Estimating Approach Path Coverage of Aircraft-Derived Meteorological Data in Advanced Air Traffic Management Applications

Abstract

If appropriately equipped, aircraft traveling throughout the global air space have the unique capability to measure and report high-resolution meteorological data, under all weather conditions. These data can have high economic value for both aviation and nonaviation uses by communicating a dense picture of weather conditions from thousands of ad hoc sensors operating daily in the global air space over areas of an aviation operational interest. However, ensuring that the technology provides adequate levels of service and safety requires a clear understanding of system performance characteristics in conjunction with sensor and data link capabilities, broadcast frequencies, equipage rates, and operational service environment requirements. This paper explores the density of coverage as a measure of performance by presenting the problem as a stochastic area coverage model of a homogeneous dynamic wireless ad hoc sensor network. A model was developed to relate the density needs of various advanced air traffic management applications to the spatial and temporal coverage of aircraft-sensed meteorological data in the airport terminal area. A comprehensive experimental design is presented with varying aircraft equipage rates, message broadcast frequencies, coverage granularities, and traffic demand levels. Infrastructure and sensor limitations are included to capture some realism within the model. Results are determined by solving this variation on a traditional set covering model using Monte Carlo simulation techniques.

Simulating air transportation networks under capacity constraints

“…In the literature, Monte Carlo simulation has been used as one of the tools in the aviation and air transport research for several purposes. Wide range of applications included climate analysis (Dahlmann et al , 2016) and meteorological data (Audenaerd, 2014), air traffic safety (Di Gravio et al , 2016) and security (Monteiro et al , 2016), risk analysis (Skorupski, 2016), aircraft design (Ng and Willcox, 2015), crash analysis (Ferreri et al , 2016), among others. On the other hand, there were several simulation studies analyzing the problems related specifically to air transportation infrastructure, operations and airports.…”

Applying improved wind and aircraft performance data in wake procedure concepts

“…This landing speed is usually defined by the aircraft operating manual as 1.3 times the stall speed with the selected landing flaps. The nominal approach speed profile in Figure 10 is typical of what has been used in the past to estimate aircraft speed on final approach [9,12].…”

“…Since the motivating research question pertained to aircraft-derived data density, validity requirements were outside the scope of the model. It is worth mentioning that significant effort is being conducted to define the level of data accuracy required by a variety of application areas turning to aircraft-derived data for decision-making [12,15,16,17].…”