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Electro-optical and infrared (EO/IR) sensor and scene generation models are useful tools that can facilitate understanding the behavior of an imaging system and its data processing chain under myriad scenarios without expensive and time-consuming testing of an actual system. EO/IR models are especially important to researchers in remote sensing where truth data is required but often costly and impractical to obtain. The Air Force Institute of Technology (AFIT) Sensor and Scene Emulation Tool (ASSET) is an educational, engineering-level tool developed to rapidly generate large numbers of physically realistic EO/IR data sets. This work describes the implementation of a focal plane array (FPA) model of charge-coupled device (CCD) and complementary metal-oxide semiconductor (CMOS) photodetectors as a component in ASSET. The FPA model covers conversion of photo-generated electrons to voltage and then to digital numbers. It incorporates sense node, source follower, and analog-to-digital converter (ADC) components contributing to gain non-linearities and includes noise sources associated with the detector and electronics such as shot, thermal, 1/f, and quantization noise. This paper describes the higher fidelity FPA and electronics model recently incorporated into ASSET, and it also details model validation using an EO/IR imager in laboratory measurements. The result is an improved model capable of rapidly generating realistic synthetic data representative of a wide range of EO/IR systems for use algorithm development and assessment, particularly when large numbers of truth data sets are required (e.g., machine learning).
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