基于EMD提取散射特征的目标识别

I. Jouny
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引用次数: 4

摘要

利用复经验模态分解(EMD)提取的散射特征进行雷达目标识别。EMD与Hilbert-Huang变换相关联,可用于从雷达反向散射中提取固有振荡,即隐式模态函数(IMFs)。这些imf可以与目标散射中心的位置相关联,从而与询问雷达所看到的目标几何形状或下程轮廓相关联。然后将EMD提取的特征提供给基于距离的目标识别系统。利用合成雷达数据和实际雷达数据对所提出的目标分类方案进行了测试。
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Target recognition using scattering features extracted with EMD
Scattering features extracted via complex Empirical Mode Decomposition (EMD) are used for radar target recognition. EMD, which is associated with the Hilbert-Huang transform, can be used to extract inherent oscillations known as Implicit Mode Functions (IMFs) from a radar backscatter. These IMFs can be associated with the locations of the target scattering centers, and consequently with the target geometry or down range profile as seen by the interrogating radar. Features extracted using EMD are then presented to a distance-based target recognition system. The proposed target classification scheme is tested using synthetic and real radar data recorded in a compact range.
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