A Novel Lidar Signal Denoising Method Based on Convolutional Autoencoding Deep Learning Neural Network

The lidar is susceptible to the dark current of the detector and the background light during the measuring process, which results in a significant amount of noise in the lidar return signal. To reduce noise, a novel denoising method based on the convolutional autoencoding deep-learning neural networ...

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Autores principales:	Minghuan Hu, Jiandong Mao, Juan Li, Qiang Wang, Yi Zhang
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	lidar deep learning autoencoder convolutional neural network denoising Meteorology. Climatology QC851-999
Acceso en línea:	https://doaj.org/article/0c1aadc8638a48bdacb3944ca4abe698
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id	oai:doaj.org-article:0c1aadc8638a48bdacb3944ca4abe698
record_format	dspace
spelling	oai:doaj.org-article:0c1aadc8638a48bdacb3944ca4abe6982021-11-25T16:44:09ZA Novel Lidar Signal Denoising Method Based on Convolutional Autoencoding Deep Learning Neural Network10.3390/atmos121114032073-4433https://doaj.org/article/0c1aadc8638a48bdacb3944ca4abe6982021-10-01T00:00:00Zhttps://www.mdpi.com/2073-4433/12/11/1403https://doaj.org/toc/2073-4433The lidar is susceptible to the dark current of the detector and the background light during the measuring process, which results in a significant amount of noise in the lidar return signal. To reduce noise, a novel denoising method based on the convolutional autoencoding deep-learning neural network is proposed. After the convolutional neural network was constructed to learn the deep features of lidar signal, the signal details were reconstructed by decoding part to obtain the denoised signal. To verify the feasibility of the proposed method, both the simulated signals and the actually measured signals by Mie-scattering lidar were denoised. Some comparisons with the wavelet threshold denoising method and the variational modal decomposition denoising method were performed. The results show the denoising effect of the proposed method was significantly better than the other two methods. The proposed method can eliminate complex noise in the lidar signal while retaining the complete details of the signal.Minghuan HuJiandong MaoJuan LiQiang WangYi ZhangMDPI AGarticlelidardeep learningautoencoderconvolutional neural networkdenoisingMeteorology. ClimatologyQC851-999ENAtmosphere, Vol 12, Iss 1403, p 1403 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	lidar deep learning autoencoder convolutional neural network denoising Meteorology. Climatology QC851-999
spellingShingle	lidar deep learning autoencoder convolutional neural network denoising Meteorology. Climatology QC851-999 Minghuan Hu Jiandong Mao Juan Li Qiang Wang Yi Zhang A Novel Lidar Signal Denoising Method Based on Convolutional Autoencoding Deep Learning Neural Network
description	The lidar is susceptible to the dark current of the detector and the background light during the measuring process, which results in a significant amount of noise in the lidar return signal. To reduce noise, a novel denoising method based on the convolutional autoencoding deep-learning neural network is proposed. After the convolutional neural network was constructed to learn the deep features of lidar signal, the signal details were reconstructed by decoding part to obtain the denoised signal. To verify the feasibility of the proposed method, both the simulated signals and the actually measured signals by Mie-scattering lidar were denoised. Some comparisons with the wavelet threshold denoising method and the variational modal decomposition denoising method were performed. The results show the denoising effect of the proposed method was significantly better than the other two methods. The proposed method can eliminate complex noise in the lidar signal while retaining the complete details of the signal.
format	article
author	Minghuan Hu Jiandong Mao Juan Li Qiang Wang Yi Zhang
author_facet	Minghuan Hu Jiandong Mao Juan Li Qiang Wang Yi Zhang
author_sort	Minghuan Hu
title	A Novel Lidar Signal Denoising Method Based on Convolutional Autoencoding Deep Learning Neural Network
title_short	A Novel Lidar Signal Denoising Method Based on Convolutional Autoencoding Deep Learning Neural Network
title_full	A Novel Lidar Signal Denoising Method Based on Convolutional Autoencoding Deep Learning Neural Network
title_fullStr	A Novel Lidar Signal Denoising Method Based on Convolutional Autoencoding Deep Learning Neural Network
title_full_unstemmed	A Novel Lidar Signal Denoising Method Based on Convolutional Autoencoding Deep Learning Neural Network
title_sort	novel lidar signal denoising method based on convolutional autoencoding deep learning neural network
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/0c1aadc8638a48bdacb3944ca4abe698
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A Novel Lidar Signal Denoising Method Based on Convolutional Autoencoding Deep Learning Neural Network

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