Paper
23 September 2013 Application study of principal component based physical retrieval algorithm for hyperspectral infrared sensors
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Abstract
An ultra-fast principal component based physical retrieval algorithm has been developed at NASA Langley research center. Works are under way to maximize the application potential of the algorithm in order to generate reliable products from hyper-spectral sensor data for climate studies. The algorithm has been tested using synthetic data for various infrared sensors. This paper describes in detail about retrieval sensitivity study carried out for several hyper-spectral infrared sensors using this physical algorithm. The retrieval accuracy obtained using the algorithm for the atmospheric parameters including trace gases of interests is discussed. Its dependence on the sensor system noise and spectral resolution is illustrated by comparing the retrieval performance achieved for different sensors. PCRTM has been demonstrated to be a reliable tool for end-to-end sensor performance simulations and has great potential for real-time trace gas retrieval applications.
© (2013) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Wan Wu, Xu Liu, Hui Li, Daniel K. Zhou, and Allen M. Larar "Application study of principal component based physical retrieval algorithm for hyperspectral infrared sensors", Proc. SPIE 8866, Earth Observing Systems XVIII, 88660G (23 September 2013); https://doi.org/10.1117/12.2024239
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KEYWORDS
Clouds

Absorption

Infrared radiation

Infrared sensors

Algorithm development

Sensors

Carbon monoxide

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