OpenSky19:Papers with Abstracts

Abstract. The German Air Navigation Service Provider (ANSP) DFS Deutsche Flugsicherung (DFS) is operating a surveillance infrastructure mainly based on radars and multilateration systems, which provides surveillance information and receives aircraft derived data. The implementation and use of the new surveillance technology Automatic Dependent Surveillance – Broadcast (ADS-B) has to provide benefits in terms of safety, performance or costs. DFS operations require a permanent double surveillance coverage for the area of responsibility. This requirement actually means triple surveillance coverage (in order to provide a seamless service also in case of system outages or planned down times). DFS is implementing ADS-B as the third surveillance layer to reduce costs. Each surveillance layer has to fulfil the performance and safety requirements independently. The fulfilment of safety requirements, integrity and continuity, will require validation of the passively received ADS-B information.
Data integrity and continuity need to be considered w.r.t. safety requirements, but may also have to address security. The integrity of ADS-B data can be ensured either by comparison with data from other surveillance sensors (dependent validation) or by analyzing the properties of the data itself (independent validation). The independent validation of the ADS-B data is a necessary prerequisite for providing a self-contained independent surveillance layer using the ADS-B technology. In a first step, DFS will implement ADS-B as a dependent layer: (1) for validation of the assumption on surveillance performance, (2) to gain experience on data integrity and data continuity, (3) to prepare possible mitigations e.g. against spoofing or jamming and (4) to recognize potential shortcomings in the airborne installations and identify possible mitigations. This first step will support necessary developments (e.g. ADS-B Validation Unit) to move with ADS-B towards the use as an independent surveillance layer reducing infrastructure costs and improve radio spectrum protection.
Abstract. Identification of causes of the delays within transition airspace is an important step in evaluating performance of the Terminal Maneuvering Area (TMA) Air Navigation Services: without knowing the current performance levels, it is difficult to identify which areas could be improved. Inefficient vertical profiles within TMA and deviations from the optimal flight paths due to bad weather conditions are the main sources of performance decline. In this work, we analyse punctuality and vertical efficiency of Stockholm Arlanda airport arrivals, and seek to quantify the fuel consumption impact associated with the inefficient vertical flight profiles within the Terminal Maneuvering Area (TMA).
We use Opensky Network data for evaluation of the Stockholm Arlanda airport performance, comparing it to the DDR2 data provided by Eurocontol, outlining the advantages and disadvantages of both.
Abstract. A key technology to analyze high volume spatio-temporal data streams is complex event processing (CEP). CEP is unique in its ability to not only continuously process data as it arrives through common operations such as aggregations, but also to support pattern matching queries. Pattern Matching allows to detect a user-defined sequence of temporal predicates on event streams. The high volume flight data as provided by the OpenSky Network has a lot of characteristics that make it a perfect match for CEP. In particular, pattern matching operators can be utilized to detect a plethora of movement (landing, starting, evasion) and group patterns (airplanes closing in on each other) in a timely manner. However, CEP queries can be complex in nature and may require a combination of domain expertise and historical data analysis in order to deliver the desired results. In order to address these issues, we have combined a database-backed CEP system (ChronicleDB) with a scientific toolbox for interactive data exploration and geo visualization (Vat System). This allows users to interactively execute CEP queries and visually confirm the validity of their results, thus, simplifying the parameter tuning considerably.
In addition, our solution supports efficient and interactive time travel queries. It allows to combine event streams with additional data sources (e.g., remote sensing images) and processing technologies (e.g., machine learning models) to extract higher level knowledge. Finally, our ongoing work on visual analytics explores extrapolating query results to provide more timely feedback for critical situations and multi-query optimization techniques to allow for an even more efficient system in general.
Abstract. In this paper, we address the ground-to-air (G2A) localization problem using a crowd- sourced network with a mix of synchronized and unsynchronized receivers. First, we use a dynamic model to represent the offset and the skew of the unsynchronized receivers. This model is then used with a Kalman filter (KF) to compensate for the drifts of the unsynchronized receivers’ clocks. Subsequently, the location of the aerial vehicle (AV) is estimated using another KF with the multilateration (MLAT) method and the dynamic model of the AV. We demonstrate the performance advantages of our method through a dataset collected by the OpenSky network. Our results show that the proposed dual KF method decreases the average localization error by orders of magnitude compared with a solo multilateration method. In particular, the proposed method brings the average localization error from tens of kilometers down to hundreds of meters, based on the considered dataset.
