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Statistical Basis for Multispectral Infrared Seeker Trade Studies

机译：多光谱红外搜寻者贸易研究的统计基础

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摘要

Characterization of the utility of information derived from a sensor tasked with performing the function of target object identification requires the consideration of a large number of system parameters including: 1. Possible object classes under observation 2. Measurement-related properties of these objects 3. Observation geometry 4. Sensor modality / waveband(s) 5. Sensor noise characteristics 6. Uncertainties in sensor noise characteristics It is important to consider these parameters in a systematic way in order to objectively assess their relative effects on target selection. Since each of the listed parameters - with the exception of the spectral band(s) - is probabilistic in nature, it makes sense to cast the identification problem in a logically comprehensive way which statistically captures their interdependency. Such a formulation will lend itself to the evaluation and optimization of various aspects of measurement fidelity. This paper discusses a novel approach to systematically incorporating each of the parameters listed above in order to provide a basis for performing a number of system trade studies. The process will be illustrated in the context of a search for the optimal band pair to be used in a two-color infrared (IR) sensor.
机译：表征从执行目标物体识别功能的传感器获取的信息的效用，需要考虑大量的系统参数，包括：1.观察中可能的物体类别2.这些物体的测量相关属性3.观察几何形状4.传感器模态/波段5.传感器噪声特性6.传感器噪声特性的不确定性为了系统地评估这些参数对目标选择的相对影响，系统地考虑这些参数很重要。由于列出的每个参数（除了（一个或多个）光谱带以外）本质上都是概率性的，因此以逻辑上全面的方式投放识别问题是有意义的，该方式可以统计地捕获其相互依赖性。这样的表述将有助于评估和优化测量保真度的各个方面。本文讨论了一种新颖的方法，可以系统地合并上面列出的每个参数，从而为进行大量系统贸易研究提供基础。将在搜索要在双色红外（IR）传感器中使用的最佳波段对的上下文中说明该过程。

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