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Use of a high-resolution deterministic weather forecast for strategic air traffic management decision support

January 14, 2011
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Conference Paper
Author:
Michael L. Robinson
…
Published in:
91st American Meteorological Society Annual Meeting, 22-27 January 2011.
Topic:
aviation weather
R&D area:
R&D group:

Summary

One of the most significant air traffic challenges is managing the National Airspace System (NAS) in a manner that optimizes efficiency and mitigates avoidable delay, while maintaining safety, when convective weather is present. To do this, aviation planners seek to develop strategic air traffic management (ATM) plans and initiatives that anticipate weather constraints 2-8 hours in the future and identify options and alternatives for efficient operations during the off-nominal NAS conditions. In support of strategic planning, traffic managers currently conduct bi-hourly Strategic Planning Telcons (SPTs) and devise weather impact mitigations plans using the human-generated Collaborative Convective Forecast Product (CCFP). However, most operational decision-makers agree that the quasi-deterministic CCFP "polygons" (accompanied by a "low/high" forecast confidence rating) lack the granularity and temporal resolution to adequately support efficient strategic ATM plans and decisions. Moreover, traffic managers also assert that probabilistic forecasts of convective weather likelihood, while helpful in highlighting regions of possible airspace disruptions, generally lack the ability to resolve specific weather characteristics pertinent to strategic planning. MIT Lincoln Laboratory, NCAR Research Applications Laboratory, and NOAA Earth Systems Research Laboratory (ESRL) have collaborated to develop a high-resolution, rapidly updating 0-8 hour deterministic precipitation and echo tops forecast, known as CoSPA, to aid operational decision-makers in developing strategic plans for weather impact mitigation. In the summer of 2010, a comprehensive field study was conducted to assess potential benefits and the operational performance of CoSPA in the context of strategic ATM planning. The data were gathered by simultaneous real-time observations of I5 FAA and airline operations facilities during 15 convective weather impact days affecting the Northern Plains, Great Lakes, and East Coast regions of the NAS. CoSPA field evaluation results will be presented to demonstrate the various ways aviation planners have utilized the increased spatial and temporal resolution of CoSPA - the ability of CoSPA to resolve storm structure and refine forecasts with high update rates - to make more detailed assessments of potential weather impacts and to determine the subsequent need for airspace management initiatives. Results will also be presented that highlight CoSPA enhancement needs, primarily related to forecast uncertainty, that would improve the operational effectiveness of CoSPA-derived weather impact mitigation plans. Finally, opportunities to translate CoSPA deterministic forecasts into integrated weather-ATM decision support for specific strategic planning tasks will be discussed
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Summary

One of the most significant air traffic challenges is managing the National Airspace System (NAS) in a manner that optimizes efficiency and mitigates avoidable delay, while maintaining safety, when convective weather is present. To do this, aviation planners seek to develop strategic air traffic management (ATM) plans and initiatives that...

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Use of a high-resolution deterministic weather forecast for strategic air traffic management decision support

Aircraft collision avoidance using Monte Carlo real-time belief space search

January 13, 2011
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Journal Article
Author:
Travis Wolf
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Published in:
J. Intell. Robot. Syst., Vol. 64, No. 2, 2011, pp. 277-98.
Topic:
collision avoidance
R&D area:
R&D group:

Summary

The aircraft collision avoidance problem can be formulated using a decision-theoretic planning framework where the optimal behavior requires balancing the competing objectives of avoiding collision and adhering to a flight plan. Due to noise in the sensor measurements and the stochasticity of intruder state trajectories, a natural representation of the problem is as a partially-observable Markov decision process (POMDP), where the underlying state of the system is Markovian and the observations depend probabilistically on the state. Many algorithms for finding approximate solutions to POMDPs exist in the literature, but they typically require discretization of the state and observation spaces. This paper investigates the introduction of a sample-based representation of state uncertainty to an existing algorithm called Real-Time Belief Space Search (RTBSS), which leverages branch-and-bound pruning to make searching the belief space for the optimal action more efficient. The resulting algorithm, called Monte Carlo Real-Time Belief Space Search (MC-RTBSS), is demonstrated on encounter scenarios in simulation using a beacon-based surveillance system and a probabilistic intruder model derived from recorded radar data.
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Summary

The aircraft collision avoidance problem can be formulated using a decision-theoretic planning framework where the optimal behavior requires balancing the competing objectives of avoiding collision and adhering to a flight plan. Due to noise in the sensor measurements and the stochasticity of intruder state trajectories, a natural representation of the...

