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False alarm recognition in hyperspectral gas plume identification

机译:高光谱烟羽识别中的虚假警报识别

摘要

According to one embodiment, a method for analyzing hyperspectral data includes collecting first hyperspectral data of a scene using a hyperspectral imager during a no-gas period and analyzing the first hyperspectral data using one or more gas plume detection logics. The gas plume detection logic is executed using a low detection threshold, and detects each occurrence of an observed hyperspectral signature. The method also includes generating a histogram for all occurrences of each observed hyperspectral signature which is detected using the gas plume detection logic, and determining a probability of false alarm (PFA) for all occurrences of each observed hyperspectral signature based on the histogram. Possibly at some other time, the method includes collecting second hyperspectral data, and analyzing the second hyperspectral data using the one or more gas plume detection logics and the PFA to determine if any gas is present. Other systems and methods are also included.
机译:根据一个实施例,一种用于分析高光谱数据的方法包括:在无气体时段期间使用高光谱成像器收集场景的第一高光谱数据,以及使用一个或多个气体羽流检测逻辑来分析第一高光谱数据。使用低检测阈值执行气体羽流检测逻辑,并检测观察到的高光谱特征信号的每次出现。该方法还包括针对使用气羽检测逻辑检测到的每个观察到的高光谱特征的所有出现生成直方图,以及基于该直方图确定对于每个观察到的高光谱特征的所有出现的误报概率(PFA)。可能在其他时间,该方法包括收集第二高光谱数据,并使用一个或多个气体羽流检测逻辑和PFA分析第二高光谱数据以确定是否存在任何气体。还包括其他系统和方法。

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