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
雷达波束覆盖区域内风电场后向散射引起的杂波与气象目标回波具有类似的特性,进而影响气象目标参数估计的稳健性,导致气象雷达产生误检测与误识别。利用气象雷达二次产品(Level-Ⅱ)实测数据,基于最大后验概率(maximum a posteriori,MAP...雷达波束覆盖区域内风电场后向散射引起的杂波与气象目标回波具有类似的特性,进而影响气象目标参数估计的稳健性,导致气象雷达产生误检测与误识别。利用气象雷达二次产品(Level-Ⅱ)实测数据,基于最大后验概率(maximum a posteriori,MAP)算法实现风电场杂波抑制。在传统MAP算法基础上,考虑气象雷达和风电场位置、地形等因素对雷达波束的影响,并将其作为先验信息来选取有效的气象雷达高仰角扫描数据,以此来改善风电场杂波的抑制效果。针对高扫及低扫区域内径向速度变化较为剧烈所导致的MAP杂波抑制算法性能下降的问题,基于气象目标参数随距离均匀分布特性,用风电场周围未污染气象目标的径向速度作为先验信息,对传统MAP算法抑制后的径向速度进行修正。为定量评价风电场抑制算法的性能,给出了定量评价风电场杂波抑制效果的性能指标,并利用气象雷达不同体扫模式VCP(volume cover pattern)下的Level-Ⅱ数据对本文提出算法的有效性进行了验证。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
针对风轮机叶片雷达散射截面积的变化特性,分析了风轮机叶片雷达散射截面积(Radar Cross Section,RCS)对其整体雷达散射特性占比情况,实现对叶片解析模型适用范围的选取。考虑了风轮机叶片旋转平面与雷达视线(Line of Sight,LOS)夹角、...针对风轮机叶片雷达散射截面积的变化特性,分析了风轮机叶片雷达散射截面积(Radar Cross Section,RCS)对其整体雷达散射特性占比情况,实现对叶片解析模型适用范围的选取。考虑了风轮机叶片旋转平面与雷达视线(Line of Sight,LOS)夹角、叶片材料、叶片几何形状等因素对风轮机散射特性的影响,运用UG软件对风轮机叶片进行三维建模,利用真实叶片与相应简化圆柱叶片电磁散射特性的差异构建高保真的风轮机真实叶片电磁散射特性的解析模型,实现风轮机叶片RCS的快速计算。最后将解析模型计算结果与实测数据进行对比,验证了论文给出的真实叶片电磁散射特性解析模型的有效性。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.
文摘雷达波束覆盖区域内风电场后向散射引起的杂波与气象目标回波具有类似的特性,进而影响气象目标参数估计的稳健性,导致气象雷达产生误检测与误识别。利用气象雷达二次产品(Level-Ⅱ)实测数据,基于最大后验概率(maximum a posteriori,MAP)算法实现风电场杂波抑制。在传统MAP算法基础上,考虑气象雷达和风电场位置、地形等因素对雷达波束的影响,并将其作为先验信息来选取有效的气象雷达高仰角扫描数据,以此来改善风电场杂波的抑制效果。针对高扫及低扫区域内径向速度变化较为剧烈所导致的MAP杂波抑制算法性能下降的问题,基于气象目标参数随距离均匀分布特性,用风电场周围未污染气象目标的径向速度作为先验信息,对传统MAP算法抑制后的径向速度进行修正。为定量评价风电场抑制算法的性能,给出了定量评价风电场杂波抑制效果的性能指标,并利用气象雷达不同体扫模式VCP(volume cover pattern)下的Level-Ⅱ数据对本文提出算法的有效性进行了验证。
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。
文摘针对风轮机叶片雷达散射截面积的变化特性,分析了风轮机叶片雷达散射截面积(Radar Cross Section,RCS)对其整体雷达散射特性占比情况,实现对叶片解析模型适用范围的选取。考虑了风轮机叶片旋转平面与雷达视线(Line of Sight,LOS)夹角、叶片材料、叶片几何形状等因素对风轮机散射特性的影响,运用UG软件对风轮机叶片进行三维建模,利用真实叶片与相应简化圆柱叶片电磁散射特性的差异构建高保真的风轮机真实叶片电磁散射特性的解析模型,实现风轮机叶片RCS的快速计算。最后将解析模型计算结果与实测数据进行对比,验证了论文给出的真实叶片电磁散射特性解析模型的有效性。