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Aircraft collision avoidance using Monte Carlo real-time belief space search

Robust airborne collision avoidance through dynamic programming

January 3, 2011
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Project Report
Author:
Mykel J. Kochenderfer
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Published in:
MIT Lincoln Laboratory Report ATC-371
Topic:
collision avoidance
R&D area:
R&D group:

Summary

The Traffic Alert and Collision Avoidance System (TCAS) uses an on-board beacon radar to monitor the local air traffic and logic to determine when to alert pilots to potential conflict. The current TCAS logic was the result of many years of development and involved the careful engineering of many heuristic rules specified in pseudocode. Unfortunately, due to the complexity of the logic, it is difficult to revise the pseudocode to accommodate the evolution of the airspace and the introduction of new technologies and procedures. This report summarizes recent advances in computational techniques for automatically deriving the optimal logic with respect to a probabilistic model and a set of performance metrics. Simulations demonstrate how this new approach results in logic that significantly outperforms TCAS according to the standard safety and operational performance metrics.
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Summary

The Traffic Alert and Collision Avoidance System (TCAS) uses an on-board beacon radar to monitor the local air traffic and logic to determine when to alert pilots to potential conflict. The current TCAS logic was the result of many years of development and involved the careful engineering of many heuristic...

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Robust airborne collision avoidance through dynamic programming

USSS-MITLL 2010 human assisted speaker recognition

January 2, 2011
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Conference Paper
Author:
Reva Schwartz
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Published in:
Proc. IEEE ICASSP, 26 May 2011, pp. 5904-7.
Topic:
biometrics
R&D area:
R&D group:

Summary

The United States Secret Service (USSS) teamed with MIT Lincoln Laboratory (MIT/LL) in the US National Institute of Standards and Technology's 2010 Speaker Recognition Evaluation of Human Assisted Speaker Recognition (HASR). We describe our qualitative and automatic speaker comparison processes and our fusion of these processes, which are adapted from USSS casework. The USSS-MIT/LL 2010 HASR results are presented. We also present post-evaluation results. The results are encouraging within the resolving power of the evaluation, which was limited to enable reasonable levels of human effort. Future ideas and efforts are discussed, including new features and capitalizing on naive listeners.
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Summary

The United States Secret Service (USSS) teamed with MIT Lincoln Laboratory (MIT/LL) in the US National Institute of Standards and Technology's 2010 Speaker Recognition Evaluation of Human Assisted Speaker Recognition (HASR). We describe our qualitative and automatic speaker comparison processes and our fusion of these processes, which are adapted from...

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USSS-MITLL 2010 human assisted speaker recognition

Information security for situational awareness in computer network defense

January 1, 2011
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Book Chapter
Author:
Uri Blumenthal
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Published in:
Chapter Six, Situational Awareness in Computer Network Defense: Principles, Methods, and Applications, 2011, pp. 86-103.
Topic:
cryptography
R&D area:
R&D group:

Summary

Situational awareness - the perception of "what's going on" - is crucial in every field of human endeavor, especially so in the cyber world where most of the protections afforded by physical time and distance are taken away. Since ancient times, military science emphasized the importance of preserving your awareness of the battlefield and at the same time preventing your adversary from learning the true situation for as long as possible. Today cyber is officially recognized as a contested military domain like air, land, and sea. Therefore situational awareness in computer networks will be under attacks of military strength and will require military-grade protection. This chapter describes the emerging threats for computer SA, and the potential avenues of defense against them.
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Summary

Situational awareness - the perception of "what's going on" - is crucial in every field of human endeavor, especially so in the cyber world where most of the protections afforded by physical time and distance are taken away. Since ancient times, military science emphasized the importance of preserving your awareness...

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Information security for situational awareness in computer network defense

Using United States government language proficiency standards for MT evaluation

January 1, 2011
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Book Chapter
Author:
Douglas A. Jones
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Published in:
Chapter 5.3.3 in Handbook of Natural Language Processing and Machine Translation, 2011, pp. 775-82.
Topic:
human language technology
R&D area:
R&D group:

Summary

The purpose of this section is to discuss a method of measuring the degree to which the essential meaning of the original text is communicated in the MT output. We view this test to be a measurement of the fundamental goal of MT; that is, to convey information accurately from one language to another. We conducted a series of experiments in which educated native readers of English responded to test questions about translated versions of texts originally written in Arabic and Chinese. We compared the results for those subjects using machine translations of the texts with those using professional reference translations. These comparisons serve as a baseline for determining the level of foreign language reading comprehension that can be achieved by a native English reader relying on machine translation technology. This also allows us to explore the relationship between the current, broadly accepted automatic measures of performance for machine translation and a test derived from the Defense Language Proficiency Test, which is used throughout the Defense Department for measuring foreign language proficiency. Our goal is to put MT system performance evaluation into terms that are meaningful to US government consumers of MT output.
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Summary

The purpose of this section is to discuss a method of measuring the degree to which the essential meaning of the original text is communicated in the MT output. We view this test to be a measurement of the fundamental goal of MT; that is, to convey information accurately from...

