Advancements and Applications of the Fully Adaptive Radar Framework
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The Ohio State University / OhioLINK
2018
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| Online Access: | http://rave.ohiolink.edu/etdc/view?acc_num=osu1523891341711601 |
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ndltd-OhioLink-oai-etd.ohiolink.edu-osu15238913417116012021-08-03T07:06:04Z Advancements and Applications of the Fully Adaptive Radar Framework Mitchell, Adam E. Electrical Engineering Fully adaptive radar Cognitive radar To more intelligently interact with their environments, cognitive radars draw inspiration from how biological systems sense, learn, and adapt to their surroundings. The dynamic feedback loop between the cognitive system and the environment is defined as the perception-action cycle. The fully adaptive radar (FAR) framework provides a general structure for emulating the cognitive perception-action cycle in radar systems. In this work, new refinements, extensions, and applications of the FAR framework are proposed. A new construction of the FAR framework is proposed to better align with the structures theorized in cognitive neuropsychology. In this new format, the FAR cost function development, which was previously only vaguely discussed, can be well described using general functions inspired by multi-objective optimization theory. An example of cost function creation is provided. Both experimental and simulated results demonstrate how the user can quickly tailor the system performance for specific tasks by selecting the parameters of a general cost function which reflect their goals. Next, the FAR framework is applied to the task of adaptive radar imaging. This represents an important demonstration because applications of the FAR framework had previously focused exclusively on target tracking. The proposed system adapts the image resolution based on its perceptions of the scene, and it successfully operated both on a simulated scene and the post-processed measurements from the GOTCHA dataset. Finally, the FAR framework is extended to a hierarchical construction. This hierarchical fully adaptive radar (HFAR) framework allows multiple perception-action cycles to be connected, producing increasingly abstract perceptions and actions further up the hierarchy. The HFAR framework allows complex problems of varying scales to be implemented using an internally consistent structure. As an example of this approach, a two-tiered hierarchy for sensor fusion and target tracking is detailed. The efficacy of this proposed system is demonstrated through real-time experiments. 2018-07-25 English text The Ohio State University / OhioLINK http://rave.ohiolink.edu/etdc/view?acc_num=osu1523891341711601 http://rave.ohiolink.edu/etdc/view?acc_num=osu1523891341711601 unrestricted This thesis or dissertation is protected by copyright: all rights reserved. It may not be copied or redistributed beyond the terms of applicable copyright laws. |
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NDLTD |
| language |
English |
| sources |
NDLTD |
| topic |
Electrical Engineering Fully adaptive radar Cognitive radar |
| spellingShingle |
Electrical Engineering Fully adaptive radar Cognitive radar Mitchell, Adam E. Advancements and Applications of the Fully Adaptive Radar Framework |
| author |
Mitchell, Adam E. |
| author_facet |
Mitchell, Adam E. |
| author_sort |
Mitchell, Adam E. |
| title |
Advancements and Applications of the Fully Adaptive Radar Framework |
| title_short |
Advancements and Applications of the Fully Adaptive Radar Framework |
| title_full |
Advancements and Applications of the Fully Adaptive Radar Framework |
| title_fullStr |
Advancements and Applications of the Fully Adaptive Radar Framework |
| title_full_unstemmed |
Advancements and Applications of the Fully Adaptive Radar Framework |
| title_sort |
advancements and applications of the fully adaptive radar framework |
| publisher |
The Ohio State University / OhioLINK |
| publishDate |
2018 |
| url |
http://rave.ohiolink.edu/etdc/view?acc_num=osu1523891341711601 |
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AT mitchelladame advancementsandapplicationsofthefullyadaptiveradarframework |
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