Signal-to-Noise Ratio Analysis Based on Different Space Remote Sensing Instruments

Signal-to-noise ratio (SNR) analysis is a crucial component of optical system development for space remote sensing instruments. It serves as a quantitative assessment of the imaging quality and radiometric characteristics of space remote sensing. This paper utilizes the working principles and energy...

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Main Authors: Lei Zhang, Bo Li, Hanshuang Li, Guochao Gu, Xiaoxu Wang
Format: Article
Language:English
Published: IEEE 2024-01-01
Series:IEEE Photonics Journal
Subjects:
Online Access:https://ieeexplore.ieee.org/document/10309190/
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author Lei Zhang
Bo Li
Hanshuang Li
Guochao Gu
Xiaoxu Wang
author_facet Lei Zhang
Bo Li
Hanshuang Li
Guochao Gu
Xiaoxu Wang
author_sort Lei Zhang
collection DOAJ
description Signal-to-noise ratio (SNR) analysis is a crucial component of optical system development for space remote sensing instruments. It serves as a quantitative assessment of the imaging quality and radiometric characteristics of space remote sensing. This paper utilizes the working principles and energy transfer principles of space remote sensing instruments to conduct SNR analysis and model development for commonly used spaceborne imagers, spaceborne imaging spectrometers, micro-optical remote sensing instruments, and point-source spatial targets. Additionally, the paper also examines the impact of the presence and width of slits in different space environments on the SNR of space remote sensing instruments. The calculation results indicate that the analysis of Signal-to-Noise Ratio (SNR) for different space remote sensing instruments requires the establishment of distinct SNR models. The magnitude of SNR primarily depends on crucial factors such as optical system quality, detector performance, and the space environment. Therefore, in the instrument design and data processing processes, it is essential to consider how to maximize SNR and establish more accurate corresponding SNR models to provide high-quality remote sensing data.
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spelling doaj.art-09b8329cc5544d3fbdbfeeafd7a456822024-04-08T23:00:06ZengIEEEIEEE Photonics Journal1943-06552024-01-011621910.1109/JPHOT.2023.333039110309190Signal-to-Noise Ratio Analysis Based on Different Space Remote Sensing InstrumentsLei Zhang0https://orcid.org/0009-0005-7129-2500Bo Li1https://orcid.org/0009-0004-1062-5706Hanshuang Li2https://orcid.org/0000-0001-9830-2776Guochao Gu3https://orcid.org/0000-0003-4930-5799Xiaoxu Wang4https://orcid.org/0000-0002-4291-0729Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun, Jilin, ChinaChangchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun, Jilin, ChinaChangchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun, Jilin, ChinaChangchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun, Jilin, ChinaChangchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun, Jilin, ChinaSignal-to-noise ratio (SNR) analysis is a crucial component of optical system development for space remote sensing instruments. It serves as a quantitative assessment of the imaging quality and radiometric characteristics of space remote sensing. This paper utilizes the working principles and energy transfer principles of space remote sensing instruments to conduct SNR analysis and model development for commonly used spaceborne imagers, spaceborne imaging spectrometers, micro-optical remote sensing instruments, and point-source spatial targets. Additionally, the paper also examines the impact of the presence and width of slits in different space environments on the SNR of space remote sensing instruments. The calculation results indicate that the analysis of Signal-to-Noise Ratio (SNR) for different space remote sensing instruments requires the establishment of distinct SNR models. The magnitude of SNR primarily depends on crucial factors such as optical system quality, detector performance, and the space environment. Therefore, in the instrument design and data processing processes, it is essential to consider how to maximize SNR and establish more accurate corresponding SNR models to provide high-quality remote sensing data.https://ieeexplore.ieee.org/document/10309190/Detectorenergy transfersignal-to-noise ratiospace remote sensing
spellingShingle Lei Zhang
Bo Li
Hanshuang Li
Guochao Gu
Xiaoxu Wang
Signal-to-Noise Ratio Analysis Based on Different Space Remote Sensing Instruments
IEEE Photonics Journal
Detector
energy transfer
signal-to-noise ratio
space remote sensing
title Signal-to-Noise Ratio Analysis Based on Different Space Remote Sensing Instruments
title_full Signal-to-Noise Ratio Analysis Based on Different Space Remote Sensing Instruments
title_fullStr Signal-to-Noise Ratio Analysis Based on Different Space Remote Sensing Instruments
title_full_unstemmed Signal-to-Noise Ratio Analysis Based on Different Space Remote Sensing Instruments
title_short Signal-to-Noise Ratio Analysis Based on Different Space Remote Sensing Instruments
title_sort signal to noise ratio analysis based on different space remote sensing instruments
topic Detector
energy transfer
signal-to-noise ratio
space remote sensing
url https://ieeexplore.ieee.org/document/10309190/
work_keys_str_mv AT leizhang signaltonoiseratioanalysisbasedondifferentspaceremotesensinginstruments
AT boli signaltonoiseratioanalysisbasedondifferentspaceremotesensinginstruments
AT hanshuangli signaltonoiseratioanalysisbasedondifferentspaceremotesensinginstruments
AT guochaogu signaltonoiseratioanalysisbasedondifferentspaceremotesensinginstruments
AT xiaoxuwang signaltonoiseratioanalysisbasedondifferentspaceremotesensinginstruments