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An Expert System Approach to Bistatic Space-Time Adaptive Processing

Burwell, Alex
http://orcid.org/0000-0002-5386-6508
http://rave.ohiolink.edu/etdc/view?acc_num=dayton1618405886692882

Abstract Details

2021, Doctor of Philosophy (Ph.D.), University of Dayton, Electrical Engineering.
Space-Time Adaptive Processing (STAP) is a modern radar signal processing technique that leverages additional Degrees of Freedom (DoF) to cancel clutter from a background environment and produce detections of slow-moving targets. STAP is well-documented and understood; however, bistatic applications, or applications in which a radar transmitter and receiver are physically separated, present additional complications. This work explores techniques in Bistatic Space-Time Adaptive Processing (B-STAP) for Ground-Moving Target Indication (GMTI)---the detection of slow-moving surface targets through ground clutter. Due to the complexity and availability of B-STAP data, the evaluation of bistatic algorithms is challenging. A simulation framework has been created to test and evaluate monostatic and bistatic STAP algorithms, mitigating the lack of representative test data. The framework leverages foundational techniques and characteristics to provide a flexible and extensible mechanism for testing and evaluation. Additionally, the design of a new pluggable bistatic Expert System (ES) processor is presented. The ES leverages existing data excision and warping techniques and pairs them with new Range-Based Compensation (RBC) and Clutter Scoring methods to optimize covariance estimation. The simulation framework is used to evaluate the effectiveness of the ES compared to a variety of previously established bistatic processing techniques. The results validate the approach taken in the ES and provide a path for future exploration.
Andrew Bogle, PhD (Committee Chair)
Robert Penno, PhD (Committee Member)
Aaron Nielsen, PhD (Committee Member)
Ethan Lin, PhD (Committee Member)
Lorenzo Lo Monte, PhD (Committee Member)
145 p.
Electrical Engineering
bistatic radar; space-time adaptive processing; bistatic stap; stap; radar; expert system

Recommended Citations

Citations

  • Burwell, A. (2021). An Expert System Approach to Bistatic Space-Time Adaptive Processing [Doctoral dissertation, University of Dayton]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=dayton1618405886692882

    APA Style (7th edition)

  • Burwell, Alex. An Expert System Approach to Bistatic Space-Time Adaptive Processing. 2021. University of Dayton, Doctoral dissertation. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=dayton1618405886692882.

    MLA Style (8th edition)

  • Burwell, Alex. "An Expert System Approach to Bistatic Space-Time Adaptive Processing." Doctoral dissertation, University of Dayton, 2021. http://rave.ohiolink.edu/etdc/view?acc_num=dayton1618405886692882

    Chicago Manual of Style (17th edition)

dayton1618405886692882
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© 2021, all rights reserved.
This open access ETD is published by University of Dayton and OhioLINK.