2017 IEEE/AIAA 36th Digital Avionics Systems Conference (DASC)

Conference Information
Name: 2017 IEEE/AIAA 36th Digital Avionics Systems Conference (DASC)
Date: 2017-9-17 - 2017-9-21

Latest articles from this conference

, Ozgur Ozdemir, , Hani Mehrpouyan, David Matolak
2017 IEEE/AIAA 36th Digital Avionics Systems Conference (DASC) pp 1-10; https://doi.org/10.1109/dasc.2017.8102043

Small unmanned aircraft systems (UASs) are expected to take major roles in future smart cities, for example, by delivering goods and merchandise, potentially serving as mobile hot spots for broadband wireless access, and maintaining surveillance and security. Although they can be used for the betterment of the society, they can also be used by malicious entities to conduct physical and cyber attacks to infrastructure, private/public property, and people. Even for legitimate use-cases of small UASs, air traffic management (ATM) for UASs becomes of critical importance for maintaining safe and collusion-free operation. Therefore, various ways to detect, track, and interdict potentially unauthorized drones carries critical importance for surveillance and ATM applications. In this paper, we will review techniques that rely on ambient radio frequency signals (emitted from UASs), radars, acoustic sensors, and computer vision techniques for detection of malicious UASs. We will present some early experimental and simulation results on radar-based range estimation of UASs, and receding horizon tracking of UASs. Subsequently, we will overview common techniques that are considered for interdiction of UASs.
Paul Grunwald
2017 IEEE/AIAA 36th Digital Avionics Systems Conference (DASC) pp 1-4; https://doi.org/10.1109/dasc.2017.8102150

ARINC 818 standardizes the Avionics Digital Video Bus (ADVB). It is a protocol for low latency, high bandwidth, digital video transmission in both commercial and military applications. This whitepaper will discuss the history, background, and provide information on competing technologies.
Leonid Sedov, Valentin Polishchuk, Vishwanath Bulusu
2017 IEEE/AIAA 36th Digital Avionics Systems Conference (DASC) pp 1-10; https://doi.org/10.1109/dasc.2017.8101995

The plenary talk at DASC 2016 by Dr. Parimal Kopardekar, the Principal Investigator of NASA UTM program, highlighted understanding the role of volume, noise and spectrum considerations in airspace demand-capacity modeling as the three requests from UTM developers to the avionics research community [1]. This paper proposes initial answers to all three requests, for the case of unmanned aerial vehicles (UAVs) operating in low-altitude uncontrolled airspace above populated areas: we estimate airspace capacity under several metrics centered on traffic volume manageability, drones noise pollution and spectrum demand. Our work aids in bridging regulators and the industry, by providing policy makers with decision support tools which help to quantify technological requirements which the manufacturers must follow in order to ensure seamless operation of small unmanned aerial systems (sUAS) in an urban airspace.
Joel Huff, Adam Schultz, Maarten Uijt de Haag
2017 IEEE/AIAA 36th Digital Avionics Systems Conference (DASC) pp 1-10; https://doi.org/10.1109/dasc.2017.8102070