Abstract. In this paper, we present a novel way of obtaining extremely challenging image dataset for the purpose of benchmarking image anomaly detection methods. By definition, anomalies are rare occurrences, and therefore, annotation of anomalies using human workforce is difficult and costly, as large amounts of mostly non-anomalous data need to be checked. To alleviate this problem, we use satellite images from as the source of visual data, and combine them with ADS-B data to detect airplanes in a semi-automatic way. This way, our definition of anomaly is an appearance of an airplane on mostly airplane-free images. This not only speeds up annotation, but also provides the exact specification of what constitutes an anomaly, in an objective way. The resulting meta-dataset, containing references to imagery and accurate annotations will be published in the near future. It will include locations of nearly 100 positions of airplanes on satellite images and the corresponding references to satellite images, captured in vicinity of large airports in different parts of the world, in different climate zones.
Abstract. Anomalies in the airspace can provide an indicator of critical events and changes which go beyond aviation. Devising techniques, which can detect abnormal patterns can provide intelligence and information ranging from weather to political events. This work presents our latest findings in detecting such anomalies in air traffic patterns using ADS-B data provided by the OpenSky network [8]. After discussion of specific problems in anomaly detection in air traffic data, we show an experiment in a regional setting, evaluating air traffic densities with the Gini index, and a second experiment investigating the runway use at Zurich airport. In the latter case, strong available ground truth data allows to better understand and confirm findings of different learning approaches.
Abstract. A large quantity of Mode S data is being gathered by the OpenSky receiver network every day. Information regarding common flight states, such as position, ground speed, and the vertical rate is broadcast by ADS-B and has already been decoded and made available for researchers via the OpenSky historical database. However, there is still a large amount of Mode S communication data that has not yet been fully explored. Specifically, the information contained in Enhanced Mode S Surveillance downlink messages can be utilized to better support ATM research. The challenge of decoding such information lies in the implicit inference process for Mode S Comm-B messages. This paper presents a new open library, pymodes-opensky, which connects the existing open-source pyModeS decoder to the raw Mode S messages from the OpenSky historical database through the Impala shell. It also presents a convenient workflow that can be used to obtain additional information regarding airspeeds, flight intentions, and meteorological conditions of a given flight from the OpenSky database. An analysis based on a global dataset from OpenSky is conducted, and the associated Mode S interrogation statistics in different regions are shown.
Abstract. Problems tackled by researchers and data scientists in aviation and air traffic management (ATM) require manipulating large amounts of data representing trajectories, flight parameters and geographical descriptions of the airspace they fly through. The traffic library for the Python programming language defines an interface to usual processing and data analysis methods to be applied on aircraft trajectories and airspaces. This paper presents how traffic accesses different sources of data, leverages processing methods to clean, filter, clip or resample trajectories, and compares trajectory clustering methods on a sample dataset of trajectories above Switzerland.
Abstract. The Automatic Dependent Surveillance-Broadcast (ADS-B) technology is one of the pillars of the future surveillance system for air traffic control. However, its many fundamental vulnerabilities are well known and an active area of research. This paper examines two closely related ADS-B radio frequency channel issues, jamming and garbling.
Both jamming and garbling produce the same physical effect: the reception of mixed signals, coming from different sources (usually not co-located). In this paper, we assess the impact of these reception problems and examine three separate mitigation techniques. Through the use of theoretical evaluations, simulations and real-world analysis based on data collected by the OpenSky Network, we compare their effectiveness and establish a first baseline for their use in modern low-cost, crowdsourced ADS-B networks.
Abstract. GPS is used widely to determine the location of objects across the world. Getting an accurate position is a must, however, jamming signals can adversely affect the precision of received GPS signals. Thus, countermeasures are required to detect such attacks. In this paper, a new GPS jamming detection scheme is proposed to explore real-world GPS jamming incidents on air traffic data. The approach utilizes and investigates on the Automatic Dependent Surveillance-Broadcast (ADS-B) data from OpenSky receivers to detect the jamming attacks. To our knowledge, this work is the first to address GPS jamming detection based on ADS-B quality metrics. The core idea behind this scheme is based on observing the distribution of received data from aircraft under normal situation and use it later to check if there is a jamming attack. More precisely, we consider the Navigation Accuracy Category for position (NACp) parameter, whose value ranges from 0 to 15 and is indicative of the aircraft’s Estimated Position Uncertainty (EPU), as a basis to build the distribution of normal traffic across all NACp categories. In addition, we build the distribution of NaNs values of received location from aircraft for all covered OpenSky receivers at a specific location. Lastly, the distribution for each aircraft at this location is also observed and analyzed. After that, we evaluate the proposed approach by using real incidents to check its effectiveness.
