Pseudolite Architecture and Performance Analysis for the FAA\u27s NextGen Airspace

By 2025 the FAA plans to have fully implemented its NextGen Airspace design. NextGen takes advantage of modern positioning technologies as well as automation, data sharing, and display technologies that will allow more efficient use of our ever busier National Airspace (NAS). A key element of NextGen is the transition from surveillance RADAR providing aircraft separation and navigation to the use of the GPS and Automatic Dependent Surveillance Broadcast (ADS-B). ADS-B couples the precision of the GPS with networked ground and airborne receivers to provide precise situational awareness to pilots and controllers. The result is increased safety, capacity, and access with reduced reliance on an outdated and costly existing infrastructure. Reliance on the vulnerable GPS requires a backup system with higher positioning accuracy than those that are in place today. The USAF 746th Test Squadron at Holloman AFB, in partnership with Locata Corp., has demonstrated an Ultra High Accuracy Reference System (UHARS) over the Holloman Range composed of pseudolites (ground based satellites) transmitting GPS like signals. This study evaluates the suitability of the UHARS when applied on a national scale to meet Alternate Precision Navigation and Timing (APNT) requirements. From a systems architecture perspective UHARS is evaluated against APNT CONOPs stated Operational Improvements and Scenarios. From a signal architecture perspective the UHARS is evaluated against frequency and bandwidth constraints, service volume requirements and positioning accuracy determined by NextGen Airspace aircraft separation criteria

Increasing the robustness of networked systems

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2009.Includes bibliographical references (p. 133-143).What popular news do you recall about networked systems? You've probably heard about the several hour failure at Amazon's computing utility that knocked down many startups for several hours, or the attacks that forced the Estonian government web-sites to be inaccessible for several days, or you may have observed inexplicably slow responses or errors from your favorite web site. Needless to say, keeping networked systems robust to attacks and failures is an increasingly significant problem. Why is it hard to keep networked systems robust? We believe that uncontrollable inputs and complex dependencies are the two main reasons. The owner of a web-site has little control on when users arrive; the operator of an ISP has little say in when a fiber gets cut; and the administrator of a campus network is unlikely to know exactly which switches or file-servers may be causing a user's sluggish performance. Despite unpredictable or malicious inputs and complex dependencies we would like a network to self-manage itself, i.e., diagnose its own faults and continue to maintain good performance. This dissertation presents a generic approach to harden networked systems by distinguishing between two scenarios. For systems that need to respond rapidly to unpredictable inputs, we design online solutions that re-optimize resource allocation as inputs change. For systems that need to diagnose the root cause of a problem in the presence of complex subsystem dependencies, we devise techniques to infer these dependencies from packet traces and build functional representations that facilitate reasoning about the most likely causes for faults. We present a few solutions, as examples of this approach, that tackle an important class of network failures. Specifically, we address (1) re-routing traffic around congestion when traffic spikes or links fail in internet service provider networks, (2) protecting websites from denial of service attacks that mimic legitimate users and (3) diagnosing causes of performance problems in enterprises and campus-wide networks. Through a combination of implementations, simulations and deployments, we show that our solutions advance the state-of-the-art.by Srikanth Kandula.Ph.D

Proceedings of the 3rd International Conference on Models and Technologies for Intelligent Transportation Systems 2013

Challenges arising from an increasing traffic demand, limited resource availability and growing quality expectations of the customers can only be met successfully, if each transport mode is regarded as an intelligent transportation system itself, but also as part of one intelligent transportation system with “intelligent” intramodal and intermodal interfaces. This topic is well reflected in the Third International Conference on “Models and Technologies for Intelligent Transportation Systems” which took place in Dresden 2013 (previous editions: Rome 2009, Leuven 2011). With its variety of traffic management problems that can be solved using similar methods and technologies, but with application specific models, objective functions and constraints the conference stands for an intensive exchange between theory and practice and the presentation of case studies for all transport modes and gives a discussion forum for control engineers, computer scientists, mathematicians and other researchers and practitioners. The present book comprises fifty short papers accepted for presentation at the Third Edition of the conference. All submissions have undergone intensive reviews by the organisers of the special sessions, the members of the scientific and technical advisory committees and further external experts in the field. Like the conference itself the proceedings are structured in twelve streams: the more model-oriented streams of Road-Bound Public Transport Management, Modelling and Control of Urban Traffic Flow, Railway Traffic Management in four different sessions, Air Traffic Management, Water Traffic and Traffic and Transit Assignment, as well as the technology-oriented streams of Floating Car Data, Localisation Technologies for Intelligent Transportation Systems and Image Processing in Transportation. With this broad range of topics this book will be of interest to a number of groups: ITS experts in research and industry, students of transport and control engineering, operations research and computer science. The case studies will also be of interest for transport operators and members of traffic administration