Small Unmanned Aerial Systems (sUAS) operations are increasing in demand and complexity. Using multiple cooperative sUAS (i.e., a swarm) can be beneficial and is sometimes necessary to perform certain tasks (e.g. precision agriculture, mapping, surveillance) either independent or collaboratively. However, controlling the flight of multiple sUAS autonomously and in real-time in a challenging environment in terms of obstacles and navigation requires highly accurate absolute and relative position and velocity information for all platforms in the swarm. This information is also necessary to effectively and efficiently resolve possible collision encounters between the sUAS. In our swarm, each platform is equipped with a Global Navigation Satellite System (GNSS) sensor, an inertial measurement unit (IMU), a baro-altimeter and a relative range sensor (range radio). When GNSS is available, its measurements are tightly integrated with IMU and baro-altimeter measurements to obtain the platform's absolute position. At the same time, the raw measurements are exchanged with the other platforms to obtain a highly accurate relative position and velocity solution with integrity. In the presence of GNSS, this relative position and velocity is used to calibrate the range radios. When GNSS is not available due to external factors (e.g., obstructions, interference), the position and velocity estimators switch to an integrated solution based on IMU, baro and relative range measurements, to maintain an accurate relative position estimate, and reduce the drift in the swarm's absolute position estimate as is typical of an IMU-based system. Multiple multi-copter data collection platforms have been developed and equipped with GNSS, inertial sensors and range radios, which were developed at Ohio University. This paper outlines the underlying methodology, the platform hardware components and analyzes and discusses sUAS flight data results.
Kit Siu, Abha Moitra, Michael Durling, Andy Crapo, Meng Li, Han Yu, Heber Herencia-Zapana, Mauricio Castillo-Effen, Shiraj Sen, Craig McMillan, et al.
2017 IEEE/AIAA 36th Digital Avionics Systems Conference (DASC) pp 1-10; https://doi.org/10.1109/dasc.2017.8102059

The size and complexity associated with software that monitors, controls, and protects flight critical products continues to grow. This is compounded by an increased use of autonomous systems which are just as complex, if not more so, since many operator responsibilities are supported and replaced by software in unmanned systems. Further, these systems are subject to cyber-enabled attacks, thereby necessitating another level of complex software to ensure security. General Electric has devoted a team to research and develop a new suite of tools to address the challenges with design, development, and verification of these software-intensive products. The goals are to develop technology, processes, and tools that result in more efficient software and system development as measured by cost and cycle time, and to enable new capabilities such as autonomy and the Industrial Internet. This paper will introduce the GE approach to formal requirements capture, requirements analysis, and auto test generation. We will introduce the ASSERT™ tool chain (Analysis of Semantic Specifications and Efficient generation of Requirements-based Tests). We will demonstrate aspects of the tool on an autonomous aerial inspection system.
Sebastian Timar, Mark Peters, Paul Davis, Mary Beth Lapis, Ian Wilson, Paul Van Tulder, Phil Smith
2017 IEEE/AIAA 36th Digital Avionics Systems Conference (DASC) pp 1-9; https://doi.org/10.1109/dasc.2017.8101982

This paper presents the implementation and application of a prototype What-if Analysis decision support tool for airport traffic planning. The What-if Analysis tool is used to predict airport traffic performance during a future time horizon with forecast operating conditions and to design Departure Management Programs to mitigate the negative impacts of predicted demand/capacity imbalances. Application scenarios include dynamic weather imposing ground hold and/or Miles-In-Trial restrictions on airport departures. We demonstrate the use of the prototype for a historical traffic and weather scenario at Charlotte Douglas International Airport (CLT). Future work includes enhancing the capabilities and user interfaces of the tool, and researching methods to predict future traffic management initiatives from forecast weather and traffic conditions.
E. Theunissen, T. Kotegawa
2017 IEEE/AIAA 36th Digital Avionics Systems Conference (DASC) pp 1-7; https://doi.org/10.1109/dasc.2017.8102089

Testing of Detect and Avoid (DAA) systems ranges from the use of pre-defined inputs, through part-task and full mission simulations up to flight testing. Live, Virtual and Constructive (LVC) data-sources yield the same observation to a client of this data and provide the opportunity to achieve a seamless transition between the various phases of testing. The interface of a system under test is likely to change during early development stages and thus the design of the LVC environment must ensure that such changes do not propagate through the LVC environment in such a way that it unnecessarily affects other components. Modularity is the key enabler for separating functionalities that have different design-evaluation cycle times. The current state-of-the-art in software development for real-time distributed systems enables a modular approach using industry standard middleware. This paper discusses how such an LVC environment has been realized and provides an overview of its use in several flight tests of DAA systems.
Lukas Marcel Schalk, Martin Herrmann
2017 IEEE/AIAA 36th Digital Avionics Systems Conference (DASC) pp 1-7; https://doi.org/10.1109/dasc.2017.8102112

