Publications
Machine intelligent gust front algorithm for the Terminal Doppler Weather Radar (TDWR) and Integrated Terminal Weather System (ITWS)
November 13, 1996
Conference Paper
Published in:
Workshop on Wind Shear and Wind Shear Alert Systems, 13-15 November, 1996.
Summary
Thunderstorms often generate gust fronts that can have significant impact on airport operations. Unanticipated changes in wind speed and direction are of concern from an air traffic safety viewpoint (hazardous wind shear) as well as from an airport planning point of view (runway configuration). Automated gust front detection is viewed by FAA and the air traffic community as an important component of current and future hazardous weather detection systems including the Terminal Doppler Weather Radar (TDWR), ASR-9 with Weather Systems Processor (ASR-9 WSP), and the Integrated Terminal Weather Systems (ITWS) for which TDWR is a principal sensor. In cooperation with the FAA, Lincoln Laboratory has successfully developed and tested a real-time Machine Intelligent Gust Front Algorithm (MIGFA) for use with Doppler weather radars. This algorithm resulted from the successful fusion of two complementing technologies developed at Lincoln Laboratory: computer vision/machine intelligence techniques originally developed for automated target recognition, and automated product-oriented weather radar data processing. Using these techniques, a version of MIGFA designed for use with TDWR has demonstrated substantial improvement over the existing TDWR gust front algorithm, detecting more and greater extents of gust fronts with fewer false alarms. MIGFA is slated to eventually replace the existing TDWR gust front algorithm and will be used as the gust front algorithm for the planned ITWS and ASR-9 WSP systems. A brief overview of techniques used by MIGFA to identify and track gust fronts will bre presented in this paper. More details, along with recent detection performance results, can be obtained from prior publications. However, detection and tracking of a gust front is only part of the task. Once the location of a gust front has been determined, the associated wind shear estimate and wind shift forecast must be computed. Several issues arises. For example, a gust front can be tens of kilometers in length, with outflow strength and contrasting environmental winds varying considerably along its length. Where along the front should the wind shear analysis be performed? Also, for airport planning purposes, air traffic controllers and managers need to plan runway configuration based on winds that may change suddenly when a gust front moves over the airport. Depending on the nature of the gust front, some of these winds are relatively transient while others are more persistent. How should the wind shift advisory produced by the algorithm take this into account? MIGFA uses a consensus derived from a variety of estimation techniques as a robust means of generating wind shear and wind shift estimates for detected gust fronts. These techniques, and some of their limitations, are discussed. Results of comparisons of MIGFA-generated wind shear and wind shift reports against observations are also presented. The paper concludes by outlining planned enhancements to incorporate additional information available under ITWS that should further improve the quality of MIGFA's wind shear and wind shift forecasts.
Summary
Thunderstorms often generate gust fronts that can have significant impact on airport operations. Unanticipated changes in wind speed and direction are of concern from an air traffic safety viewpoint (hazardous wind shear) as well as from an airport planning point of view (runway configuration). Automated gust front detection is viewed...
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ASR-9 Weather System Processor (WSP): wind shear algorithms performance assessment
May 7, 1996
Project Report
Published in:
MIT Lincoln Laboratory Report ATC-247
Summary
Lincoln Laboratory has developed a prototype Airport Surveillance Radar Weather Systems Processor (ASR-WSP) that has been used for field measurements and operational demonstrations since 1987. Measurements acquired with this prototype provide an extensive data base for development and validation of the algorithms the WSP uses to generate operational wind shear information for Air Traffic Controllers. This report addresses the performance of the current versions of the WSP's microburst and gust front wind shear detection algorithms on available data from each of the WSP's operational sites. Evaluation of the associated environmental characteristics (e.g., storm structure, radar ground clutter environment) allows for generalization of results of the other major U.S. climatic regimes where the production version of WSP will be deployed.
