Abstract
This paper describes a method to enhance current surveillance systems used in air traffic control. Those systems are currently based on statistical data fusion, relying on a set of statistical models and assumptions. The proposed method allows for the on-line calibration of those models and enhanced detection of non-ideal situations, increasing surveillance products integrity. It is based on the definition of a set of observables from the fusion process and a rule based expert system with the objective to change processing order, algorithms or even remove some sensor data from the processing chain.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Rong Li, X., Bar-Shalom, Y.: Design of an Interacting Multiple Model Algorithm for Air Traffic Control Tracking. IEEE Transactions on Control System Technology 1(3) (Septemper 1993)
Rafati, A., Moshiri, B., Rezaei, J.: A new algorithm for general asynchronous sensor bias estimation in multisensor-multitarget systems. In: Proceeding of the 10th International Conference on Information Fusion, Quebec, Canada (2007)
Lin, X., Bar-Shalom, Y., Kirubarajan, T.: Multisensor multitarget bias estimation for general asynchronous sensors. IEEE Transactions on Aerospace and Electronic Systems 41, 899–921 (2005)
Lin, X., Bar-shalom, Y., Kirubarajan, T.: Multisensor-multitarget bias estimation for general asynchronous sensors. IEEE Transactions on Aerospace and Electronic Systems 41(3), 899–921 (2005)
ADS-B/TIS-B Functional Architecture, Draft version 0.7. In: EUROCONTROL (July 30, 2003)
Leeson, M.J.: Error Analysis for a wide area multilateration system. QinetiQ/ C&IS/ ADC/ 520896/7/19
Hoogendoorn, R.A., Neven, W.H.L.: ARTAS: Multisensor tracking in an ATC environment. NLR-TP-97657
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2011 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Besada, J.A., Frontera, G., Bernardos, A.M., de Miguel, G. (2011). Adaptive Data Fusion for Air Traffic Control Surveillance. In: Corchado, E., Kurzyński, M., Woźniak, M. (eds) Hybrid Artificial Intelligent Systems. HAIS 2011. Lecture Notes in Computer Science(), vol 6679. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-21222-2_15
Download citation
DOI: https://doi.org/10.1007/978-3-642-21222-2_15
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-21221-5
Online ISBN: 978-3-642-21222-2
eBook Packages: Computer ScienceComputer Science (R0)