The increasing availability of cheap and powerful drones for various applications is likely to cause a heavy usage of the very low level airspace in metropolitan areas with hundreds of simultaneously airborne drones per square kilometer in the near future. Certainly, the predicted large number of drones presents a major challenge to future UTM and especially to supporting communications systems. However, a robust and reliable communications system for drone-to-infrastructure communications is inevitably needed to grant all drones access to various services provided by UTM. In previous works, it has already been shown that commercial LTE networks are capable of providing connectivity to drones flying at low altitudes in principle. However, airborne drones which transmit data to the UTM infrastructure produce severe inter-cell interference since they have a strong line-of-sight connection to multiple LTE base stations at a time. Hence, we investigate further the suitability of the LTE uplink for drone-to-infrastructure communications in very low level airspace by LTE system-level simulations in this work. In particular, we identify the maximum drone density that can be thoroughly monitored and safely coordinated by a UTM system with LTE communication links. Our simulations show that an LTE system with 5 Mhz uplink bandwidth can support a message delivery ratio of more than 95% for drone densities of up to 200 drones per square kilometer assuming that all drones have to periodically transmit messages of 300 bytes at a rate of 10 Hz. It is concluded that future research has to focus on the mitigation of inter-cell interference so even a larger number of drones can get reliable access to all UTM services.
Brian Baxley, Kurt Swieringa, Roy Roper, Clay Hubbs, Paul Goess, Richard Shay
2017 IEEE/AIAA 36th Digital Avionics Systems Conference (DASC) pp 1-10; https://doi.org/10.1109/dasc.2017.8102073

A 19-day flight test of an Interval Management (IM) avionics prototype was conducted in Washington State using three aircraft to precisely achieve and maintain a spacing interval behind the preceding aircraft. NASA contracted with Boeing, Honeywell, and United Airlines to build this prototype, and then worked closely with them, the FAA, and other industry partners to test this prototype in flight. Four different IM operation types were investigated during this test in the en route, arrival, and final approach phases of flight. Many of the IM operations met or exceeded the design goals established prior to the test. However, there were issues discovered throughout the flight test, including the rate and magnitude of IM commanded speed changes and the difference between expected and actual aircraft deceleration rates.
Nikolai Okuniek, Lukas Sparenberg
2017 IEEE/AIAA 36th Digital Avionics Systems Conference (DASC) pp 1-10; https://doi.org/10.1109/dasc.2017.8102045

This paper investigates opportunities and challenges when implementing Trajectory-based Taxi Operations at airports dependent on the availability of Collaborative Decision Making (CDM) processes in Europe and the U.S. The German Aerospace Center (DLR) and the National Aeronautics and Space Administration (NASA) jointly developed a concept of operations for Trajectory-based Taxi Operations. An essential prerequisite of this concept is that adequate information sharing processes referring to collaborative decision making are available. CDM concepts like Airport Collaborative Decision Making (A-CDM) and Surface Collaborative Decision Making (S-CDM) were introduced by EUROCONTROL and the FAA, respectively, to improve the use of the available airport infrastructure. Both concepts aim to improve the efficiency of airport operations by reducing congestion on the airport surface, improving the traffic flow efficiency, and reducing uncertainties during airport operations. Both concepts are compared in this paper with a focus on taxi operations and the impact on the stakeholders. This paper provides an answer to the question which opportunities and challenges might be faced with the implementation of Trajectory-based Taxi Operations at airports with A-CDM and S-CDM. Especially from the perspective of involved stakeholders, the operational objectives that are partially contradicting to each other are discussed. It is shown that both CDM processes generally leverage the implementation of Trajectory-based Taxi Operations. However, there are still existing gaps that are identified and addressed in this paper. They based on current research in the area of airport surface traffic optimization towards Trajectory-based Taxi Operations.
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