Summary
Lincoln Laboratory has developed a prototype Airport Surveillance Radar Weather Systems Processor (ASR-WSP) that has been used for field measurements and operational demonstrations since 1987. Measurements acquired with this prototype provide an extensive data base for development and validation of the algorithms the WSP uses to generate operational wind shear...
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Machine intelligent gust front detection for the Integrated Terminal Weather System (ITWS)
January 15, 1995
Conference Paper
Published in:
Sixth Conf. on Aviation Weather Systems, 15-20 January 1995, pp. 378-383.
Summary
The Integrated Terminal Weather System (ITWS), currently in development by the FAA, will produce a fully-automated integrated terminal weather information system to improve the safety, efficiency and capacity of terminal area aviation operations. The ITWS will acquire data from FAA and National Weather Service sensors as well as from aircraft in flight in the terminal area. The ITWS will provide products to Air Traffic personnel that are immediately usable without further meteorological interpretation. These products include current terminal area weather and short-term (0-30 minute) predictions of significant weather phenomena. The Terminal Doppler Weather Radar (TDWR) will serve as a principle sensor providing data to a number of the ITWS algorithms. One component of the ITWS will be an algorithm for detecting gust fronts and wind shifts. A gust front is the leading edge of a cold air outflow from a thunderstorm. The outflow, which is deflected at the ground, may propagate many miles ahead of the generating thunderstorm, and may persist as an outflow boundary long after the original storm has dissipated. Gust fronts can have a significant impact on air terminal operations since they often produce pronounced changes in wind speed and direction, forcing a change in active runway configuration and rerouting of aircraft within in the terminal airspace. In addition, wind shear, turbulence, and cross-winds along the frontal boundary pose significant safety hazards to departing and landing aircraft. Reliable detection and forecasting of gust fronts and wind shifts will both improve air safety and reduce costly delays. Lincoln Laboratory has developed an Initial Operational Capability (IOC) Machine Intelligent Gust Front Algorithm (MIGFA) for the ITWS which currently utilizes TDWR and LL WAS or ASOS anemometer data and makes use of new techniques of knowledge-based signal processing originally developed in the context of automatic target recognition [Verly, 1989]. Extensions to the IOC to incorporate additional sensor or product data available under the ITWS (e.g., NEXRAD, terminal winds) are currently under development. MIGFA was first developed for the Airport Surveillance Radar with Wind Shear Processor (ASR-9 WSP). Its design and performance have been documented in previous reports by the authors [Delanoy 1993a]. This paper focuses on the design of the more recently developed TDWR MIGFA and its extension and adaptation to the ITWS (a more detailed description of the TDWR MIGFA can be found in Troxel [1994]). An overview of the signal processing techniques used for detection and tracking is presented, as well as a brief discussion of the wind analysis methods used to arrive at the wind shift and wind shear estimates. Quantitative performance analyses using data collected during recent field testing in Orlando, FL and Memphis, TN are presented. Test results show that MIGFA substantially outperforms the gust front detection algorithm used in current TDWR systems [Hermes, 1993] (MIGFA is currently under consideration as an upgrade option for TDWR).
Summary
The Integrated Terminal Weather System (ITWS), currently in development by the FAA, will produce a fully-automated integrated terminal weather information system to improve the safety, efficiency and capacity of terminal area aviation operations. The ITWS will acquire data from FAA and National Weather Service sensors as well as from aircraft...
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Machine intelligent approach to automated gust front detection for Doppler weather radars
April 4, 1994
Conference Paper
Published in:
SPIE, Vol. 2220, Sensing, Imaging, and Vision for Control and Guidance of Aerospace Vehicles, 4-5 April 1994, pp. 182-193.
