Towards resilient UAV: Escape time in GPS denied environment with sensor drift

Hyung Jin Yoon, Wenbin Wan, Hunmin Kim, Naira Hovakimyan, Lui Sha, Petros G. Voulgaris

Research output: Contribution to journalConference articlepeer-review


This paper considers a resilient state estimation framework for unmanned aerial vehicles (UAVs) that integrates a Kalman filter-like state estimator and an attack detector. When an attack is detected, the state estimator uses only IMU signals as the GPS signals do not contain legitimate information. This limited sensor availability induces a sensor drift problem questioning the reliability of the sensor estimates. We propose a new resilience measure, escape time, as the safe time within which the estimation errors remain in a tolerable region with high probability. This paper analyzes the stability of the proposed resilient estimation framework and quantifies a lower bound for the escape time. Moreover, simulations of the UAV model demonstrate the performance of the proposed framework and provide analytical results.

Original languageEnglish (US)
Pages (from-to)423-428
Number of pages6
Issue number12
StatePublished - Oct 2019
Event21st IFAC Symposium on Automatic Control in Aerospace, ACA 2019 - Cranfield, United Kingdom
Duration: Aug 27 2019Aug 30 2019


  • Resilient estimation
  • Stochastic system
  • Unmanned aerial vehicle

ASJC Scopus subject areas

  • Control and Systems Engineering


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