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Using United States government language proficiency standards for MT evaluation

Topic identification

January 1, 2011
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Book Chapter
Author:
Timothy J. Hazen
Published in:
Chapter 12, Spoken Language Understanding: Systems for Extracting from Speech, Gokhan Tur and Renato De Mori, eds., 2011, pp. 319-356.
Topic:
topic identification
R&D area:
R&D group:

Summary

In this chapter we discuss the problem of identifying the underlying topics beings discussed in spoken audio recordings. We focus primarily on the issues related to supervised topic classification or detection tasks using labeled training data, but we also discuss approaches for other related tasks including novel topic detection and unsupervised topic clustering. The chapter provides an overview of the common tasks and data sets, evaluation metrics, and algorithms most commonly used in this area of study.
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Summary

In this chapter we discuss the problem of identifying the underlying topics beings discussed in spoken audio recordings. We focus primarily on the issues related to supervised topic classification or detection tasks using labeled training data, but we also discuss approaches for other related tasks including novel topic detection and...

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Topic identification

MIT Lincoln Laboratory TCAS surveillance performance

December 28, 2010
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Project Report
Author:
Charles E. Rose
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Published in:
MIT Lincoln Laboratory Report ATC-370
Topic:
collision avoidance
R&D area:
R&D group:

Summary

The Traffic Alert and Collision Avoidance System (TCAS) Version 7 surveillance requirements were developed in the mid-1990s with the use of limited radar data. Recently, a more comprehensive radar data source has become available, enabling a thorough analysis of TCAS surveillance performance throughouth the National Airspace System (NAS). This paper characterizes six high traffic terminal environments over three months. A busy one hour period was selected from each location for density and equipage measurements. This paper then describes the use of a high fidelity simulation to characterize TCAS surveillance performance in the isx locations. Transponder utilization due to TCAS and TCAS surveillance range are compared with the design requirements, including interference limiting specifications. The effect of TCAS surveillance activity on Air Traffic Control (ATC) ground radar performance is also investigated. Results indicate that the surveillance algorithms perform as intended and that TCAS has a minimal impact on ground radar. Areas of concern are noted for future investigation.
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Summary

The Traffic Alert and Collision Avoidance System (TCAS) Version 7 surveillance requirements were developed in the mid-1990s with the use of limited radar data. Recently, a more comprehensive radar data source has become available, enabling a thorough analysis of TCAS surveillance performance throughouth the National Airspace System (NAS). This paper...

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MIT Lincoln Laboratory TCAS surveillance performance

Direct and latent modeling techniques for computing spoken document similarity

December 12, 2010
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Conference Paper
Author:
Timothy J. Hazen
Published in:
SLT 2010, IEEE Workshop on Spoken Language Technology, 12-15 December 2010.
Topic:
topic identification
R&D area:
R&D group:

Summary

Document similarity measures are required for a variety of data organization and retrieval tasks including document clustering, document link detection, and query-by-example document retrieval. In this paper we examine existing and novel document similarity measures for use with spoken document collections processed with automatic speech recognition (ASR) technology. We compare direct vector space approaches using the cosine similarity measure applied to feature vectors constructed with various forms of term frequency inverse document frequency (TF-IDF) normalization against latent topic modeling approaches based on latent Dirichlet allocation (LDA). In document link detection experiments on the Fisher Corpus, we find that an approach that applies bagging to models derived from LDA substantially outperforms the direct vector space approach.
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Summary

Document similarity measures are required for a variety of data organization and retrieval tasks including document clustering, document link detection, and query-by-example document retrieval. In this paper we examine existing and novel document similarity measures for use with spoken document collections processed with automatic speech recognition (ASR) technology. We compare...

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Direct and latent modeling techniques for computing spoken document similarity

Subgraph detection using eigenvector L1 norms

December 6, 2010
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Conference Paper
Author:
Benjamin A. Miller
…
Published in:
23rd Int. Conf. on Neural Info. Process. Syst., NIPS, 6-9 December 2010, pp. 1633-41.
Topic:
signal processing
R&D area:
R&D group:

Summary

When working with network datasets, the theoretical framework of detection theory for Euclidean vector spaces no longer applies. Nevertheless, it is desirable to determine the detectability of small, anomalous graphs embedded into background networks with known statistical properties. Casting the problem of subgraph detection in a signal processing context, this article provides a framework and empirical results that elucidate a "detection theory" for graph-valued data. Its focus is the detection of anomalies in unweighted, undirected graphs through L1 properties of the eigenvectors of the graph's so-called modularity matrix. This metric is observed to have relatively low variance for certain categories of randomly-generated graphs, and to reveal the presence of an anomalous subgraph with reasonable reliability when the anomaly is not well-correlated with stronger portions of the background graph. An analysis of subgraphs in real network datasets confirms the efficacy of this approach.
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Summary

When working with network datasets, the theoretical framework of detection theory for Euclidean vector spaces no longer applies. Nevertheless, it is desirable to determine the detectability of small, anomalous graphs embedded into background networks with known statistical properties. Casting the problem of subgraph detection in a signal processing context, this...

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Subgraph detection using eigenvector L1 norms
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