Select courses from list below:
Practical Applications of Thermal Imaging Systems
Engineering Approach to Imaging Systems Design
Testing and Evaluation of E-O Imaging Systems
Electro-Optical Imaging System Performance

Electro-optical Imaging System Performance

Imaging system design and performance depend upon a myriad of radiometric, spectral, and spatial parameters. The “bare bones” sensor consists of optics, detector, display, and an observer. Range degrading parameters include 3D noise, optical blur, and pixel interpolation. Scenario parameters include detection, recognition, and identification probability, target contrast, target size, line-of-sight motion, and atmospheric conditions. Generally, the customer provides the scenario and the analyst optimizes sensor parameters to achieve maximum acquisition range. A wide variety of programs have been available in the past (e.g., SSCamIP, NVThermIP etc.). These programs have been consolidated into the Night Vision Integrated Performance Model (NVIPM). For convenience, the calculations are performed in the frequency domain (MTF analysis). This is often called image chain modeling. Although the math is sometimes complex, the equations are graphed for easy interpretation. NVIPM can easily perform trade studies and provides a gradient (sensitivity) analysis. Gradient analysis lists those parameters (in decreasing order) that affect acquisition range.

This course consists of 6 sections: (1) The history of imaging system design and the transition from scanning arrays to staring arrays, (2) imaging system chain analysis covering MTF theory, “bare bones” system design, environmental effects (atmospheric attenuation, turbulence, and line-of-sight motion a.k.a. jitter), sampling artifacts, and image processing, (3) detector responsivity, radiometry, various noise sources (photon, dark current, read) and the resulting SNR, (4) targets, backgrounds, and target signatures, (5) various image quality metrics which includes NVIPM, and (6) acquisition range and trade studies. By far, the most important section is the trade study graphical representations. Three optimization examples are provided (case study examples): long range imaging, short range imaging, and IRST systems.

While the course emphasizes infrared system design, it applies to visible, NIR, and short infrared (SWIR) systems. From an optimization viewpoint, the only difference across the spectral bands is the target signature nomenclature. When considering hardware design, the spectral region limits lens material and detector choices.

This course will enable to you to

  • Use the correct MTFs for image chain analysis
  • Identify the subsystem (e.g., motion, optics, detector, electronics, and display) that limits performance
  • Understand the limitations of range performance predictions
  • Appreciate the importance of trade studies
  • Appreciate the value of graphs rather than a table of numbers
  • Be conversant with the myriad of technical terms

  This course is intended for researchers, engineers, system designers, managers, and buyers who want to understand the wealth of information available from imaging system end-to-end analysis. It is helpful if the students are familiar with linear system theory (MTF analysis).

Course level: Intermediate
Course length: full day

Gerald Holst is an independent consultant for imaging system analysis and testing. He was a technical liaison to NATO, research scientist for DoD, and a member of the Lockheed-Martin senior technical staff. Dr. Holst has chaired the SPIE conference Infrared Imaging Systems: Design, Analy­sis, Modeling and Test­ing since 1989. He is author of over 30 journal articles and 6 books (published by SPIE and/or JCD Publishing). Dr. Holst is a member of OSA and is a SPIE Fellow.

Electro-Optical Imaging System Performance: Staring Arrays, 6th ed (SPIE Press and JCD Publishing, 2017), by Gerald C. Holst.

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