Latest revision as of 19:15, 28 January 2021

Abstract

Recent United States Federal Aviation Administration (FAA) wake turbulence research conducted at the John A. Volpe National Transportation Systems Center (The Volpe Center) has continued to monitor the representative localizer Flight Technical Error (FTE) associated with Instrument Landing System (ILS) arrivals. This work complements, extends, and improves on previously published localizer FTE results by calculating FTE from more recent Airport Surface Detection Equipment — Model X (ASDE-X) datasets with improved data quality characteristics, as well as providing a quantification of the FTE measurement uncertainty due to the geometry of the Remote Unit (RU) sensor array that provides the analysis data. The technical description of the ASDE-X system is published as [1]. This paper presents additional FTE results and improved uncertainty calculations for ILS arrivals at John F. Kennedy International Airport (JFK) and Detroit Metropolitan Wayne County Airport (DTW), as well as comparisons with previous documented FTE results from Lambert — St. Louis International Airport (STL). The measurement uncertainty assessment provided insight on the level of confidence that can be placed in each runway specific dataset, and these localizer FTE results confirm the previously published observation that the observed FTE performance is consistently much tighter than the International Civil Aviation Organization (ICAO) navigation tolerances commonly used in safety simulations.

Original document

The different versions of the original document can be found in:

• https://ntlrepository.blob.core.windows.net/lib/43000/43000/43008/Hall_Localizer.pdf

• http://xplorestaging.ieee.org/ielx5/6088077/6095898/06096067.pdf?arnumber=6096067,

http://dx.doi.org/10.1109/dasc.2011.6096067

• https://ntl.bts.gov/lib/43000/43000/43008/Hall_Localizer.pdf,

http://yadda.icm.edu.pl/yadda/element/bwmeta1.element.ieee-000006096067,

https://rosap.ntl.bts.gov/view/dot/9484,

https://ieeexplore.ieee.org/document/6096067,

https://academic.microsoft.com/#/detail/2036759531