Airport Surface Detection Equipment Research Articles

Airport Surface Arrival and Departure Scheduling Using Extended First-Come, First-Served Scheduler

This paper demonstrates the effectiveness of the Extended First-Come, First-Served (EFCFS) scheduler for integrated arrival and departure scheduling by comparing the scheduling results with the recorded operational data at Incheon International Airport (ICN), Republic of Korea. The EFCFS scheduler can handle multiple capacity- or flow-rate-related constraints along the path of each flight, which is represented by a node–link graph structure, and can solve large-scale problems with low computational cost. However, few studies have attempted a systematic verification of the EFCFS scheduler by comparing the scheduling results with historical operational data. In this paper, flights are scheduled between gates and runways on the airport surface with detailed constraints such as runway wake turbulence separation minima and conflict-free taxiing. The scheduler is tested using historical flight data from 15 August 2022 at ICN. The input schedule is generated based on the flight plan data extracted from the Flight Operation Information System (FOIS) and airport surface detection equipment data, and the results are compared with the times extracted from the FOIS data. The scheduling results for 500 aircraft show that the average takeoff delay is reduced by about 19 min, while the average landing delay is increased by less than one minute when the gate occupancy constraint is not considered. The results also confirm that the EFCFS effectively utilizes the available time slots to reduce delays by switching the original departure or arrival orders for a small number of flights.

Investigating Runway Incursion Incidents at United States Airports

According to the Federal Aviation Administration (FAA), the number of runway incursions is increasing. Over the last two decades, the number of runway incursions at U.S. airports has increased from 987 in 2002 to 25,036 in 2020. Runway incursions are a major threat to aviation safety, causing major delays and financial consequences for airlines, as well as injury or death through incidents such as aircraft collisions. The FAA promotes the implementation of runway safety technology, infrastructure, procedural methods, alterations to airport layouts, and training practices to reduce the frequency of runway incursions. In this paper, the relationship between airport geometry factors, mitigating technologies, and the number of runway incursions at large hub airports in the United States was investigated using a random effects Poisson model for analyses of panel data. Airport operations data from the FAA Air Traffic Activity System, runway incursion data from the FAA Aviation Safety Information Analysis and Sharing System from 2002 to 2020, and airport geometry data created using airport geometry features from the FAA airport diagrams were collected. Thirty large hub airports with FAA-installed mitigating technologies were investigated. The model identified significant variables that correlate with runway incursions for large hub airport categories defined by the National Plan of Integrated Airport Systems (NPIAS). The model results indicate that airports with significant numbers of runway-to-runway intersection points increase runway incursion rates and mitigating technologies Runway Status Lights (RWSLs) and Airport Surface Detection Equipment, Model X (ASDE-X), can help reduce runway incursions at severity levels A and B.

Empirical Method for Estimating Aircraft Fuel Consumption in Ground Operations

This study proposes a novel procedure for estimating aircraft fuel burn during ground operations using aircraft trajectory data acquired from an airport surface surveillance system. A fundamental assumption employed throughout the study is that aircraft fuel burn on the ground depends on taxi phases and corresponding thrust settings. The computational process is split into three steps: (1) define a taxi phase for each data point by analyzing the trajectory data; (2) find the fuel flow index appropriate for each taxi phase of each engine type from the International Civil Aviation Organization (ICAO) Engine Emissions Databank which contains fuel flow indices for four flight status of every commercial engine; and (3) estimate the total fuel burn on the ground for each flight by multiplying the time duration at each taxi phase by the corresponding fuel flow rate. Using 24-hour surface trajectory data collected from the Airport Surface Detection Equipment (ASDE) system at Seoul/Incheon International Airport, all flights operated on the day were analyzed applying this procedure. The results indicate that suggested taxi fuel burn rates are estimated to be about 17% lower than the ICAO values. The proposed procedure is expected to be used as an alternative method for ground fuel burn estimation.

Simulation of Runway Operations with Application of Dynamic Wake Separations to Study Runway Limitations

This paper presents an evaluation of runway operations at Chicago O’Hare International Airport to estimate the impact of proposed wake vortex separation including Recategorization Phase II and III dynamic separations. The evaluation uses a Monte Carlo simulation model that considers arrival and departure operations. The simulation accounts for static and dynamic wake vortex separations, aircraft fleet mix, runway occupancy times, aircraft approach speeds, aircraft wake circulation capacity, environmental conditions, and operational error buffers. Airport data considered for this analysis are based on Airport Surface Detection Equipment Model X records from Chicago O’Hare International Airport from January to November 2016. Dynamic wake separations are tailored to each unique set of conditions by using environmental and aircraft performance parameters as input and allowing aircraft to be exposed to the same wake vortex strength as in Recategorization Phase II (RECAT II). The analysis shows that further reductions beyond RECAT II for aircraft pairs separated by 2 nautical miles or less is not operationally feasible. These wake separations already result in little to no wake dependency. When this is the case, the challenges in wake separation are to meet runway occupancy times and to make sure aircraft separations allow for human operational variations without resulting in aircraft turnarounds or double-aircraft-occupancy runway violations.

