Publications
U.S. Department of Transportation Federal Aviation Administration Field Demonstration #2: Final Report for Staffed NextGen Tower (SNT)
March 1, 2012
Project Report
Published in:
MIT Lincoln Laboratory Report ATC-389
Topic:
R&D area:
Summary
Staffed NextGen Towers (SNT), a research concept being developed and validated by the Federal Aviation Administration (FAA), is a paradigm shift to providing air traffic control services primarily via surface surveillance approved for operational use by controllers instead of the existing out-the-window (OTW) view at high-density airports. SNT was exercised as a prototype installed at the Dallas-Fortworth International Airport (DFW) during a two-week demonstration in the spring of 2011. MIT Lincoln Laboratory conducted this demonstration for the FAA in coordination with DFW air traffic control (ATC) and the DFW airport authority. This proof-of-concept demonstration used live traffic and was conducted by shadowing East tower operations from the DFW center tower, which is a back-up facility currently not typically used for air traffic control. The objective of this SNT field demonstration was to validate the supplemental SNT concept, to assess the operational suitability of the Tower Information Display System (TIDS) display for surface surveillance, and to evaluate the first iteration of prototype cameras in providing visual augmentation. TIDS provided surface surveillance information using an updated user interface that was integrated with electronic flight data. The cameras provided both fixed and scanning views of traffic to augment the OTW view. These objectives were met during the two-week field demonstration. DFW air traffic provided twelve controllers, three front line manager (FLMs), and three traffic management coordinators (TMCs) as test subjects. The twelve National Air Traffic Controllers Association (NATCA) DFW controllers "worked" the traffic according to their own techniques, using new hardware and software that included high resolution displays of surveillance data augmented by camera views. This equipment was designed to provide enhanced situational awareness to allow controllers to manage increased traffic volume during poor visibility conditions, leading to increased throughput. Results indicated that the likelihood of user acceptance and operational suitability is high for TIDS as a primary means for control, given surface surveillance that is approved for operational use. Human factors data indicated that TIDS could be beneficial. However, major technical issues included two display freezes, some incorrectly depicted targets, and display inconsistencies on TIDS. The cameras experienced numerous technical limitations that negatively influenced the human factors assessment of them. This report includes the percentages of human factors and technical success criteria that passed at DFW-2.
Summary
Staffed NextGen Towers (SNT), a research concept being developed and validated by the Federal Aviation Administration (FAA), is a paradigm shift to providing air traffic control services primarily via surface surveillance approved for operational use by controllers instead of the existing out-the-window (OTW) view at high-density airports. SNT was exercised...
READ MORE
Photonic ADC: overcoming the bottleneck of electronic jitter
February 13, 2012
Journal Article
Published in:
Opt. Express, Vol. 20, No. 4, 13 February 2012, pp. 4454-4469.
Topic:
R&D area:
Summary
Accurate conversion of wideband multi-GHz analog signals into the digital domain has long been a target of analog-to-digital converter (ADC) developers, driven by applications in radar systems, software radio, medical imaging, and communication systems. Aperture jitter has been a major bottleneck on the way towards higher speeds and better accuracy. Photonic ADCs, which perform sampling using ultra-stable optical pulse trains generated by mode-locked lasers, have been investigated for many years as a promising approach to overcome the jitter problem and bring ADC performance to new levels. This work demonstrates that the photonic approach can deliver on its promise by digitizing a 41 GHz signal with 7.0 effective bits using a photonic ADC built from discrete components. This accuracy corresponds to a timing jitter of 15 fs - a 4-5 times improvement over the performance of the best electronic ADCs which exist today. On the way towards an integrated photonic ADC, a silicon photonic chip with core photonic components was fabricated and used to digitize a 10 GHz signal with 3.5 effective bits. In these experiments, two wavelength channels were implemented, providing the overall sampling rate of 2.1 GSa/s. To show that photonic ADCs with larger channel counts are possible, a dual 20- channel silicon filter bank has been demonstrated.
Summary
Accurate conversion of wideband multi-GHz analog signals into the digital domain has long been a target of analog-to-digital converter (ADC) developers, driven by applications in radar systems, software radio, medical imaging, and communication systems. Aperture jitter has been a major bottleneck on the way towards higher speeds and better accuracy...
READ MORE
Diffractive beam combining of a 2.5-kW fiber laser array
January 29, 2012
Conference Paper
Published in:
ASSP 2012, Advanced Solid-State Photonics, 29 January - 1 February 2012.
Summary
Five 500-W fiber amplifiers were coherently combined with 79% efficiency using a diffractive optical element (DOE) combiner, generating a single beam whose M^2 = 1.1 beam quality exceeded that of the inputs.
