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.
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