Suppression of scattering clutter in underwater LiDAR based on CEEMDAN-wavelet threshold denoising algorithm

None Fan Chao-Yang, None Li Chao-Feng, None Yang Su-Hui, None Liu Xin-Yu, None Liao Ying-Qi
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Abstract

The echo of underwater lidar often contains a significant quantity of scattering clutters. In order to effectively suppress this scattering clutter and improve the ranging accuracy of underwater lidar, a novel denoising method based on complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) and wavelet threshold denoising is proposed.The CEEMDAN-wavelet threshold denoising algorithm uses the correlation coefficient to select intrinsic mode function (IMF) components obtained from the CEEMDAN decomposition. The IMFs, which are more closely related to the original signal, are selected. Then, the wavelet thresholding denoising algorithm is applied to each of the selected IMFs to perform additional denoising. For each IMF component, specific threshold values are calculated based on their frequency and amplitude characteristics. Subsequently, the wavelet coefficients of the IMF components are processed by using these threshold values. Finally, the denoised IMF components are combined and reconstructed to obtain the final denoised signal. Applying the wavelet threshold denoising algorithm to IMF components can effectively remove noise components that cannot be removed by traditional CEEMDAN partial reconstruction methods. By using the threshold value calculated based on the characteristics of each IMF component, the wavelet thresholding denoising process is improved in comparison with directly using a single threshold value. This approach enhances the algorithm’s adaptability and enables more effective removal of noise from the signal.We apply the proposed method to underwater ranging experiments. A 532 nm intensity-modulated continuous wave laser is used as a light source. Ranging is performed for a target in water with varying attenuation coefficients. A white polyvinyl chloride (PVC) reflector is used as a target. When the correlation extreme value is directly used to determine the delay at a distance of 3.75 attenuation length, it results in a ranging error of 19.2 cm. However, after applying the proposed method, the ranging error is reduced to 6.2 cm, thus effectively improving the ranging accuracy. These results demonstrate that the method has a significant denoising effect in underwater lidar system.
基于ceemdan -小波阈值去噪算法的水下激光雷达散射杂波抑制
水下激光雷达的回波中往往含有大量的散射杂波。为了有效抑制这种散射杂波,提高水下激光雷达的测距精度,提出了一种基于自适应噪声的全系综经验模态分解(CEEMDAN)和小波阈值去噪的去噪方法。</sec><sec> CEEMDAN-小波阈值去噪算法,该算法利用相关系数选择由CEEMDAN分解得到的本征模态函数(IMF)分量。选择与原始信号关系更密切的imf。然后,将小波阈值去噪算法应用于每个选定的imf进行附加去噪。对于每个IMF分量,根据其频率和幅度特性计算特定的阈值。然后,利用这些阈值对IMF分量的小波系数进行处理。最后,对去噪后的IMF分量进行组合重构,得到去噪后的最终信号。对IMF分量应用小波阈值去噪算法,可以有效去除传统CEEMDAN部分重构方法无法去除的噪声分量。利用基于IMF各分量特征计算的阈值,与直接使用单一阈值相比,改进了小波阈值去噪过程。该方法增强了算法的适应性,能够更有效地去除信号中的噪声。我们将该方法应用于水下测距实验。采用532nm调强连续波激光器作为光源。对不同衰减系数的水中目标进行测距。使用白色聚氯乙烯(PVC)反射器作为目标。当直接使用相关极值确定3.75衰减长度距离上的时延时,测距误差为19.2 cm。应用该方法后,测距误差降至6.2 cm,有效提高了测距精度。结果表明,该方法在水下激光雷达系统中具有显著的去噪效果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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