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An L-Band EMI Analysis of Different Components Used with the NXP HoverGames UAV
This research analyzes L-band EMI interference generated by different components placed on an NXP HoverGames UAV, a key aspect in understanding and preventing failure in the system's GPS correct functioning. Even if the results are specific to this type of drone, particular data can be extracte...
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creator | Dobrea, Dan-Marius Dobrea, Monica-Claudia |
description | This research analyzes L-band EMI interference generated by different components placed on an NXP HoverGames UAV, a key aspect in understanding and preventing failure in the system's GPS correct functioning. Even if the results are specific to this type of drone, particular data can be extracted to qualitatively characterize the electromagnetic behavior of different types of processors running different operating systems and executing a deep learning algorithm. The tests done within the research led to some conclusions with an important impact in the practical field. One such conclusion is that running a human detection algorithm on CUDA processors generates a minimum of EMI disturbances of the GPS unit, much less than running the same program on existing CPU units on the same development board. The paper also provides an insight into a potential combination of different hardware (onboard computers, telemetry units, RC receivers) that can work together with minimal interference on the GPS. |
doi_str_mv | 10.1109/EHB55594.2022.9991300 |
format | conference_proceeding |
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Even if the results are specific to this type of drone, particular data can be extracted to qualitatively characterize the electromagnetic behavior of different types of processors running different operating systems and executing a deep learning algorithm. The tests done within the research led to some conclusions with an important impact in the practical field. One such conclusion is that running a human detection algorithm on CUDA processors generates a minimum of EMI disturbances of the GPS unit, much less than running the same program on existing CPU units on the same development board. 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Even if the results are specific to this type of drone, particular data can be extracted to qualitatively characterize the electromagnetic behavior of different types of processors running different operating systems and executing a deep learning algorithm. The tests done within the research led to some conclusions with an important impact in the practical field. One such conclusion is that running a human detection algorithm on CUDA processors generates a minimum of EMI disturbances of the GPS unit, much less than running the same program on existing CPU units on the same development board. The paper also provides an insight into a potential combination of different hardware (onboard computers, telemetry units, RC receivers) that can work together with minimal interference on the GPS.</abstract><pub>IEEE</pub><doi>10.1109/EHB55594.2022.9991300</doi><tpages>4</tpages></addata></record> |
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language | eng |
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source | IEEE Xplore All Conference Series |
subjects | Electromagnetic interference EMI GPS onboard computer Operating systems Real-time systems Receivers Streaming media Task analysis Telemetry UAV |
title | An L-Band EMI Analysis of Different Components Used with the NXP HoverGames UAV |
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