Summary
Five 500-W fiber amplifiers were coherently combined with 79% efficiency using a diffractive optical element (DOE) combiner, generating a single beam whose M^2 = 1.1 beam quality exceeded that of the inputs.
READ MORE
Creating a cyber moving target for critical infrastructure applications using platform diversity
January 28, 2012
Journal Article
Published in:
Int. J. of Critical Infrastructure Protection, Vol. 5, No. 1, March 2012, pp. 30-39.
Topic:
R&D area:
R&D group:
Summary
Despite the significant effort that often goes into securing critical infrastructure assets, many systems remain vulnerable to advanced, targeted cyber attacks. This paper describes the design and implementation of the Trusted Dynamic Logical Heterogeneity System (TALENT), a framework for live-migrating critical infrastructure applications across heterogeneous platforms. TALENT permits a running critical application to change its hardware platform and operating system, thus providing cyber survivability through platform diversity. TALENT uses containers (operating-system-level virtualization) and a portable checkpoint compiler to create a virtual execution environment and to migrate a running application across different platforms while preserving the state of the application (execution state, open files and network connections). TALENT is designed to support general applications written in the C programming language. By changing the platform on-the-fly, TALENT creates a cyber moving target and significantly raises the bar for a successful attack against a critical application. Experiments demonstrate that a complete migration can be completed within about one second.
Summary
Despite the significant effort that often goes into securing critical infrastructure assets, many systems remain vulnerable to advanced, targeted cyber attacks. This paper describes the design and implementation of the Trusted Dynamic Logical Heterogeneity System (TALENT), a framework for live-migrating critical infrastructure applications across heterogeneous platforms. TALENT permits a running...
READ MORE
Estimation of New York departure fix capacities in fair and convective weather
January 23, 2012
Conference Paper
Published in:
3rd Aviation, Range, and Aerospace Meteorology, 23 January 2012.
Topic:
R&D area:
R&D group:
Summary
When convective weather impacts the New York Metro airspace, traffic managers may employ several tactics to mitigate weather impacts and maintain manageable and efficient flow of traffic to and from the airports. These tactics, which include maneuvering individual flights through weather, merging and redirecting traffic flows to avoid storms, and rerouting traffic from blocked routes onto unimpacted or less-impacted routes, all affect the capacity of the affected airspace resources (departure fixes, routes, or gates). Furthermore, the location of the weather impacts can have a great influence on the amount of leeway that traffic managers have in applying these tactics. In New York, departure fixes, the gateways to en route airspace where departure traffic from several metroplex airports are merged onto en route airways, are particularly critical. When congestion (volume of traffic in excess of capacity) occurs near departure fixes as a result of weather impacts, traffic managers must resort to airborne holding or unplanned departure stops to quickly reduce traffic over the fix to manageable levels. Nonetheless, when convective weather impacts densely packed and busy metroplex airspaces, it is inevitable that traffic will need to use impacted departure fixes and routes to keep delays in check. For this reason, predictions of the weather-impacted capacity of critical airspace resources like departure fixes that are based in the reality of commonly used impact mitigation tactics, are needed to help traffic managers anticipate and avoid disruptive congestion at weather-impacted departure fixes. The Route Availability Planning Tool (RAPT) is a departure management decision support tool that has been used in the New York operations since 2003. It predicts the weather impact on departure fixes and routes based on departure times. RAPT assigns a departure status (RED, YELLOW, or GREEN) to individual departure routes based on the departure time, the predicted severity of the convective weather that will impact the route, the likelihood that a pilot will deviate to avoid the weather along the route, and the operational sensitivity to deviations in the departure airspace that the route traverses. These blockages assist traffic managers in prompt route reopening of routes closed by convective weather impacts, as well as providing situational awareness for impeding impacts on routes. RAPT also identifies the location of weather impacts along the departure route. This paper presents an analysis of observed fair weather and convective weather impacted throughput on New York departure fixes. RAPT departure status and impact location are used to characterize the severity of departure fix weather impacts, and weather-impacted fix capacity ranges are estimated as a function of RAPT impacts. The use of traffic flow merging is identified, and weather impacted capacity ranges for commonly used merged flows are also estimated.
Summary
When convective weather impacts the New York Metro airspace, traffic managers may employ several tactics to mitigate weather impacts and maintain manageable and efficient flow of traffic to and from the airports. These tactics, which include maneuvering individual flights through weather, merging and redirecting traffic flows to avoid storms, and...
READ MORE
A tree-based ensemble method of the prediction and uncertainty quantification of aircraft landing times
January 22, 2012
Conference Paper
Published in:
10th Conf. on Artificial and Computational Intelligence, 22 January 2012.
