Publications

Airport wind information is critical for ensuring safe aircraft operations and for managing runway configurations. Airports across the National Airspace System (NAS) are served by a wide variety of wind sensing systems that have been deployed over many decades. This analysis presents a survey of existing systems and user requirements, identifies potential shortfalls, and offers recommendations for improvements to support the long-term goals of the FAA NextGen system.

MIT Lincoln Laboratory personnel conducted field observations of the Consolidated Storm Prediction for Aviation (CoSPA) 8-hr deterministic convective forecast, and the decision support tool, Traffic Flow Impact (TFI), from 6 June to 31 October 2017. Four field observations were performed during the demonstration period.

A companion Lincoln Laboratory report (ATC-437, “Preliminary Weather Information Gaps for UAS Operations”) identified initial gaps in the ability of current weather products to meet the needs of UAS operations. Building off of that work, this report summarizes the development of a proposed initial roadmap for research to fill the gaps that were identified.

Unmanned Aircraft System (UAS) operations in the National Airspace System (NAS) are rapidly increasing. For example, 2017 has seen dramatically increased low altitude UAS usage for disaster relief and by first responders. The ability to carry out these operations, however, can be strongly impacted by adverse weather conditions. This report documents a preliminary quick-look identification and assessment of gaps in current weather decision support for UAS operations.

NextGen applications with time-based control elements, such as required time of arrival (RTA) at a meter fix under 4D trajectory-based operations (4D-TBO)/time of arrival control (TOAC) procedures or assigned spacing goal between aircraft under Interval Management (IM) procedures, are subject to the quality of the atmospheric forecast utilized by participating aircraft. The work described in this report summarizes the major activities conducted in the current phase of this program which builds upon prior work.

The 2016 Storm Prediction for Aviation (CoSPA) Demonstration was conducted from 1 June to 31 October 2016. As part of the demonstration, Federal Aviation Administration (FAA) facilities and commercial airlines were visited by MIT Lincoln Laboratory (MIT LL) observers, including initial training visits. Targeted field observations were conducted to gather information on how the CoSPA weather forecast was used in operations, to obtain feedback on new capabilities, and to collect comments for improvement.

Many NextGen applications depend on access to high accuracy wind data due to time-based control elements, such as required time of arrival at a meter fix under 4D-Trajectory-Based Operations/Time of Arrival Control procedures or compliance to an assigned spacing goal between aircraft under Interval Management procedures. The work described in this report summarizes the activities conducted in FY15, which builds upon prior work.

In this paper, we consider the task of language identification in the context of mismatch conditions. Specifically, we address the issue of using unlabeled data in the domain of interest to improve the performance of a state-of-the-art system.

Today's infrastructure as a service (IaaS) cloud environments rely upon full trust in the provider to secure applications and data. In this paper we introduce keylime, a scalable trusted cloud key management system. Keylime provides an end-to-end solution for both bootstrapping hardware rooted cryptographic identities for IaaS nodes and for system integrity monitoring of those nodes via periodic attestation.

This work monetizes the environmental benefits of Terminal Flight Data Manager (TFDM) capabilities which reduce fuel burn and gaseous emissions, and in turn reduce climate change and air quality effects.