Summary
Automated gust front detection is an important component of the Airport Surveillance Radar with Wind Shear Processor (ASR-9 WSP) and Terminal Doppler Weather Radar (TDWR) systems being developed for airport terminal areas. Gust fronts produce signatures in Doppler radar imagery which are often weak, ambiguous, or conditional, making detection and continuous tracking of gust fronts challenging. Previous algorithms designed for these systems have provided only modest performance when compared against human observations. A Machine Intelligent Gust Front Algorithm (MIGFA) has been developed that makes use of two new techniques of knowledge-based signal processing originally developed in the context of automatic target recognition. The first of these, functional template correlation (FTC), is a generalized matched filter incorporating aspects of fuzzy set theory. The second technique is the use of "interest" as a medium for pixel-level data fusion. MIGFA was first developed for the ASR-9 WSP system. Its design and performance have been documented in a number of earlier reports. This paper focuses on the more recently developed TDWR MIGFA, describing the signal-processing techniques used and general algorithm design. A quantitative performance analysis using data collected during recent real-time testing of the TDWR MIGFA in Orlando, Florida is also presented. Results show that MIGFA substantially outperforms the gust front detection algorithm used in current TDWR systems.
Summary
Automated gust front detection is an important component of the Airport Surveillance Radar with Wind Shear Processor (ASR-9 WSP) and Terminal Doppler Weather Radar (TDWR) systems being developed for airport terminal areas. Gust fronts produce signatures in Doppler radar imagery which are often weak, ambiguous, or conditional, making detection and...
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Assessment of the weather detection capability of an Airport Surveillance Radar with solid-state transmitter
February 24, 1994
Project Report
Published in:
MIT Lincoln Laboratory Report ATC-209
Summary
The Federal Aviation Administration may acquire a new Airport Surveillance Radar-ASR-11-to replace aging ASR-7s and ASR-8s with a digital terminal radar consistent with Advanced Automation System requirements. A survey of the radar manufacturing industry suggests that a solid-state transmitter will likely be a component of this radar. The ASR-11 will feature a digital weather processing channel to measure and display six calibrated levels of precipitation reflectivity. An additional weather surveillance goal is the capability to support detection of low altitude wind shear phenomena. Use of a low peak power, solid-state transmitter and associated pulse compression technology raises several issues with respect to the capability of ASR-11 to meet these weather measurement objectives: 1. ASR-11 sensitivity will be degraded by approximately 16 to 20 dB relative to the Klystron-based ASR-9 at short range. This results because it is not feasible to use pulse compression waveforms to compensate for low peak transmitter power at short range; 2. Stability of a solid state ASR-11 transmitter may significantly exceed that of previous vacuum tube ASR transmitters. Increased clutter suppression capability associated with this enhanced stability could partially offset the reduced sensitivity of ASR-11 in meeting weather detection goals; 3. Pulse compression range sidelobes may resilt in "ghost" images of actual weather features, displaced in range by as much as 10 km. In some circumstances, these could result in false indications of operationally significant weather features such as thunderstorm-induced gust fronts. We examine these issues through straightforward analyses and simulation. Our assessment depends heavily on Doppler weather radar measurements of thunderstorms and associated wind shear phenomena obtained with Lincoln Laboratory's Terminal Doppler Weather Radar and ASR-9 testbeds. Overall, our assessment indicates that a solid-state transmitter ASR-11 can provide six-level weather reflectivity data with accuracy comparable to that of the ASR-9. Detection of low altitude wind shear phenomena using a solid-state transmitter ASR is more problematic. Reduced sensitivity at short range--the range interval of primary operational concern for an on-airport ASR--results in significant degradation of its capability to measure the reflectivity and Doppler velocity signatures associated with gust fronts and "dry" microbursts. This degradation is not offset by the enhanced clutter suppression capability provided by a solid-state transmitter. Although pulse compression range sidelobes do not appear to be a major issue if they are held to the -55 dB level, simulations are presented where range sidelobes result in a false gust front wind shear signature.
