Measurement of Airport Operations Using a Low-Cost Transponder Data Receiver and Collection Unit

Accurate counts of aircraft operations at unmonitored or partially-monitored general aviation airports are important due to their role in the allocation of funds for airport development and improvement. While the Federal Aviation Administration annually invests approximately $1B in small commercial and general aviation airports, fewer than 270 of these 2,950 airports have either full- or part-time air traffic personnel available to register operations counts. Aircraft operations at airports with limited personnel may be counted using temporary acoustic, pneumatic, or video devices, and observations from contract staff. The related sample sizes are inherently small, leading to inaccuracies in the extrapolation of long-term totals. In some cases, the counts may simply be estimated unscientifically by airport managers. Data from aircraft transponders, critical for the safe and efficient management of airspace, may also be used to accurately count airport operations. This data may be collected by a receiver and analyzed with appropriate algorithms. While a majority of the data records (Basic Mode S and Mode C) do not include aircraft positions, a small portion (Extended Mode S) contain position information from which aircraft distances may be directly computed. This dissertation describes a method by which these known distances may be used to calibrate an adaptive digital filter that can be used to estimate distances for the remainder of the aircraft that do not transmit position information. The resulting distance estimates, which exhibit an average error of 0.77 nm per transponder record within 5.0 nm of the receiver, may then be used in conjunction with aircraft altitude and other parameters to identify and register airport operations. Over 16 million data records from three receiver installations at two general aviation airports with collection periods varying from eight to 180 days were used to evaluate the algorithms. The automated operations counts were compared with official air traffic control tower counts obtained from the FAA’s Air Traffic Activity Data System (ATADS) database. A 180-day evaluation found the algorithm provided counts within 2.2% of 52,750 operations; shorter-term comparisons were accurate to within 10% of the FAA counts. The method therefore appears to be an effective and inexpensive means of establishing accurate operations counts at airports with limited personnel