Abstract. With the rapidly growing global air traffic, the impacts of the particulate matter (PM) in the aviation exhaust on climate, environment and public health are likely rising. The particle number and size distribution are crucial metrics for toxicological analysis and aerosol-cloud interactions. The modern aircraft engines are characterized by decreasing levels of mass emissions of particulate matter, leading to little contribution to the mass concentration. However, the abundant ultrafine particles in the aviation exhaust with diameters less than 100 nm may significantly increase the particle number concentration (PNC). Here we will introduce our recent studies on utilizing the Automatic Dependent Surveillance-Broadcast (ADS-B) from OpenSky network to develop the black carbon (BC) particle number emission inventory for global civil aviation and to investigate the influences of aviation emissions on the particle number concentration near Zurich airport.
The developed inventory indicated that the BC particle number emission was approximately (10.9±2.1)×1025 per year with an average emission index of (6.06±1.18)×1014 per kg of burned fuel, which was about 1.3% of the total ground anthropogenic emissions, and 3.6% of the road transport emission.
The preliminary dispersion results showed that the number concentration of volatile particles emitted by aviation was about 2 orders of magnitude higher than that of non-volatile particles. The annual mean contributions of the Zurich airport to the particle number concentrations ranged from about 105 cm-3 at the airport entrance to about 103 cm-3 at ETH Honggerberg (about 6 km away). There were about 1000 hours per year for the investigated locations to have more than 1000 cm-3 from the airport, with medians of about 104 cm-3.
The OpenSky network ADS-B database provides a new opportunity to estimate the aviation emission using the detailed flight trajectory data. The dataset will contribute to reducing the uncertainties in the development of emission inventory, and improve the air quality simulation in the vicinities of airports.
Abstract. Receiving signals on the 1090 MHz frequency, one of the most important radio frequencies used in aviation, is typically done using ground-based receivers. However, an increasing number of airborne or even space-based receivers also aim to receive these signals for applications such as air traffic surveillance and collision avoidance. In this paper, we present our results from a high-altitude radio frequency measurement campaign with the goal to gain insights about the challenges and limitations of receiving 1090 MHz signals at high altitudes. We used a high-altitude balloon equipped with a software-defined radio to collect 1090 MHz signal data. In an extensive analysis of these data, we identify several challenges and provide a first impression of the radio environment at altitudes up to 33.5 km.
Abstract. ADS-B technology is expanding the amount of flight data made available, in the open source, for public sector research. Nowhere is this benefit more visible than in anti- corruption and global transparency research where ADS-B derived flight data is helping expose the airborne movements of corrupt global elites, dodgy public officials, and a vast array of illicit and criminal actors including wildlife traffickers and conflict financiers.
Abstract. The introduction of Automatic Dependent Surveillance-Broadcast (ADS-B) in Aviation as mandated in the US [3,4] and in Europe [1,2] rests on the (at least theoretical) benefits of the switch of paradigm in ATC surveillance from (continuously) active interrogation of aircraft positions by primary radars to (almost always) automatic broadcast of data by the aircraft. The cost/benefit analysis in favour of this shift weights on the 1) higher frequency and precision of the aircraft information (position, speed, . . . ) made available to ATC/neighbouring aircraft leading to increased safety and increased airspace capacity and 2) on the (at least one) order of magnitude reduction in ground infrastructure costs [5]. Infrastructure needs nontheless to be deployed both on the ground and in the air; and in the end it is the passenger who pays via taxes on tickets or airports services: so what is the status of deployment? This paper investigates, using only open and free data, the status of compliance of aircraft in the European airspace, i.e. how many aircraft flying in Europe comply to the EASA ADS-B mandate.
Abstract. Airspace route planning relies on many regulations and individual factors that can be hard to understand for audiences without advanced domain knowledge. This aspect is problematic if regulations are discussed in complex debates about changing air traffic distributions, affecting the broad public in negative and positive ways. To increase accessibility and transparency, we propose a regulation-oriented scheme of trajectory filters that includes a fully automated detection component for regulation deviations. The scheme further includes filters by daytime, custom areas, MTOM, and is part of a client-independent web prototype. In this publication, we specify details on individual filters and their inter- play (1st contribution), while putting a particular emphasis on the deviation detector (2nd contribution).