不同天气条件下自然背景和人造目标的日、长波高光谱测量分析

Christoph Borel-Donohue, D. Rosario, J. Romano
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引用次数: 1

摘要

本文描述了用Telops公司的长波高光谱相机对新泽西州Picatinny兵工厂采集的图像傅里叶变换光谱数据进行端到端处理。本文的第一部分讨论了从原始数据到标定的辐射率和发射率数据的处理。在几个月的时间里,在不同的天气条件下,每隔6分钟从213英尺高的替代坦克目标塔上采集数据,这是由马里兰州陆军研究实验室赞助的一个项目。开发了一个自动校准和分析程序,可以创建校准数据文件和HTML文件。第一个处理阶段是平场。在此步骤中,使用平均基线来查找死像素(基线低或最大值)。在干涉图部分的标准偏差处检测到噪声像素。使用由单个黑体测量确定的增益和偏移量,创建了一个平场和坏像素校正校准立方体。在第二阶段,每个平场立方体进行傅里叶变换,并进行两点辐射校准。对于选定的立方体,采用温度发射率分离算法。第二部分讨论了环境影响,如日和季节的大气和温度变化以及云量对数据的影响。为了测试环境条件的影响,将距离不变异常检测方法应用于校准的辐射度、亮度温度和发射率数据。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Analysis of diurnal, long-wave hyperspectral measurements of natural background and manmade targets under different weather conditions
In this paper we describe the end-to-end processing of image Fourier Transform spectrometry data taken at Picatinny Arsenal in New Jersey with the long-wave hyperspectral camera from Telops. The first part of the paper discusses the processing from raw data to calibrated radiance and emissivity data. Data was taken during several months under different weather conditions every 6 minutes from a 213ft high tower of surrogate tank targets for a project sponsored by the Army Research Laboratory in Adelphi, MD. An automatic calibration and analysis program was developed which creates calibrated data files and HTML files. The first processing stage is a flat-fielding. During this step the mean base line is used to find dead pixels (baseline low or at the maximum). Noisy pixels are detected where the standard deviation over the part of the interferogram. A flat-fielded and bad pixel corrected calibration cube using the gain and offset determined by a single blackbody measurement is created. In the second stage each flat-fielded cube is Fourier transformed and a 2-point radiometric calibration is performed. For selected cubes a temperature-emissivity separation algorithm is applied. The second part discusses environmental effects such as diurnal and seasonal atmospheric and temperature changes and the effect of cloud cover on the data. To test the effect of environmental conditions the range-invariant anomaly detection approach is applied to calibrated radiance, brightness temperature and emissivity data.
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