Reactive Temporal Logic-Based Precursor Detection Algorithm for Terminal Airspace Operations

The air traffic management system is one of the most complex manmade systems, with stringent standards for safety and operational performance. Modern surveillance systems make available detailed flight and airport information through onboard and ground recording systems. These recorded datasets can be used for detecting and/or predicting anomalies that hinder safe and efficient operations. The prediction of an anomaly is performed by identifying events that precede the occurrence of an anomaly, which are called precursors. In this paper, we propose a precursor detection algorithm that can identify precursors for flight anomalies through data-driven models designed with surveillance data recorded in the terminal airspace. The proposed algorithm is demonstrated to detect precursors of flight anomalies in the terminal airspace around LaGuardia Airport in New York City using real traffic data obtained from the Airport Surface Detection Equipment–Model X and the terminal automation information service surveillance datasets.

Unimpeded Taxi-Time Prediction Based on the Node–Link Model

This paper presents a new method for predicting unimpeded taxi time based on the airport node–link model through statistical analysis of the airport surface detection equipment surveillance data. The proposed method can predict taxi-out and taxi-in times for departure and arrival flights, respectively, by calculating the link travel times on a node–link model of the airport surface movement. The prediction performance of the proposed method was evaluated using recorded track data from Incheon International Airport during April 2015. Furthermore, the prediction performance was compared with three other methods well known for calculating unimpeded taxi times. The root-mean-squared error of the unimpeded taxi times predicted by the proposed method showed a prediction error of about 1 min for the departure and arrival flights. Moreover, the results showed significant improvement in the predictions of the unimpeded taxi time compared to the other methods.

Analysis of surveillance position error for airfield detection

Purpose The surveillance equipment is one of the most important parts for current air traffic control systems. It provides aircraft position and other relevant information including flight parameters. However, the existing surveillance equipment has certain position errors between true and detected positions. Operators must understand and account for the characteristics on magnitude and frequency of the position errors in the surveillance systems because these errors can influence the safety of aircraft operation. This study aims to develop the simulation model for analysis of these surveillance position errors to improve the safety of aircrafts in airports. Design/methodology/approach This study investigates the characterization of the position errors observed in airport surface detection equipment of an airport ground surveillance system and proposes a practical method to numerically reproduce the characteristics of the errors. Findings The proposed approach represents position errors more accurately than an alternative simple approach. This study also discusses the application of the computational results in a microscopic simulation modeling environment. Practical implications The surveillance error is analyzed from the radar trajectory data, and a random generator is configured to implement these data. These data are used in the air transportation simulation through an application programing interface, which can be applied to the aircraft trajectory data in the simulation. Subsequently, additionally built environment data are used in the actual simulation to obtain the results from the simulation engine. Originality/value The presented surveillance error analysis and simulation with its implementation plan are expected to be useful for air transportation safety simulations.

Metrics to Characterize Airport Operational Performance Using Surface Surveillance Data

Detailed surface surveillance datasets from sources such as the Airport Surface Detection Equipment, Model-X (ASDE-X) can potentially be used to analyze airport operations, in addition to their primary purpose of enhancing safety. This paper describes how surface surveillance data can be used to measure airport performance characteristics in three different ways: charactering surface flows, including identification of congestion hotspots, queue dynamics and departure throughput; developing metrics to evaluate the daily operational performance; and developing metrics to gauge long-term performance across different runway configurations and operating conditions. The proposed metrics have been developed with active feedback from operations personnel at Boston Logan International Airport, and are therefore evaluated and discussed using this airport as an example. These metrics can provide useful feedback on operational performance to airport operators, and, therefore, have the potential to improve the efficiency of surface operations at airports.

Efficient blobs-to-tracks assignment for ASDE-radar data processing

The data association problem with sensors providing multiple detections per target is addressed in the paper. This is the case of the ASDE (airport surface detection equipment) radar, used for tracking ground targets moving on an airport surface. Blobs reconnection and assignment to tracks is jointly carried out in the proposed coupled scheme, with an extended distance considering all available estimations regarding target positions and attributes. The system takes into account constraints for worst-case computation requirements, so guaranteeing real-time operation. A heuristic is used to prune the number of hypotheses to be evaluated and keep it below a fixed bound, guiding the search to the appropriate decisions under such limitations. The system has been evaluated in some complex scenarios generated by simulation, analysing the trade-off between performance and computation, and it is compared with a conventional decoupled scheme performing one-to-one association of detections to tracks.