Summary
The Federal Aviation Administration may acquire a new Airport Surveillance Radar-ASR-11-to replace aging ASR-7s and ASR-8s with a digital terminal radar consistent with Advanced Automation System requirements. A survey of the radar manufacturing industry suggests that a solid-state transmitter will likely be a component of this radar. The ASR-11 will...
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Machine Intelligent Gust Front Algorithm
November 4, 1993
Project Report
Published in:
MIT Lincoln Laboratory Report ATC-196
Summary
The Federal Aviation Administration has sponsored research and development of algorithms for automatic gust front detection as part of a suite of hazardous weather detection capabilities for airports. These algorithms are intended for use with Doppler radar systems, specifically the Terminal Doppler Weather Radar (TDWR) and the Airport Surveillance Radar enhanced with a Wind Shear Processor (ASR-9 WSP). Although gust fronts are observable with fairly reliable signatures in TDWR data, existing gust front detection algorithms have achieved only modest levels of detection performance. For smaller airports not slated to receive a dedicated TDWR, the ASR-9 WSP will provide a less expensive wind shear detection capability. Gust front detection in ASR-9 SP data is an even more difficult problem, given the reduced sensitivity and less reliable Doppler measurements of this radar. A Machine Intelligent Gust Front Algorithm (MIGFA) has been constructed at Lincoln Laboratory that is a radical departure from previous design strategies. Incorporating knowledge-based, signal-processing techniques initially developed at Lincoln Laboratory for automatic target recognition, MIGFA uses meterological knowledge, spatial and temporal context, conditional data fusion, delayed thresholding, and pixel-level fusion of evidence to improve gust front detection performance significantly. In tests comparing MIGFA with an existing state-of-the-art algorithm applied to ASR-9 WSP data, MIGFA has substantially outperformed the older algorithm. In fact, by some measures, MIGFA has done as well or better than human interpreters of the same data. Operational testing of this version was done during 1992 in Orlando, Florida. The desing, test results, and performance evaluation of hte ASR-9 WSP version of MIGFA are presented in this report, which was prepared as part of the documentation package for the ASR-9 WSP gust front algorithm.
Summary
The Federal Aviation Administration has sponsored research and development of algorithms for automatic gust front detection as part of a suite of hazardous weather detection capabilities for airports. These algorithms are intended for use with Doppler radar systems, specifically the Terminal Doppler Weather Radar (TDWR) and the Airport Surveillance Radar...
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A machine intelligent gust front algorithm for Doppler weather radars
May 24, 1993
Conference Paper
Published in:
26th Int. Conf. on Radar Meteorology, 24-28 May 1993, pp. 654-656.
Summary
Gust fronts generated by thunderstorms can seriously affect the safety and efficiency of airport operations. Lincoln Laboratory, under contract with the Federal Aviation Administration (FAA), has had a significant role in the development of two Doppler radar systems that are capable of detecting low altitude wind shears, including gust fronts, in the airport terminal control area. These systems are the latest generation Airport Surveillance Radar, enhanced with a Wind Shear Processor (ASR-98 WSP) and the Terminal Doppler Weather Radar (TDWR).
Summary
Gust fronts generated by thunderstorms can seriously affect the safety and efficiency of airport operations. Lincoln Laboratory, under contract with the Federal Aviation Administration (FAA), has had a significant role in the development of two Doppler radar systems that are capable of detecting low altitude wind shears, including gust fronts...
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Automated gust front detection using knowledge-based signal processing
April 20, 1993
Conference Paper
Published in:
Proc. 1993 IEEE Natl. Radar Conf., 20-22 April 1993, pp. 150-155.
