115 research outputs found
Analysis of weather impact on flight efficiency for Stockholm Arlanda Airport arrivals
Analysis of punctuality of airport arrivals, as well as identification of causes of the delays within transition airspace, is an important step in evaluating performance of the Terminal Maneuvering Area (TMA) Air Navigation Ser- vices. In this work we analyse how different weather events influence arrival punctuality and vertical flight efficiency on example of Stockholm Arlanda airport. We quantify the impact of the deviations from the flight plans influenced by different weather events, by demonstrating that they result in significant arrival delays, vertical inefficiencies and calculating how much extra fuel is wasted due to vertical flight inefficiency within Stockholm TMA.Peer ReviewedPostprint (published version
LocaRDS: A Localization Reference Data Set
The use of wireless signals for the purposes of localization enables a host of applications relating to the determination and verification of the positions of network participants ranging from radar to satellite navigation. Consequently, this has been a longstanding interest of theoretical and practical research in mobile networks and many solutions have been proposed in the scientific literature. However, it is hard to assess the performance of these in the real world and, more importantly, to compare their advantages and disadvantages in a controlled scientific manner. With this work, we attempt to improve the current state of art methodology in localization research and to place it on a solid scientific grounding for future investigations. Concretely, we developed LocaRDS, an open reference data set of real-world crowdsourced flight data featuring more than 222 million measurements from over 50 million transmissions recorded by 323 sensors. We demonstrate how we can verify the quality of LocaRDS measurements so that it can be used to test, analyze and directly compare different localization methods. Finally, we provide an example implementation for the aircraft localization problem and a discussion of possible metrics for use with LocaRDS
LoVe is in the Air -- Location Verification of ADS-B Signals using Distributed Public Sensors
The Automatic Dependant Surveillance-Broadcast (ADS-B) message scheme was
designed without any authentication or encryption of messages in place. It is
therefore easily possible to attack it, e.g., by injecting spoofed messages or
modifying the transmitted Global Navigation Satellite System (GNSS)
coordinates. In order to verify the integrity of the received information,
various methods have been suggested, such as multilateration, the use of Kalman
filters, group certification, and many others. However, solutions based on
modifications of the standard may be difficult and too slow to be implemented
due to legal and regulatory issues. A vantage far less explored is the location
verification using public sensor data. In this paper, we propose LoVe, a
lightweight message verification approach that uses a geospatial indexing
scheme to evaluate the trustworthiness of publicly deployed sensors and the
ADS-B messages they receive. With LoVe, new messages can be evaluated with
respect to the plausibility of their reported coordinates in a location
privacy-preserving manner, while using a data-driven and lightweight approach.
By testing our approach on two open datasets, we show that LoVe achieves very
low false positive rates (between 0 and 0.00106) and very low false negative
rates (between 0.00065 and 0.00334) while providing a real-time compatible
approach that scales well even with a large sensor set. Compared to currently
existing approaches, LoVe neither requires a large number of sensors, nor for
messages to be recorded by as many sensors as possible simultaneously in order
to verify location claims. Furthermore, it can be directly applied to currently
deployed systems thus being backward compatible
dump1030: open-source plug-and-play demodulator/decoder for 1030MHz uplink
Automatic Dependent Surveillance (ADS), Automatic Dependent
Surveillance-Broadcast (ADS-B), Secondary Surveillance Radars (SSR), and Mode S
are key air surveillance technologies representing a critical component of
next-generation air transportation systems. However, compared to 1090MHz
demodulators and decoders, which have plenty of implementations, the 1030MHz
uplink receivers are, in general, scarcely, if at all, represented.
In this paper, we present the development and evaluation of dump1030 -
cross-platform plug-and-play open-source implementation for decoding 1030MHz
uplink Mode A/C/S interrogations. We demonstrate and detail an agile
development process of building dump1030 by adapting a state-of-the-art
dump1090 design and implementation. In our repeated experiments, dump1030
achieves a high detection accuracy of 1030MHz interrogation signals based on
lab evaluation using synthetically-generated interrogation signals. We also
discuss a handful of practical use cases where dump1030 can find immediate
application and implementation, both in research and industrial settings
Validating directed graphs by applying formal concept analysis to conceptual graphs
Although tools exist to aid practitioners in the construction
of directed graphs typified by Conceptual Graphs (CGs), it is still quite
possible for them to draw the wrong model, mistakenly or otherwise.
In larger or more complex CGs it is furthermore often difficult without
close inspection to see clearly the key features of the model. This paper
thereby presents a formal method, based on the exploitation of CGs as
directed graphs and the application of Formal Concept Analysis (FCA).
FCA elucidates key features of CGs such as pathways and dependencies,
inputs and outputs, cycles, and joins. The practitioner is consequently
assisted in reasoning with and validating their models
ADS-B Crowd-Sensor Network and Two-Step Kalman Filter for GNSS and ADS-B Cyber-Attack Detection
Automatic Dependent Surveillance-Broadcast is an Air Traffic Control system in which aircraft transmit their own information (identity, position, velocity, etc.) to ground sensors for surveillance purposes. This system has many advantages compared to the classical surveillance radars: easy and low-cost implementation, high accuracy of data, and low renewal time, but also limitations: dependency on the Global Navigation Satellite System, a simple unencrypted and unauthenticated protocol. For these reasons, the system is exposed to attacks like jamming/spoofing of the on-board GNSS receiver or false ADS-B messages' injection. After a mathematical model derivation of different types of attacks, we propose the use of a crowd sensor network capable of estimating the Time Difference Of Arrival of the ADS-B messages together with a two-step Kalman filter to detect these attacks (on-board GNSS/ADS-B tampering, false ADS-B message injection, GNSS Spoofing/Jamming). Tests with real data and simulations showed that the algorithm can detect all these attacks with a very high probability of detection and low probability of false alarm
Engage D2.2 Final Communication and Dissemination Report
This deliverable reports on the communication and dissemination activities carried out by the Engage consortium over the duration of the network.
Planned activities have been adapted due to the Covid-19 pandemic, however a full programme of workshops and summer schools has been organised. Support has been given to the annual SESAR Innovation Days conference and there has been an Engage presence at many other events.
The Engage website launched in the first month of the network. This was later joined by the Engage ‘knowledge hub’, known as the EngageWiki, which hosts ATM research and knowledge. The wiki provides a platform and consolidated repository with novel user functionality, as well as an additional channel for the dissemination of SESAR results.
Engage has also supported and publicised numerous research outputs produced by PhD candidates and catalyst fund projects
Trajectory Clustering for Air Traffic Categorisation
Availability of different types of data and advances in data-driven techniques open the path to more detailed analyses of various phenomena. Here, we examine the insights that can be gained through the analysis of historical flight trajectories, using data mining techniques. The goal is to learn about usual (or nominal) choices airlines make in terms of routing, and their relation with aircraft types and operational flight costs. The clustering is applied to intra-European trajectories during one entire summer season, and a statistical test of independence is used to evaluate the relations between the variables of interest. Even though about half of all flights are less than 1000 km long, and mostly operated by one airline, along one trajectory, the analysis shows that, for longer flights, there exists a clear relation between the trajectory clusters and the operating airlines (in about 49% of city pairs) and/or the aircraft types (30%), and/or the flight costs (45%)
- …