Applied software systems

Research Article

Diagnostic Methods and Digital Twins for Improving Sensor Fault Tolerance in UAVs

Nikolay Sergej'vich Abramov¹, Vasily Fedor'ovich Kalugin²

1,2	Ailamazyan Program Systems Institute of RAS, Ves'kovo, Russia
1	n-say@nsa.pereslavl.ru

Abstract. This paper provides a survey of methods employed in the design of digital twins for improving the reliability of UAV sensors. Particular emphasis is placed on inertial sensors, since their failure is the most critical. The article defines the concept of a digital twin and its architecture in the context of diagnostics and signal restoration of UAV sensors. The principal diagnostic approaches based on sensor data are systematized, including model-based, data-driven, and knowledge-based methods. Recovery techniques for sensor readings utilizing hardware and analytical redundancies are discussed. Additionally, open source datasets for fault and anomaly detection in UAVs are reviewed. (In Russian).

Keywords: digital twins, UAVs, inertial sensors, sensor reliability, fault diagnostics, signal recovery, diagnostics, fault tolerance, anomaly detection, datasets

MSC-2020 68Txx; 93-10, 93C95

For citation: Nikolay S. Abramov, Vasily F. Kalugin. Diagnostic Methods and Digital Twins for Improving Sensor Fault Tolerance in UAVs. Program Systems: Theory and Applications, 2026, 17:3, pp. 127–161. (In Russ.). https://psta.psiras.ru/2026/3_127-161.

Full text of article (PDF): https://psta.psiras.ru/read/psta2026_3_127-161.pdf.

The article was submitted 01.06.2026; approved after reviewing 13.07.2026; accepted for publication 13.07.2026; published online 15.09.2026.