Soft error assessment of attitude estimation algorithms running on resource-constrained devices under neutron radiation
There is a growing incorporation of unmanned aerial vehicles (UAVs) within remote and urban environments due to their versatility and ability to access hard-to-reach and/or congested places. UAVs offer low-cost solutions for many applications, including healthcare (e.g., medical supplies delivery) and surveillance during public events, protests, or emergencies (e.g., nuclear accident). However, drone utilisation in urban areas often relies on strict regulations to ensure safe and responsible operation. UAVs are subject to radiation-induced soft errors, and identifying the most vulnerable software and hardware components to radiation exposure is a advisable task, which is difficult to undertake. An essential task to UAVs correct operation is attitude estimation. This paper assesses the soft error reliability of three attitude estimation algorithms running on two resource-constrained microprocessors under neutron radiation. Results suggest that the extended Kalman filter (EKF) algorithm provides the best mean work to failure result for critical fault events, which is about 3× more than the indirect Kalman filter (IKF) and 1.5× more w.r.t. the novel quaternion Kalman filter algorithm (NQKF).
Funding
MultiRad (PAI project funded by Région Auvergne-Rhône-Alpes)
DTP 2018-19 Loughborough University
Engineering and Physical Sciences Research Council
Find out more...IRT Nanoelec (ANR-10-AIRT-05 project funded by French PIA)
UGA/LPSC/GENESIS platform
CAPES
CNPq (grants no. 317087/2021-5 and 407477/2022-5)
FAPERGS
History
School
- Mechanical, Electrical and Manufacturing Engineering
Published in
IEEE Transactions on Nuclear SciencePublisher
Institute of Electrical and Electronics EngineersVersion
- AM (Accepted Manuscript)
Rights holder
© IEEEPublisher statement
© 2024 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.Acceptance date
2024-03-12Publication date
2024-03-18Copyright date
2024ISSN
0018-9499eISSN
1558-1578Publisher version
Language
- en