Potential Information Integration of a Surface Management System Concept with Other Air Traffic Systems

NASA and FAA have identified the need for future air traffic control (ATC) automation tools to integrate with other existing or planned automation tools. Issues such as complementary decision support features (i.e. combining departure and arrival planning tools), limited display space in the FAA facilities, and the potential for performance benefits of integrating systems have driven the need to examine integration. NASA is currently leading the research and development of the Surface Management System (SMS). SMS is an information and decision support tool designed to aid ATC controllers and traffic managers in managing surface operations. This document provides an initial examination of the potential integration of the SMS concept to integrate with the Airport Surface Detection Equipment X-band (ASDE-X) and the Traffic Management Advisor (TMA).

Increasing airport efficiency: injecting new technology

Advanced surface movement guidance and control systems (A-SMGCS) - called airport surface detection equipment in North America - can potentially solve the airport capacity bottleneck while maintaining at least the current safety level. A-SMGCS are becoming increasingly sophisticated and play a major role in avoiding runway incursions. To investigate the feasibility of phasing in new technology to ease airport operations, the European Commission has funded several research projects. The latest project, called VISION (improVed aIrport A-SMGCS by integrated multisensor data fuSION), aims to apply all the technologies developed in previous projects, including A-SMGCS, to a set of real airports.

Radar SCR improvement using a wavelet transform

AbstractSince the autocorrelation function of radar clutter between cells usually attenuates rapidly compared to that of the signal, the waveform after detection has larger changes in the clutter than the signal. Improving the signal‐to‐clutter ratio (SCR) in conventional radar relies on the integration effect of the amplitude, but here we tried to use the differences in the frequency components of the waveforms. We compared the output after detection obtained from aircraft flying over the ocean by asynchronous detection shipborne radar to the waveform that used Daubechies wavelet, and verified the effect. Next, we defined the signal area and the SCR and quantitatively calculated the improvement. Although we were able to verify an improvement of several decibels for a nearby target, the effect could not be obtained for a distant target. We could provide nearly the same improvement for all of the targets by changing the filter that varies the cutoff frequency with distance. In experiments, we were able to demonstrate a similar improvement by using wavelets in the detected output of the experimental Airport Surface Detection Equipment set up at Sendai Airport. © 2002 Wiley Periodicals, Inc. Electron Comm Jpn Pt 1, 85(10): 23–32, 2002; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/ecja.1128

Airport surface detection equipment

A special-purpose, high-resolution, radar that maps the airport surface has proved a useful tool to monitor aircraft movements under conditions of poor visibility. Such radars are referred to as ASDE (Airport Surface Detection Equipment). The rationale for the design and critical parameter selection for the ASDE-3 is presented. Key features of the chosen design are a rotodome with variable focus antenna, frequency-agile TWT transmitter, and a digital scan converter. Each feature brought specific and significant improvement to the system performance and these improvements, are discussed in some depth.

Ground Control of Airport Traffic

As a result of complex airport geometry and high traffic volume, the control of aircraft on the ground is becoming increasingly difficult. Poor weather and night add to the problems. Airport surface detection and control equipment is being developed to assist the pilot and the traffic controller. The cost of these systems, however, may cause some to be eliminated.

The Communications Picture in 1965

The communications capacity required of the Common System for the year 1965 is projected from figures of fix postings for 1946 and 1954. In 1946, 8,800,000 fixes were reported; in 1954, 16,900,000 fixes were recorded. If this trend continues, the forecast for 1965 is 1,100,000 instrument approaches, and 32 million fix postings! Additionally, there are new requirements to be considered for the 1965 communications system. These are Airport Surface Detection Equipment and expanded helicopter service making short distance flights between cities and from airports to urban heliports, plus the ever increasing tendency for all flights to be controlled similarly to IFR flights. Studies on improving communications, conducted in the Boston area, have indicated the pattern for future work to be undertaken. One finding was the excessive amount of time spent by the controller communicating rather than controlling. The possibility of using codes for routine communications to eliminate repetition of messages between pilot and controller was suggested by this study. The Common System Beacon, under development primarily for radar reinforcement and flight identity, with the addition of altitude information would lend itself well to coding, with a subsequent saving in voice communications time. In the investigation of a communications system for the Common System of Air Navigation and Traffic Control, the goal should be for one of limitless communications capacity. This is the challenge for the communications engineer.