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A Focal Plane Array and Electronics Model for CMOS and CCD Sensors in the AFIT Sensor and Scene Emulation Tool

Developing an improved model capable of generating realistic synthetic data that represents a wide range of systems can lead to new algorithms and data exploitation techniques.

Electro-optical and infrared (EO/IR) sensor models are useful tools that can facilitate understanding a system’s behavior without expensive and time-consuming testing of an actual system. EO/IR models are especially important to the military industry where truth data is required but is sometimes impractical to obtain through experimentation due to expense or difficulties in procuring hardware.

This research describes implementation of a focal plane array (FPA) model of charge-coupled device (CCD) and complementary metal-oxide semiconductor (CMOS) photodetectors as a component in the Air Force Institute of Technology (AFIT) Sensor and Scene Emulation Tool (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.

Advances in solid-state technology have increased image quality in recent years. Reductions in photodetector sizes have enabled an increase in the number of elements in a pixel array of constant area, allowing proportional increases in the resolution of the system. However, this decrease in pixel size has also reduced the collection area available to convert incident photons to photoelectron signal, which often results in a reduced signal to noise ratio (SNR). This makes it increasingly difficult to sense dim signals or distinguish radiometric characteristics from noise. New and better algorithms for signal processing are one way to compensate for the potential loss in sensitivity and noise performance.

ASSET was created to produce synthetic data representative of real electro-optic and infrared (EO/IR) sensors. Its development was driven by the need for realistic data under controlled conditions without the expense of conducting field or laboratory experiments. ASSET can produce data suitable for signal processing and algorithm development for both real and hypothetical systems by accurately modeling scene and sensor characteristics. The latter is especially important, as military researchers increasingly use modeling for assessing theoretical system performance to keep pace with sensor technology development, without the need to build an entire sensor system.

Many modern image sensors use charge-coupled device (CCD) or complementary metal-oxide semiconductor (CMOS) solid-state photosensors to convert light into a digital signal. Due to imperfections of photosensors, such a conversion is not ideal and leads to noise in the measured signal. Therefore, one can either estimate and reduce the impact of noise from the image sensor, or simulate and predict what the performance of a given sensor will be in terms of image appearance, given the device specifications and key design parameters.

The high-level simulation of noise in photosensors, however, is still an area of active research. The main problem is that photosensors are affected by many different sources of noise, some of which cannot be modeled effectively using only Gaussian noise. The growing use of new pixel architectures, especially staring focal plane array (FPA) technology, introduces new parameters affecting system performance that are not adequately addressed by current models (e.g. offset FPN due to pixel’s transistors). There is a need for high-level image sensor system modeling tools that allow engineers to see realistic visual effects of noise where the user can change individual design or process parameters to quickly see the resulting effects on image quality. This research attempts to address the issue of the lack of high-level photosensor modeling tools that enable the user to simulate realistic effects of noise on CCD and CMOS image sensors.

This work was done by Fernando D. Fernandez for the Air Force Institute of Technology. AFRL-0288

Topics:
Aerospace Data Acquisition Data Acquisition Defense Defense industry Detectors Electronic Components Electronic equipment Electronics Electronics & Computers Imaging Integrated circuits Optical Components Optics Photonics Semiconductors & ICs Sensors Sensors and actuators Thermal Sensors
This Brief includes a Technical Support Package (TSP).
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A Focal Plane Array and Electronics Model for CMOS and CCD Sensors in the AFIT Sensor and Scene Emulation Tool

(reference AFRL-0288) is currently available for download from the TSP library.

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    Aerospace & Defense Technology Magazine

    This article first appeared in the April, 2020 issue of Aerospace & Defense Technology Magazine (Vol. 5 No. 2).

    Read more articles from this issue here.

    Read more articles from the archives here.

    Overview

    The document is a Master's thesis by Fernando D. Fernandez, titled "A Focal Plane Array and Electronics Model for CMOS And CCD Sensors in the AFIT Sensor and Scene Emulation Tool (ASSET)." It was completed at the Air Force Institute of Technology (AFIT) and covers the period from October 2017 to March 2019. The thesis focuses on the development of a model for focal plane arrays (FPAs) and the associated electronics used in Complementary Metal-Oxide-Semiconductor (CMOS) and Charge-Coupled Device (CCD) sensors, which are critical components in infrared and electro-optical systems.

    The introduction outlines the problem statement and provides an overview of the research objectives. The thesis aims to enhance the ASSET, a tool designed for sensor and scene emulation, by integrating a detailed model of FPAs and their electronics. This integration is intended to improve the accuracy and efficiency of simulations used in sensor development and testing.

    The document is structured into several key sections. The first part discusses the theoretical background necessary for understanding the operation of photodiodes, CCD and CMOS technologies, and the various noise factors that affect sensor performance, such as dark current and shot noise. The thesis also includes a detailed description of the sensor model, which encompasses the conversion of photons to electrons and the subsequent processing of these signals.

    The ASSET overview section describes the tool's capabilities and its significance in the context of military applications, where accurate sensor modeling can reduce the need for expensive physical testing. The thesis emphasizes the importance of understanding the electronic characteristics of sensors to optimize their performance in real-world scenarios.

    The document concludes with a bibliography that cites relevant literature, including a key reference by Driggers, Friedman, and Nichols on infrared and electro-optical systems. The thesis is approved for public release, indicating its contribution to the field of sensor technology and its potential applications in defense and aerospace sectors.

    Overall, Fernandez's work represents a significant step in advancing the modeling of sensor technologies, providing valuable insights for future research and development in the area of electro-optical systems.

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