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Synthetic Aperture LADAR Automatic Target Recognizer Design and Performance Prediction via Geometric Properties of Targets

Ross, Jacob W.
http://rave.ohiolink.edu/etdc/view?acc_num=wright1651838605629331

Abstract Details

2022, Doctor of Philosophy (PhD), Wright State University, Computer Science and Engineering PhD.
Synthetic Aperture LADAR (SAL) has several phenomenology differences from Synthetic Aperture RADAR (SAR) making it a promising candidate for automatic target recognition (ATR) purposes. The diffuse nature of SAL results in more pixels on target. Optical wavelengths offers centimeter class resolution with an aperture baseline that is 10,000 times smaller than an SAR baseline. While diffuse scattering and optical wavelengths have several advantages, there are also a number of challenges. The diffuse nature of SAL leads to a more pronounced speckle effect than in the SAR case. Optical wavelengths are more susceptible to atmospheric noise, leading to distortions in formed imagery. While these advantages and disadvantages are studied and understood in theory, they have yet to be put into practice. This dissertation aims to quantify the impact switching from specular SAR to diffuse SAL has on algorithm design. In addition, a methodology for performance prediction and template generation is proposed given the geometric and physical properties of CAD models. This methodology does not rely on forming images, and alleviates the computational burden of generating multiple speckle fields and redundant ray-tracing. This dissertation intends to show that the performance of template matching ATRs on SAL imagery can be accurately and rapidly estimated by analyzing the physical and geometric properties of CAD models.
Michael Raymer, Ph.D. (Advisor)
Krishnaprasad Thirunarayan, Ph.D. (Committee Member)
Vincent Velten, Ph.D. (Committee Member)
Brian Rigling, Ph.D. (Committee Member)
Fred Garber, Ph.D. (Committee Member)
Mateen Rizki, Ph.D. (Committee Member)
126 p.
Computer Science
Synthetic Aperture RADAR; Synthetic Aperture LADAR; CAD; Automatic Target Recognition; Performance Prediction

Recommended Citations

Citations

  • Ross, J. W. (2022). Synthetic Aperture LADAR Automatic Target Recognizer Design and Performance Prediction via Geometric Properties of Targets [Doctoral dissertation, Wright State University]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=wright1651838605629331

    APA Style (7th edition)

  • Ross, Jacob. Synthetic Aperture LADAR Automatic Target Recognizer Design and Performance Prediction via Geometric Properties of Targets. 2022. Wright State University, Doctoral dissertation. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=wright1651838605629331.

    MLA Style (8th edition)

  • Ross, Jacob. "Synthetic Aperture LADAR Automatic Target Recognizer Design and Performance Prediction via Geometric Properties of Targets." Doctoral dissertation, Wright State University, 2022. http://rave.ohiolink.edu/etdc/view?acc_num=wright1651838605629331

    Chicago Manual of Style (17th edition)

wright1651838605629331
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© 2022, all rights reserved.
This open access ETD is published by Wright State University and OhioLINK.