scholarly journals AS-CRI: A New Metric of FTIR-Based Apparent Spectral-Contrast Radiant Intensity for Remote Thermal Signature Analysis

2019 ◽  
Vol 11 (7) ◽  
pp. 777 ◽  
Author(s):  
Sungho Kim ◽  
Jungho Kim ◽  
Jinyong Lee ◽  
Junmo Ahn

Infrared signature analysis that considers both the target and background is fundamentally important to the development of target detection systems as well as in the design of ships for thermal stealth. This paper presents the analysis results of long-term infrared signature variations in terms of the apparent spectral-contrast radiant intensity measured using Fourier transform infrared (FTIR)-based hyperspectral images. A novel apparent spectral-contrast radiant intensity (AS-CRI) measure is proposed to evaluate the spectral infrared signature accurately at the sensor point of view. The spectral information by AS-CRI can provide the optimal band for either target detection or thermal stealth purposes, considering the background and atmospheric transmittance. In addition, the effects of seasonal and weather variations were analyzed from the long-term hyperspectral image database constructed during 2018.01–2018.08 (three times a day). A TELOPS HYPER-CAM MWE camera was adopted to acquire 374 bands in 1.5–5.5 μm. The automatic weather system (AWS) can provide 24 h weather recordings for the signature evaluation. The experimental results validate the utility of the novel AS-CRI method to find spectral bands for a range of infrared signature applications including small infrared target detection.

2021 ◽  
Author(s):  
Weiying Xie ◽  
Jiaqing Zhang ◽  
Jie Lei ◽  
Yunsong Li ◽  
Xiuping Jia

Author(s):  
Xuefeng Liu ◽  
Congcong Wang ◽  
Hao Wang ◽  
Min Fu ◽  
Yuping Feng ◽  
...  

2020 ◽  
Vol 8 (12) ◽  
pp. 1030
Author(s):  
Junbo Zhang ◽  
Chonglan Ren ◽  
Hu Zhang ◽  
Fang Yin ◽  
Shuo Zhang ◽  
...  

The dynamic predator–prey relations in the food web are vital for understanding the function and structure of ecosystems. Dietary estimation is a research hotspot of quantitative ecology, providing key insights into predator–prey relationships. One of the most promising approaches is quantitative fatty acid signature analysis (QFASA), which is the first generation of statistical tools to estimate the quantitative trophic predator–prey relationships by comparing the fatty acid (FA) signatures among predators and their prey. QFASA has been continuously widely applied, refined and extended since its introduction. This article reviewed the research progress of QFASA from development and application. QFASA reflects the long-term diet of predator, and provides the quantitative dietary composition of predator, but it is sensitive to the metabolism of predator. The calibration coefficients (CCs) and the FA subset are two crucial parameters to explain the metabolism of predators, but the incorrect construction or improper use of CCs and the FA subset may cause bias in dietary estimation. Further study and refinement of the QFASA approach is needed to identify recommendations for which CCs and subsets of FA work best for different taxa and systems.


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