Kalman filter residual-based integrity monitoring against measurement faults

Mathieu Joerger, Boris Pervan

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

This paper introduces a new Kalman filter-based method for detecting sensor faults in linear dynamic systems. In contrast with existing sequential fault-detection algorithms, the proposed method enables direct evaluation of the integrity risk, which is the probability that an undetected fault causes state estimate errors to exceed predefined bounds of acceptability. The new method is also computationally efficient and straightforward to implement. The algorithm's detection test statistic is established in three steps. First, the weighted norms of current and past-time Kalman filter residuals are defined as generalized non-centrally chi-square distributed random variables. Second, these residuals are proved to be stochastically independent from the state estimate error. Third, current-time and past-time residuals are shown to be mutually independent, so that the Kalman filter-based test statistic can be recursively updated in real time by simply adding the current-time residual contribution to a previously computed weighted norm of past-time residuals. The Kalman filter-based integrity monitor is evaluated against worst-case fault profiles, which are also derived in this paper. Finally, performance analyses results are presented for an example application of aircraft precision approach navigation, where differential ranging signals from a multi-constellation satellite navigation system are filtered for positioning and carrier phase cycle ambiguity estimation.

Original languageEnglish (US)
Title of host publicationAIAA Guidance, Navigation, and Control Conference 2012
StatePublished - Dec 1 2012
Externally publishedYes
EventAIAA Guidance, Navigation, and Control Conference 2012 - Minneapolis, MN, United States
Duration: Aug 13 2012Aug 16 2012

Publication series

NameAIAA Guidance, Navigation, and Control Conference 2012

Other

OtherAIAA Guidance, Navigation, and Control Conference 2012
CountryUnited States
CityMinneapolis, MN
Period8/13/128/16/12

Fingerprint

Air navigation
Linear control systems
Statistical tests
State estimation
Kalman filters
Statistics
Monitoring
Navigation systems
Fault detection
Random variables
Dynamical systems
Navigation
Aircraft
Satellites
Sensors

ASJC Scopus subject areas

  • Aerospace Engineering
  • Control and Systems Engineering
  • Electrical and Electronic Engineering

Cite this

Joerger, M., & Pervan, B. (2012). Kalman filter residual-based integrity monitoring against measurement faults. In AIAA Guidance, Navigation, and Control Conference 2012 (AIAA Guidance, Navigation, and Control Conference 2012).

Kalman filter residual-based integrity monitoring against measurement faults. / Joerger, Mathieu; Pervan, Boris.

AIAA Guidance, Navigation, and Control Conference 2012. 2012. (AIAA Guidance, Navigation, and Control Conference 2012).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Joerger, M & Pervan, B 2012, Kalman filter residual-based integrity monitoring against measurement faults. in AIAA Guidance, Navigation, and Control Conference 2012. AIAA Guidance, Navigation, and Control Conference 2012, AIAA Guidance, Navigation, and Control Conference 2012, Minneapolis, MN, United States, 8/13/12.
Joerger M, Pervan B. Kalman filter residual-based integrity monitoring against measurement faults. In AIAA Guidance, Navigation, and Control Conference 2012. 2012. (AIAA Guidance, Navigation, and Control Conference 2012).
Joerger, Mathieu ; Pervan, Boris. / Kalman filter residual-based integrity monitoring against measurement faults. AIAA Guidance, Navigation, and Control Conference 2012. 2012. (AIAA Guidance, Navigation, and Control Conference 2012).
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