Abstract
Recent advances in infrared focal plane fabrication have allowed for the production of sensors with small detector size (small pitch) and long integration time (deep electron wells) in large-format arrays. Individually, these are all welcome developments, but we raise the question of whether it is possible to utilize all of these technologies in concert to optimize performance. If so, a key part of such a system will be digital boost filtering, to recover the performance loss due to diffraction blur. We describe a system design concept called PWP (Pitch-Well-Processing) that uses each of these features along with Wiener filtering to optimize range performance. Current targeting performance models, chiefly the Targeting Task Performance (TTP) metric, predict a significant increase in range performance due to boost filtering. We present these calculations within and compare the results to observer perception experiments conducted on simulated target imagery (formed from close-range thermal signatures artificially degraded by blur and noise). Initially, we used Triangle Orientation Discrimination (TOD) targets for basic experiments, followed by experiments using a set of 12 military vehicles. In both types of test, the range at which observers could reliably identify the target was measured with and without digital filtering. This dissertation is focused on the following problems: integrating boost filtering into a system design, measuring the effect of boost filtering through perception experiments, and modeling the same experiments using the TTP metric.
Notes
If this is your thesis or dissertation, and want to learn how to access it or for more information about readership statistics, contact us at STARS@ucf.edu
Graduation Date
2020
Semester
Spring
Advisor
Driggers, Ronald
Degree
Doctor of Philosophy (Ph.D.)
College
College of Engineering and Computer Science
Department
Electrical and Computer Engineering
Degree Program
Computer Engineering
Format
application/pdf
Identifier
CFE0008428; DP0023864
URL
https://purls.library.ucf.edu/go/DP0023864
Language
English
Release Date
November 2025
Length of Campus-only Access
5 years
Access Status
Doctoral Dissertation (Campus-only Access)
STARS Citation
Short, Robert, "Target Acquisition Performance Improvement with Boost and Restoration Filtering Using Deep-Electron-Well Infrared Detectors" (2020). Electronic Theses and Dissertations, 2020-2023. 456.
https://stars.library.ucf.edu/etd2020/456
Restricted to the UCF community until November 2025; it will then be open access.