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Butterfield-Masters-Thesis.pdf (5.35 MB)

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Using Synthetic Cognits and The Combined Cumulative Squared Deviation as Tools to Quantify the Performance of Cognitive Radar Algorithms

Butterfield, Aaron S
http://orcid.org/0000-0002-8063-864X
http://rave.ohiolink.edu/etdc/view?acc_num=osu1461242979

Abstract Details

2016, Master of Science, Ohio State University, Electrical and Computer Engineering.
The computational speed of computing has pushed the digital arm of the radar closer to the antenna, allowing for more flexibility in radar platforms. In conjunction, human cognition has been an interesting case study for building cognitive algorithms for radar platforms. These algorithms employ a perception-action cycle as the base of their functionality. Scaling cognitive algorithms to show high level cognition has been relatively little progress because of the complexity in visualizing the scope of cognitive algorithms. In addition, there has been little forward motion on how to analyze the performance of cognitive algorithms. As a result, this thesis introduces the concept of a synthetic cognit as an abstraction to defining cognition in a radar platform. It introduces the loop diagram as a way to specify the scope of a synthetic cognit that allows an engineer to quickly see the hierarchical connection between a particular synthetic cognit and any other. Once the cognit is defined, goals are established as a control interface to the synthetic cognit. The performance of the algorithm is then calculated using a Combined Cumulative Squared Deviation (CCSD) and Cumulative Coherent Processing Interval (CCPI). This is done by comparing the CCSD and CCPI of the cognit with certain Static Radar Equivalents (SREs) and with other synthetic cognits. It is found that the CCSD and CCPI are effective metrics for quantifying the performance of cognitive algorithms but are highly dependent on the environment to truly compare performance.
Graeme Smith, Ph.D (Advisor)
Fernando Teixeira, Ph.D (Committee Member)
71 p.
Electrical Engineering
cognitive radar, cognit, radar, quantification, cognitive algorithm, Fuster, Haykin

Recommended Citations

Citations

  • Butterfield, A. S. (2016). Using Synthetic Cognits and The Combined Cumulative Squared Deviation as Tools to Quantify the Performance of Cognitive Radar Algorithms [Master's thesis, Ohio State University]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=osu1461242979

    APA Style (7th edition)

  • Butterfield, Aaron. Using Synthetic Cognits and The Combined Cumulative Squared Deviation as Tools to Quantify the Performance of Cognitive Radar Algorithms. 2016. Ohio State University, Master's thesis. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=osu1461242979.

    MLA Style (8th edition)

  • Butterfield, Aaron. "Using Synthetic Cognits and The Combined Cumulative Squared Deviation as Tools to Quantify the Performance of Cognitive Radar Algorithms." Master's thesis, Ohio State University, 2016. http://rave.ohiolink.edu/etdc/view?acc_num=osu1461242979

    Chicago Manual of Style (17th edition)

osu1461242979
1,174
© 2016, all rights reserved.
This open access ETD is published by The Ohio State University and OhioLINK.