Filtering Enhanced Traffic Management System (ETMS) altitude data

• Autorzy: Palacios R. , Hansman R. J.
• Języki publikacji: EN

Abstrakty

EN

Enhanced Traffic Management System (ETMS) stores all the information gathered by the Federal Aviation Administration (FAA) from aircraft flying in the US airspace. The data stored from each flight includes the 4D trajectory (latitude, longitude, altitude and timestamp), radar data and flight plan information. Unfortunately, there is a data quality problem in the vertical channel and the altitude component of the trajectories contains some isolated samples in which a wrong value was stored. Overall, the data is generally accurate and it was found that only 0.3% of the altitude values were incorrect, however the impact of these erroneous data in some analyses could be important, motivating the development of a filtering procedure. The approach developed for filtering ETMS altitude data includes some specific algorithms for problems found in this particular dataset, and a novel filter to correct isolated bad samples (named Despeckle filter). As a result, all altitude errors were eliminated in 99.7% of the flights affected by noise, while preserving the original values of the samples without bad data. The algorithm presented in this paper attains better results than standard filters such as the median filter, and it could be applied to any signal affected by noise in the form of spikes.

Słowa kluczowe

EN

air transportation; traffic management; signal processing; filters

• Wydawca: Komitet Metrologii i Aparatury Naukowej PAN
• Czasopismo: Metrology and Measurement Systems
• Rocznik: 2013
• Tom: Vol. 20, nr 3
• Strony: 453--464
• Opis fizyczny: Bibliogr. 13 poz., rys., wykr.

Twórcy

autor

Palacios R.

• Instituto de Investigación Tecnológica, ICAI School of engineering, Universidad Pontificia Comillas, Madrid, Spain
• Aeronautics and Astronautics department, Massachusetts Institute of Technology, Cambridge, MA, USA

autor

Hansman R. J.

• Aeronautics and Astronautics department, Massachusetts Institute of Technology, Cambridge, MA, USA

Bibliografia

• [1] FAA (2009). Enhanced Traffic Management System (ETMS), Web site, http://hf.tc.faa.gov/projects/etms.htm, accessed July/2010.
• [2] Volpe (2007). Enhanced Traffic Management System (ETMS) Functional Description, ver. 8.5, Report no. VNTSC-TFM-FD-005, November 2007, Cambridge, MA.
• [3] Krozel J., Rosman D., and Carniol T. (2002). Analysis of En route Sector Demand Prediction Accuracy and Quantification of Error Sources. Final Report, Report RTO 66. Metron Aviation, Reston, VA, USA.
• [4] Futer A. (2009). Dynamic wheels-up time predictions, IEEE/AIAA 28th Digital Avionics SystemsConference. DASC 2009, 23-29 Oct. 2009, Cambridge, MA, USA, 2.B.1 (15 pp.).
• [5] Futer A. (2006). Improving ETMS’ Ground Time Predictions, IEEE/IATA 25TH Digital Avionics Systems Conference. DASC 2006, Portland, OR, 1-12.
• [6] Klein A., and Hafner F. (2005). Computation and Analysis of Aircraft Proximities in the NAS Using ETMS Data, IEEE/IATA 24th Digital Avionics Systems Conference, DASC 2005., Washington, DC, 3.B.6_1--3.B.6_11.
• [7] Myers T., Brennan M., and Klopfenstein M. (2008). A New Approach to Analyzing Airborne Delay, Journal of Guidance, Control, and Dynamics, 31(6), 1793-1801.
• [8] Loizou C. P., and Pattichis C. S. (2008). Despeckle Filtering Algorithms and Software for Ultrasound Imaging, Morgan & Claypool Publishers series.
• [9] Loizou C. P., Pattichis C. S., Christodoulou C. I., Istepanian R. S. H., Pantziaris M., and Nicolaides A. (2005). Comparative evaluation of despeckle filtering in ultrasound imaging of the carotid artery, Ultrasonics, Ferroelectrics and Frequency Control, IEEE Transactions on, 52(10), 1653-1669.
• [10] Liu Y., Liu C., and Wang D. (2009). A 1D time-varying median filter for seismic random, spike-like noise elimination, Geophysics, 74(1), V17-V24.
• [11] Chatterji G. B., Sridhar B., and Kim D. (2003). Analysis of ETMS Data Quality for Traffic Flow Management Decisions, AIAA Guidance, Navigation, and Control Conference and Exhibit, Austin, TX, Paper 5626.
• [12] Tiganj Z., Mboup M., Pouzat C., and Belkoura L. (2010). “An Algebraic Method for Eye Blink Artifacts Detection in Single Channel EEG Recordings,” Proceedings 17th International Conference on Biomagnetism Advances in Biomagnetism - BIOMAG 2010, Berlin, Germany, 175-178.
• [13] Eberly D. (2008). Derivative Approximation by Finite Differences, Geometric Tools, LLC. Scottsdale, AZ, USA.

Uwagi

EN

This work has been partially supported by the “Secretaría General de Universidades del Ministerio de Educación” of Spain. (Programa de becas para estancias de profesores e investigadores en centros extranjeros).