Changchun Institute of Optics,Fine Mechanics and Physics,CAS
Signal-to-noise ratio analysis based on different space remote sensing instruments | |
L. Zhang, B. Li, H. Li, G. Gu and X. Wang | |
2023 | |
发表期刊 | 19430655
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页码 | 1-12 |
摘要 | 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. Authors |
DOI | 10.1109/JPHOT.2023.3330391 |
URL | 查看原文 |
收录类别 | ei |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://ir.ciomp.ac.cn/handle/181722/68179 |
专题 | 中国科学院长春光学精密机械与物理研究所 |
推荐引用方式 GB/T 7714 | L. Zhang, B. Li, H. Li, G. Gu and X. Wang. Signal-to-noise ratio analysis based on different space remote sensing instruments[J]. 19430655,2023:1-12. |
APA | L. Zhang, B. Li, H. Li, G. Gu and X. Wang.(2023).Signal-to-noise ratio analysis based on different space remote sensing instruments.19430655,1-12. |
MLA | L. Zhang, B. Li, H. Li, G. Gu and X. Wang."Signal-to-noise ratio analysis based on different space remote sensing instruments".19430655 (2023):1-12. |
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