Micro-Doppler feature extraction of unmanned aerial vehicles(UAVs)is important for their identification and classification.Noise and the motion state of the UAV are the main factors that may affect feature extraction ...Micro-Doppler feature extraction of unmanned aerial vehicles(UAVs)is important for their identification and classification.Noise and the motion state of the UAV are the main factors that may affect feature extraction and estimation precision of the micro-motion parameters.The spectrum of UAV echoes is reconstructed to strengthen the micro-motion feature and reduce the influence of the noise on the condition of low signal to noise ratio(SNR).Then considering the rotor rate variance of UAV in the complex motion state,the cepstrum method is improved to extract the rotation rate of the UAV,and the blade length can be intensively estimated.The experiment results for the simulation data and measured data show that the reconstruction of the spectrum for the UAV echoes is helpful and the relative mean square root error of the rotating speed and blade length estimated by the proposed method can be improved.However,the computation complexity is higher and the heavier computation burden is required.展开更多
准确地估计小型旋翼无人机的微动参数对无人机的识别具有重要意义,针对小型旋翼无人机弱微动特征的提取问题,本文提出了RSP-CFD(Reassigned Spectrogram-Cadence Frequency Diagram, RSP-CFD)的特征提取方法。首先采用高分辨时频分析方...准确地估计小型旋翼无人机的微动参数对无人机的识别具有重要意义,针对小型旋翼无人机弱微动特征的提取问题,本文提出了RSP-CFD(Reassigned Spectrogram-Cadence Frequency Diagram, RSP-CFD)的特征提取方法。首先采用高分辨时频分析方法RSP分析旋翼无人机的微动特性,其次在RSP的基础上利用CFD方法提取旋翼无人机的微动特征,最后通过极大值参数估计方法实现对旋翼转速、叶片长度的估计。结果表明RSP-CFD方法对旋翼无人机微动特征的提取具有较高的准确性,弥补了传统方法的不足,进而为旋翼无人机的分类提供理论基础和技术支撑。展开更多
为了实现对低空多旋翼无人机的旋翼片数及其转动周期参数进行识别,提出了基于逆合成孔径雷达(ISAR)像序列的多旋翼无人机参数估算方法,利用欧拉旋转矩阵对多旋翼无人机运动模型进行建模,并分析了多旋翼无人机ISAR像成像机理,然后利用距...为了实现对低空多旋翼无人机的旋翼片数及其转动周期参数进行识别,提出了基于逆合成孔径雷达(ISAR)像序列的多旋翼无人机参数估算方法,利用欧拉旋转矩阵对多旋翼无人机运动模型进行建模,并分析了多旋翼无人机ISAR像成像机理,然后利用距离瞬时多普勒算法获取了多旋翼无人机的ISAR像序列,通过成像仿真发现,当旋翼与雷达视向垂直时在成像平面上会出现强散射;再对ISAR像数据进行预处理,获取了强散射在时间-距离向上的分布矩阵,结合蚁群算法估算出了旋翼数目,并用自相关估算出了转动周期。仿真结果表明:提出的算法具有较好的抗噪性,在信噪比大于-10 d B的情况下,实现了对旋翼片数及其转动周期的估算,且旋翼转动周期估算误差小于8%。展开更多
基金supported by the National Natural Science Foundation of China(62141108)Natural Science Foundation of Tianjin(19JCQNJC01000)。
文摘Micro-Doppler feature extraction of unmanned aerial vehicles(UAVs)is important for their identification and classification.Noise and the motion state of the UAV are the main factors that may affect feature extraction and estimation precision of the micro-motion parameters.The spectrum of UAV echoes is reconstructed to strengthen the micro-motion feature and reduce the influence of the noise on the condition of low signal to noise ratio(SNR).Then considering the rotor rate variance of UAV in the complex motion state,the cepstrum method is improved to extract the rotation rate of the UAV,and the blade length can be intensively estimated.The experiment results for the simulation data and measured data show that the reconstruction of the spectrum for the UAV echoes is helpful and the relative mean square root error of the rotating speed and blade length estimated by the proposed method can be improved.However,the computation complexity is higher and the heavier computation burden is required.
文摘准确地估计小型旋翼无人机的微动参数对无人机的识别具有重要意义,针对小型旋翼无人机弱微动特征的提取问题,本文提出了RSP-CFD(Reassigned Spectrogram-Cadence Frequency Diagram, RSP-CFD)的特征提取方法。首先采用高分辨时频分析方法RSP分析旋翼无人机的微动特性,其次在RSP的基础上利用CFD方法提取旋翼无人机的微动特征,最后通过极大值参数估计方法实现对旋翼转速、叶片长度的估计。结果表明RSP-CFD方法对旋翼无人机微动特征的提取具有较高的准确性,弥补了传统方法的不足,进而为旋翼无人机的分类提供理论基础和技术支撑。
文摘为了实现对低空多旋翼无人机的旋翼片数及其转动周期参数进行识别,提出了基于逆合成孔径雷达(ISAR)像序列的多旋翼无人机参数估算方法,利用欧拉旋转矩阵对多旋翼无人机运动模型进行建模,并分析了多旋翼无人机ISAR像成像机理,然后利用距离瞬时多普勒算法获取了多旋翼无人机的ISAR像序列,通过成像仿真发现,当旋翼与雷达视向垂直时在成像平面上会出现强散射;再对ISAR像数据进行预处理,获取了强散射在时间-距离向上的分布矩阵,结合蚁群算法估算出了旋翼数目,并用自相关估算出了转动周期。仿真结果表明:提出的算法具有较好的抗噪性,在信噪比大于-10 d B的情况下,实现了对旋翼片数及其转动周期的估算,且旋翼转动周期估算误差小于8%。
