Publications
Wind-shear detection performance study for multifunction phased array radar (MPAR) risk reduction
June 12, 2013
Project Report
Published in:
MIT Lincoln Laboratory Report ATC-409
Summary
Multifunction phased array radars (MPARs) of the future that may replace the current terminal wind-shear detection systems will need to meet the Federal Aviation Administration's (FAA) detection requirements. Detection performance issues related to on-airport siting of MPAR, its broader antenna beamwidth relative to the TDWR, and the change in operational frequency from C band to S band are analyzed. Results from the 2012 MPAR Wind-Shear Experiment (WSE) are presented, with microburst and gust-front detection statistics for the Oklahoma City TDWR and the National Weather Radar Testbed (NWRT) phased array radar, which are located 6 km apart. The NWRT has sensitivity and beamwidth similar to a conceptual terminal MPAR (TMPAR), which is a scaled-down version of a full-size MPAR. The microburst results show both the TDWR probability of detection (POD) and the estimated NWRT POD exceeding the 90% requirement. For gust fronts, however, the overall estimated NWRT POD was more than 10% lower than the TDWR POD. NWRT data is also used to demonstrate that rapid-scan phased array radar has the potential to enhance microburst prediction capability.
Summary
Multifunction phased array radars (MPARs) of the future that may replace the current terminal wind-shear detection systems will need to meet the Federal Aviation Administration's (FAA) detection requirements. Detection performance issues related to on-airport siting of MPAR, its broader antenna beamwidth relative to the TDWR, and the change in operational...
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Sector workload model for benefits analysis and convective weather capacity prediction
June 10, 2013
Conference Paper
Published in:
10th USA/Europe Air Traffic Management Research and Development Sem., ATM 2013, 10-13 June 2013.
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Summary
En route sector capacity is determined mainly by controller workload. The operational capacity model used by the Federal Aviation Administration (FAA) provides traffic alert thresholds based entirely on hand-off workload. Its estimates are accurate for most sectors. However, it tends to over-estimate capacity in both small and large sectors because it does not account for conflicts and recurring tasks. Because of those omissions it cannot be used for accurate benefits analysis of workload-reduction initiatives, nor can it be extended to estimate capacity when hazardous weather increases the intensity of all workload types. We have previously reported on an improved model that accounts for all workload types and can be extended to handle hazardous weather. In this paper we present the results of a recent regression of that model using an extensive database of peak traffic counts for all United States en route sectors. The resulting fit quality confirms the workload basis of en route capacity. Because the model has excess degrees of freedom, the regression process returns multiple parameter combinations with nearly identical sector capacities. We analyze the impact of this ambiguity when using the model to quantify the benefits of workload reduction proposals. We also describe recent modifications to the weather-impacted version of the model to provide a more stable normalized capacity measure. We conclude with an illustration of its potential application to operational sector capacity forecasts in hazardous weather.
Summary
En route sector capacity is determined mainly by controller workload. The operational capacity model used by the Federal Aviation Administration (FAA) provides traffic alert thresholds based entirely on hand-off workload. Its estimates are accurate for most sectors. However, it tends to over-estimate capacity in both small and large sectors because...
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An assessment of the operational utility of a GOES lightning mapping sensor
May 28, 2013
Project Report
Published in:
MIT Lincoln Laboratory Report NOAA-18A
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Summary
This report evaluates the incremental operational benefits of a proposed Lightning Mapping Sensor (LMS) for NOAA's Geostationary Operational Environmental Satellites (GOES). If deployed, LMS would provide continuous, real-time surveillance of total lightning activity over large portions of the North and South American continents and surrounding oceans. In contrast to the current National Lightning Detection Network, LMS would monitor total lightning activity, including the dominant intracloud component which is estimated to occur with order of magnitude greater frequency than cloud-to-ground lightning and may occur ten minutes or more in advance of a storm's first ground flash.
Summary
This report evaluates the incremental operational benefits of a proposed Lightning Mapping Sensor (LMS) for NOAA's Geostationary Operational Environmental Satellites (GOES). If deployed, LMS would provide continuous, real-time surveillance of total lightning activity over large portions of the North and South American continents and surrounding oceans. In contrast to the...
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Optimized airborne collision avoidance in mixed equipage environments
May 22, 2013
Project Report
Published in:
MIT Lincoln Laboratory Report ATC-408
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Summary
Developing robust collision avoidance logic that reliably prevents collision without excessive alerting is challenging due to sensor error and uncertainty in the future paths of the aircraft. Over the past few years, research has focused on the use of a computational method known as dynamic programming for producing an optimized decision logic for airborne collision avoidance. This report focuses on recent research on coordination, interoperability, and multiple-threat encounters. The methodology presented in this report results in logic that is safer and performs better than legacy TCAS. Modeling and simulation indicate that the proposed methodology can bring significant benefit to the current airspace and can support the need for safe, non-disruptive collision protection as the airspace continues to evolve.
Summary
Developing robust collision avoidance logic that reliably prevents collision without excessive alerting is challenging due to sensor error and uncertainty in the future paths of the aircraft. Over the past few years, research has focused on the use of a computational method known as dynamic programming for producing an optimized...
