A methodology for determining aircraft fuel burn using air traffic control radar data
Elliott, Matthew Price
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The air traffic system in the United States is currently undergoing a complete overhaul known as "NextGen". NextGen is the FAA's initiative to update the antiquated National Airspace System (NAS) both procedurally and technologically to reduce costs to the users and negative impacts on the general public. There are currently numerous studies being conducted that are focused on finding optimal solutions to the problems of congestion, delay, and the high fuel and noise footprints associated aircraft operations. These studies require accurate simulation techniques to assess the potential benefits and drawbacks for new procedures and technology. One common method uses air traffic control radar data. As an aircraft travels through the air traffic control system, its latitude, longitude, and altitude are recorded at set intervals. From these values, estimates of groundspeed and heading can be derived. Researchers then use this data to estimate aircraft performance parameters such as engine thrust and aircraft configuration, variables essential to estimate fuel burn, noise, and emissions. This thesis creates a more accurate method of simulating aircraft performance based solely on air traffic control radar data during the arrival process. This tool will allow the benefits of different arrival procedures to be compared at a variety of airports and wind conditions before costly flight testing is required. The accuracy of the performance estimates will be increased using the Tool for Assessing Separation and Throughput (TASAT), a fast-time Monte Carlo aircraft simulator that can simulate multiple arrivals with a mixture of different aircraft types. The tool has succeeded in matching various recorded radar profiles and has produced fuel burn estimates with an RMS error of less than 200 pounds from top of descent to landing when compared to high fidelity operational data. The output from TASAT can also be ported to FAA software tools to make higher quality predictions of aircraft noise and emissions.