Topic:
R&D area:
R&D group:
Summary
Accurate aircraft landing time predictions provide situational awareness for air traffic controllers, enable decision support algorithms and gate management planning. This paper presents a new approach for estimation of landing times using a tree-based ensemble method, namely Quantile Regression Forests. This method is suitable for real-time applications, provides robust and accurate predictions of landing times, and yields prediction intervals for individual flights, which provide a natural way of quantifying uncertainty. The approach was tested for arrivals at Dallas/Fort Worth International Airport over a range of days with a variety of operational conditions.
Summary
Accurate aircraft landing time predictions provide situational awareness for air traffic controllers, enable decision support algorithms and gate management planning. This paper presents a new approach for estimation of landing times using a tree-based ensemble method, namely Quantile Regression Forests. This method is suitable for real-time applications, provides robust and...
READ MORE
Fundamental Questions in the Analysis of Large Graphs
January 1, 2012
Book Chapter
Published in:
Graph Algorithms in the Language of Linear Algebra, pp. 353-357.
Topic:
R&D area:
R&D group:
Summary
Graphs are a general approach for representing information that spans the widest possible range of computing applications. They are particularly important to computational biology, web search, and knowledge discovery. As the sizes of graphs increase, the need to apply advanced mathematical and computational techniques to solve these problems is growing dramatically. Examining the mathematical and computational foundations of the analysis of large graphs generally leads to more questions than answers. This book concludes with a discussion of some of these questions.
Summary
Graphs are a general approach for representing information that spans the widest possible range of computing applications. They are particularly important to computational biology, web search, and knowledge discovery. As the sizes of graphs increase, the need to apply advanced mathematical and computational techniques to solve these problems is growing...
READ MORE
Subgraph Detection
January 1, 2012
Book Chapter
Published in:
Graph Algorithms in the Language of Linear Algebra, pp. 115-133.
Topic:
R&D area:
R&D group:
Summary
Detecting subgraphs of interest in larger graphs is the goal of many graph analysis techniques. The basis of detection theory is computing the probability of a “foreground” with respect to a model of the “background” data. Hidden Markov Models represent one possible foreground model for patterns of interaction in a graph. Likewise, Kronecker graphs are one possible model for power law background graphs. Combining these models allows estimates of the signal to noise ratio, probability of detection, and probability of false alarm for different classes of vertices in the foreground. These estimates can then be used to construct filters for computing the probability that a background graph contains a particular foreground graph. This approach is applied to the problem of detecting a partially labeled tree graph in a power law background graph. One feature of this method is the ability to a priori estimate the number of vertices that will be detected via the filter.
Summary
Detecting subgraphs of interest in larger graphs is the goal of many graph analysis techniques. The basis of detection theory is computing the probability of a “foreground” with respect to a model of the “background” data. Hidden Markov Models represent one possible foreground model for patterns of interaction in a...
READ MORE
Linear algebraic notation and definitions
January 1, 2012
Book Chapter
Published in:
Graph Algorithms in the Language of Linear Algebra, pp. 13-18.
Topic:
R&D area:
R&D group:
Summary
This chapter presents notation, definitions, and conventions for graphs, matrices, arrays, and operations upon them.
Summary
This chapter presents notation, definitions, and conventions for graphs, matrices, arrays, and operations upon them.
READ MORE
A knowledge-based operator for a genetic algorithm which optimizes the distribution of sparse matrix data
January 1, 2012
Book Chapter
Published in:
Parallel Architectures and Bioinspired Algorithms
Topic:
R&D area:
R&D group:
Summary
We present the Hogs and Slackers genetic algorithm (GA) which addresses the problem of improving the parallelization efficiency of sparse matrix computations by optimally distributing blocks of matrices data. The performance of a distribution is sensitive to the non-zero patterns in the data, the algorithm, and the hardware architecture. In a candidate distributions the Hogs and Slackers GA identifies processors with many operations – hogs, and processors with fewer operations – slackers. Its intelligent operation-balancing mutation operator then swaps data blocks between hogs and slackers to explore a new data distribution.We show that the Hogs and Slackers GA performs better than a baseline GA. We demonstrate Hogs and Slackers GA’s optimization capability with an architecture study of varied network and memory bandwidth and latency.
Summary
We present the Hogs and Slackers genetic algorithm (GA) which addresses the problem of improving the parallelization efficiency of sparse matrix computations by optimally distributing blocks of matrices data. The performance of a distribution is sensitive to the non-zero patterns in the data, the algorithm, and the hardware architecture. In...
READ MORE