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Airport surface traffic management decision support - perspectives based on tower flight data manager prototype
May 20, 2013
Project Report
Published in:
MIT Lincoln Laboratory Report ATC-398
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This report describes accomplishments and insights gathererd during the development of decision support tools as part of the Terminal Flight Data Manager (TFDM) program. This work was performed by MIT Lincoln Laboratory and sponsored by the Federal Aviation Administration (FAA). The TFDM program integrated flight data, aircraft surveillance, information on weather and traffic flow constraints, and other data required to optimize airport conguration and arrival/departure management functions. The prototype has been evaluated in both human-in-the-loop simulations, and during operational tests at Dallas/Fort Worth (DFW) International Airport. In parallel, the Laboratory estimated future national operational benefits for TFDM decision support functions, using analysis and performance data gathered from major airports in the US. This analysis indicated that the greatest potential operational benefits would come from decision support tools that facilitate: i) managing runway queues and sequences, ii) tactical management of flight routes and times, impacted by weather and traffic constraints, and iii) managing airport configuration changes. Evaluation of TFDM prototype decision support functions in each of these areas provided valuable insights relative to the maturity of current capabilities and research needed to close performance gaps.
Summary
This report describes accomplishments and insights gathererd during the development of decision support tools as part of the Terminal Flight Data Manager (TFDM) program. This work was performed by MIT Lincoln Laboratory and sponsored by the Federal Aviation Administration (FAA). The TFDM program integrated flight data, aircraft surveillance, information on...
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Risk-based modeling to support NextGen concept assessment and validation
March 1, 2013
Project Report
Published in:
MIT Lincoln Laboratory Report ATC-405
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This report provides a brief review of major risk-based modeling (RBM) approaches, with particular emphasis on how these tools can be applied during initial Next Generation Air Transportation System (NextGen) concept development and how their use can be validated. Effective safety analysis should play a role even during a new system's concept definition and development. Elements of NextGen are currently progressing through these early phases. NextGen will increasingly rely on integrating multiple systems and information together to enable improved efficiency, safety, and reduced environmental impact. Ensuring that such complex interconnected systems are developed to meet safety goals requires corresponding advances in RBM and safety assessment approaches. This report does not cover the more detailed safety analyses that must be applied to mature system concepts. Rather, the focus is on approaches for hazard identification, scoping, and coarse risk estimation for systems in the early conceptual development stage, when details on the design and operation of the system have yet to be resolved. Risk models applied is this constrained context cannot be expected to provide the same complete, quantitative results as they do for mature systems. Following a review of prior models, this report continues with recommendations for RBM development, application, validation, and coordination between NextGen efforts. Also, a discussion on safety and concept development is provided.
Summary
This report provides a brief review of major risk-based modeling (RBM) approaches, with particular emphasis on how these tools can be applied during initial Next Generation Air Transportation System (NextGen) concept development and how their use can be validated. Effective safety analysis should play a role even during a new...
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Wind information requirements for NextGen applications phase 1: 4D-trajectory based operations (4D-TBO)
February 20, 2013
Project Report
Published in:
MIT Lincoln Laboratory Report ATC-399
Summary
Accurate wind information is required to support some of the key applications envisioned for future air traffic concepts. A Wind Information Analysis Framework has been developed to assess wind information needs for different applications. The framework is described and then applied in a Four-Dimensional Trajectory Based Operations (4D-TBO) application using simplified versions of the framework's elements to demonstrate its utility. Realistic ranges of wind information accuracy in terms of wind forecast and Flight Management System wind representation errors are studied. Their impacts on 4D-TBO performance in terms of Required Time of Arrival compliance and fuel burn are presented. Interpretations of the findings to give insights on wind information requirements are provided, together with an outline of the planned next phase of the study to further refine the outputs.
Summary
Accurate wind information is required to support some of the key applications envisioned for future air traffic concepts. A Wind Information Analysis Framework has been developed to assess wind information needs for different applications. The framework is described and then applied in a Four-Dimensional Trajectory Based Operations (4D-TBO) application using...
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Convective initiation forecasts through the use of machine learning methods
January 9, 2013
Conference Paper
Published in:
11th Conf. on Artificial and Computational Intelligence and its Applications to the Environmental Sciences, 9 January 2013.
