array
图 2 2模态和3模态OAM波束的幅相分布
Figure 2. Amplitude and phase distribution of OAM beams with 2-mode and 3-mode
图 7 传统波束与OAM波束经不同反射面的回波方向图
Figure 7. Echo pattern of traditional beam and OAM beam through different reflector
图 9 反射场景1中观测点处反射信息
Figure 9. Reflection information at observation point in reflection scene 1
图 10 反射场景2中观测点处反射信息
Figure 10. Reflection information at observation point in reflection scene 2
图 11 反射场景3中观测点处反射信息
Figure 11. Reflection information at observation point in reflection scene 3
图 14 信噪比为10 dB时，2模态OAM波束的幅相特性
Figure 14. Amplitude and phase characteristics of 2-mode OAM beam when SNR is 10 dB
图 17 样本数据获取及标签设置示意图
Figure 17. Schematic diagram of sample data acquisition and label setting
图 18 目标间隔对场景内目标位置识别准确率的影响
Figure 18. Influence of target interval on accuracy of target location recognition in scene
图 19 信噪比对场景内目标位置识别准确率的影响
Figure 19. Influence of SNR on the accuracy of target position recognition in scene
表 1 阵列的半径
Table 1. Radius of array
模态$ l $ 阵列半径R (m) 1 0.0450 2 0.0747 3 0.1026 4 0.1302 5 0.1569 6 0.1836 7 0.2097 8 0.2361 9 0.2619 
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表 2 OAM波束经反射面1的反射角
Table 2. Reflection angle of OAM beam passing through reflector 1
$ l $ $ \theta $ (°) $ \mathrm{\varphi } $ (°) 1 11.2523 89.9940 2 11.2523 89.9819 3 11.2523 89.9819 4 11.2523 89.9699 5 11.2523 89.9579 6 11.2523 89.9579 7 11.2523 89.9458 8 11.2523 89.9458
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表 3 发射阵列及卷积神经网络的相关参数
Table 3. Parameters of transmit array and convolutional neural network
实验参数 参数值 频率 (GHz) 10 阵元数目 (个) 40 反射面尺寸 $10\lambda $ 迭代次数 100 反向传播学习率 1
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