Conformance monitoring is a key technique used to check whether an aircraft is likely to deviate or has deviated significantly from its assigned flight plan or clearance. Because of the inherent uncertainties and disturbances, it is difficult to define a reasonable range for inevitable deviations during flight. The solution framework in this paper is proposed to detect nonconformance based on the comparison between the state values measured by a surveillance system and a range of expected state values. The probabilistic framework in Gaussian processes is adopted to formulate these uncertainties and to model the behavior of conforming flights. A specified interval of the probabilistic distribution of state values in the proposed model is used as the acceptable range of expected state values. Practical examples in two common level-flight scenarios are presented to demonstrate the performance of this approach in terms of detection time and false alarm rate.
Probabilistic Approach to Conformance Monitoring Using Gaussian Processes
2017
Aufsatz (Zeitschrift)
Englisch
Probabilistic Approach to Conformance Monitoring Using Gaussian Processes
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