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Development of a detect-and-avoid sensor solution for the integration of a group 3 large unmanned aircraft system into the national airspace system

Unmanned Aircraft Systems (UAS) face one common challenge when integrating with the existing manned aircraft population in the National Airspace System (NAS). To unlock the full efficiency of UAS, the UAS integrator must comply with an onboard pilot’s requirement to see-and-avoid other aircraft while operating. Commercially available Detect-and-Avoid (DAA) sensor technologies have been developed to attempt to comply with this requirement. UAS integrators must use these sensors to meet or exceed the performance of a human pilot. This thesis covers research done to integrate an array of commercially made DAA sensors with a large Group 3 UAS both in hardware and software that was later flight tested and evaluated for usability. A fast-time simulation is presented using the principles of the National Aeronautics and Space Administration's (NASA) Detect-and-AvoID Alerting Logic for Unmanned Systems (DAIDALUS). Last, open-source tools are presented to assist future integrators in validating their DAA solutions.

Identiferoai:union.ndltd.org:MSSTATE/oai:scholarsjunction.msstate.edu:td-6234
Date06 August 2021
CreatorsRyker, Kyle Bradley
PublisherScholars Junction
Source SetsMississippi State University
Detected LanguageEnglish
Typetext
Formatapplication/pdf
SourceTheses and Dissertations

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