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首页> 外文期刊>IEEE Geoscience and Remote Sensing Letters >Denoising FMCW Ladar Signals via EEMD With Singular Spectrum Constraint
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Denoising FMCW Ladar Signals via EEMD With Singular Spectrum Constraint

机译：通过奇异谱约束通过EEMD去噪

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摘要

Frequency-modulation continuous-wave (FMCW) Laser radar (Ladar) signals may be polluted by noise, which reduces the recognition precision of the targets. This letter proposes an ensemble empirical modal decomposition (EEMD) denoising method with singular spectrum constraint for FMCW Ladar signals. In our approach, we apply EEMD to adaptively decompose the noisy FMCW Ladar signals into several intrinsic mode functions (IMFs) and decompose these IMFs into several singular value components by using the singular spectrum analysis. The singular values are then used to calculate the energy probability of each IMF, which serves as an indicator to detect the IMFs containing useful signals. The energy probability represents the coherence of the IMFs such that we could sort these IMFs into noisy and useful components according to their coherence differences. To suppress the residual noise that is interfered with the selected IMFs, we use a low-rank approximation to reconstruct the useful signals. Finally, the reconstructed IMFs are stacked together to obtain the denoised signals. Tests on synthetic and real data demonstrate that the proposed method, compared to the EEMD denoising method, could suppress more noise but filter out less useful signals in the FMCW Ladar signal denoising.
机译：频率调制连续波（FMCW）激光雷达（LADAR）信号可能被噪声污染，这降低了目标的识别精度。这封信提出了一种具有FMCW LAD信号的奇异频谱约束的集合经验模态分解（EEMD）去噪方法。在我们的方法中，我们应用EEMD将嘈杂的FMCW LADL信号自适应地分解为几个内在模式功能（IMF），并通过使用奇异频谱分析将这些IMF分解为几个奇异值分量。然后使用奇异值来计算每个IMF的能量概率，其用作检测包含有用信号的IMF的指示器。能量概率代表IMF的相干性，使得我们可以根据其相干差异将这些IMF与噪声和有用的组件分开。为了抑制干扰所选择的IMF的剩余噪声，我们使用低秩近似来重建有用的信号。最后，重建的IMF被堆叠在一起以获得去噪信号。对合成和实数据的测试表明，与EEMD去噪方法相比，该方法可以抑制更多噪声，而是在FMCW Ladar信号去噪中过滤出更少的有用信号。

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