Degradable Tracking System based on Hardware Multi-Model Estimators

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Degradable_Tracking_System_based_on_Hardware_Multi-Model_Estimators.pdf (3.02 MB)

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https://ieeexplore.ieee.org/abstract/document/9984042

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https://doi.org/10.1109/RWS55399.2022.9984042
 http://hdl.handle.net/11603/27713

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UMBC Computer Science and Electrical Engineering Department
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Author/Creator ORCID

https://orcid.org/0000-0002-4649-3467

Date

2022-12-20

Type of Work

conference papers and proceedings
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Citation of Original Publication

K. Kiriakidis et al., "Degradable Tracking System based on Hardware Multi-Model Estimators," 2022 Resilience Week (RWS), National Harbor, MD, USA, 2022, pp. 1-6, doi: 10.1109/RWS55399.2022.9984042.

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This work was written as part of one of the author's official duties as an Employee of the United States Government and is therefore a work of the United States Government. In accordance with 17 U.S.C. 105, no copyright protection is available for such works under U.S. Law.
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Abstract

Sensing systems onboard unmanned vehicles operate in an environment of constrained computational resources. A cyber-attack may primarily aim to degrade these computing devices and, ultimately, incapacitate the sensing system itself. To prepare a prototype tracking system for degradation, this paper proposes distributed hardware implementation of a Multiple Model estimator on two FPGA units and, after an attack, adaptation of the estimator by leveraging Dynamic Partial Reconfiguration of the single surviving FPGA. The method ensures that the most likely models of the estimator are loaded on to the fabric of the surviving FPGA with minimal interruption.