Summary
Storm initiation is a very challenging aspect of nowcasting. Rapidly forming storms that appear in areas of little to no pre-existing convection can pose a danger to aircraft, and have the potential to cause unforeseen delays in the national airspace system (NAS). As such, detection and prediction of the initial development of convective storms is critical to NAS operations and planning. The Corridor Integrated Weather System (CIWS) currently provides deterministic 0-2 hour storm forecasts over the NAS, and represents the 0-2 hour portion of the 0-8 hour deterministic CoSPA storm forecasts. CIWS includes a convective initiation (CI) module, however this module has difficulty initiating convection in areas of little or no pre-existing convection. In this study, we seek to improve the capabilities of the CI module using machine learning methods to detect regions of imminent convection and enhance the storm initiation to the 0-2 hour forecast. Improvements to the current CI detection capabilities will prove to be a benefit in the short term, as well in the longer term plans of the Federal Aviation Administration's (FAA) Next Generation Air Transportation System (NextGen). In order to improve the capabilities of the CI module in CIWS, data from a variety of sources are fused together to produce a forecast of CI. Data incorporated into the CI algorithm include: Satellite fields from NASA's Satellite Convective Analysis and Tracking (SATCAST), convective instability fields, and a collection of numerical models which includes NOAA's North America Rapid Refresh Ensemble Time Lag System (NARRE-TL), the Localized Aviation MOS Program (LAMP), Short Range Ensemble Forecasts (SREF), and High Resolution Rapid Refresh (HRRR) model forecasts. These fields are brought together in a machine learning framework to create a probabilistic model which is used to initiate new growth in the deterministic CIWS 0-2 hour forecast. A variety of machine learning classifiers, including logistic regression, neural networks, support vector machines, and random forests, are used to investigate which technique works best with the data available. The skill of this updated CI capability is being assessed over the summer of 2012 using multiple skill metrics including CSI, bias and fraction skill score.
Summary
Storm initiation is a very challenging aspect of nowcasting. Rapidly forming storms that appear in areas of little to no pre-existing convection can pose a danger to aircraft, and have the potential to cause unforeseen delays in the national airspace system (NAS). As such, detection and prediction of the initial...
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Tower Flight Data Manager benefits assessment: initial investment decision interim report
November 19, 2012
Project Report
Published in:
MIT Lincoln Laboratory Report ATC-394
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Summary
This document provides an overview of MIT Lincoln Laboratory's activities in support of the interim stage of the Initial Investment Decision benefits assessment for the Tower Flight Data Manager. It outlines the rationale for the focus areas, and the background, methodology, and scope in the focus areas of departure metering, sequence optimization, airport configuration optimization, and safety assessment. Estimates of the potential benefits enabled by TFDM deployment are presented for each of these areas for a subset of airports and conditions considered within the scope of the analyses. These benefits are monetized where possible. Recommendations for follow-on work, for example, to support future benefits assessment efforts for TFDM, are also discussed.
Summary
This document provides an overview of MIT Lincoln Laboratory's activities in support of the interim stage of the Initial Investment Decision benefits assessment for the Tower Flight Data Manager. It outlines the rationale for the focus areas, and the background, methodology, and scope in the focus areas of departure metering...
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Multifunction Phased Array Radar wind shear experiment
November 5, 2012
Conference Paper
Published in:
26th Conf. on Sever Local Storms, 5-8 November 2012.
Summary
Terminal Doppler Weather Radars (TDWRs) provide near-ground wind shear detection that is critical for aircraft safety at 46 airports across the United States. These systems are part of the larger network of 510 weather and aircraft surveillance radars owned and operated by government agencies in the continental United States. As the TDWR and other radar systems approach their engineering design life cycles, the Federal Aviation Administration (FAA), National Weather Service (NWS), and Department of Defense (DoD) are considering potential replacement systems (OFCM 2006; Weber et al. 2007). One option under consideration that would maintain the current airspace coverage is a replacement network of 334 Multifunction Phased Array Radars (MPARs) (Weber et al. 2007). The MPAR network described by Weber et al. (2007) would include two classes of systems: A high-resolution, full-scale version with an 8-m diameter antenna, and a lower-resolution terminal version with a 4-m diameter antenna, termed Terminal MPAR, or TMPAR. As the proposed TMPAR design has lower azimuthal beam resolution and less sensitivity than TDWRs, it is crucial to determine the impacts of that design on the detection of low-altitude wind shear. The design of the SPY-1A PAR, a research radar at the National Weather Radar Test Bed in Norman, Oklahoma (Zrnić et al. 2007), makes it a good proxy for examining the potential wind shear detection performance of the TMPAR. Therefore, in spring 2012, the National Oceanic and Atmospheric Administration (NOAA) National Severe Storms Laboratory organized and executed the MPAR Wind Shear Experiment (WSE) in collaboration with the FAA, NOAA's NWS Radar Operations Center, the University of Oklahoma Advanced Radar Research Center (OU ARRC), and the Massachusetts Institute of Technology Lincoln Laboratory (MIT LL). The primary objective of the MPAR WSE was to collect low-altitude observations with the SPY-1A PAR (hereafter, PAR) for comparison with observations from the nearby Oklahoma City (OKC) TDWR. Of particular interest is comparison of MIT LL wind shear detection algorithm performance using data from these two radars; this analysis is reported in Cho et al. (2013). Data were also collected from other radars in central Oklahoma to facilitate basic research on microbursts and other wind-producing storms. This paper provides an overview of the MPAR WSE and observed wind shear events.
Summary
Terminal Doppler Weather Radars (TDWRs) provide near-ground wind shear detection that is critical for aircraft safety at 46 airports across the United States. These systems are part of the larger network of 510 weather and aircraft surveillance radars owned and operated by government agencies in the continental United States. As...
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