Summary
For reasons of aviation safety and airport operations efficiency, gust front detection and tracking is an important product of Doppler weather radars developed for use in airport terminal areas. Previous gust front algorithms, which have relied on the detection of one or two conspicuous signatures in Doppler radar imagery, have worked reasonably well in images generated by the high-resolution, pencil-beam Terminal Doppler Weather Radar (TDWR). The latest Airport Surveillance Radar, enhanced with a Wind Shear Processor (ASR-9 WSP), is being developed as a less expensive alternative weather radar. Although gust fronts are visible to human observers in ASR-9 WSP imagery, the lower sensitivity and less reliable Doppler measurements of this radar make automated gust front detection a much more challenging problem. Using machine intelligence and knowledge-based signal processing techniques developed in the context of automatic target recognition, a Machine Intelligent Gust Front Algorithm (MIGFA) has been constructed that is radically different from the previous algorithms. Developed initially for use with ASR-9 WSP data, MIGFA substantially outperforms a state-of-the-art gust front detection algorithm based on earlier approaches. These results also indirectly suggest that MIGFA performance may be nearly as good as human performance. Preliminary results of an operational test period (two months, approximately 15000 scans processed) are presented.
Summary
For reasons of aviation safety and airport operations efficiency, gust front detection and tracking is an important product of Doppler weather radars developed for use in airport terminal areas. Previous gust front algorithms, which have relied on the detection of one or two conspicuous signatures in Doppler radar imagery, have...
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Machine intelligent gust front detection
March 1, 1993
Journal Article
Published in:
Lincoln Laboratory Journal, Vol. 6, No. 1, Spring 1993, pp. 187-212.
Summary
Techniques of low-level machine intelligence, originally developed at Lincoln Laboratory to recognize military ground vehicles obscured by camouflage and foliage, are being used to detect gust fronts in Doppler weather radar imagery. This Machine Intelligent Gust Front Algorithm (MIGFA) is part of a suite of hazardous-weather-detection functions being developed under contract with the Federal Aviation Administration. Initially developed for use with the latest generation Airport Surveillance Radar equipped with a wind shear processor (ASR-9 WSP), MIGFA was deployed for operational testing in Orlando, Florida, during the summer of 1992. MIGFA has demonstrated levels of detection performance that have not only markedly exceeded the capabilities of existing gust front algorithms, but are competitive with human interpreters.
Summary
Techniques of low-level machine intelligence, originally developed at Lincoln Laboratory to recognize military ground vehicles obscured by camouflage and foliage, are being used to detect gust fronts in Doppler weather radar imagery. This Machine Intelligent Gust Front Algorithm (MIGFA) is part of a suite of hazardous-weather-detection functions being developed under...
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The 1990 Airport Surveillance Radar Wind Shear Processor (ASR-WSP) operational test at Orlando International Airport
July 17, 1991
Project Report
Published in:
MIT Lincoln Laboratory Report ATC-178
Summary
Lincoln Laboratory, under sponsorship from the Federal Aviation Administration (FAA), is conducting a program to evaluate the capability of the newest Airport Surveillance Radars (ASR-9) to detect hazardous weather phenomena -- in particular, low-altitude wind shear created by thunderstorm-generated microbursts and gust fronts. The ASR-9 could provide coverage at airports not slated for a dedicated Terminal Doppler Weather Radar (TDWR) and could augment the TDWR at high-priority (high traffic volume, severe weather) facilities by providing a more rapid update of wind shear products, a better viewing angle for some runways, and redundancy in the event of a TDWR failure. An operational evaluation of a testbed ASR Wind Shear Processor (ASR-WSP) was conducted at the Orlando International Airport in Orlando, FL during August and September 1990. The ASR-WSP operational system issued five distinct products to Air Traffic Control: microburst detections, gust front detections, gust front movement predictions, precipitation reflectivity and storm motion. This document describes the operational system, the operational products, and the algorithms employed. An assessment of system performance is provided as one step in evaluating the operational utility of the ASR-WSP.
Summary
Lincoln Laboratory, under sponsorship from the Federal Aviation Administration (FAA), is conducting a program to evaluate the capability of the newest Airport Surveillance Radars (ASR-9) to detect hazardous weather phenomena -- in particular, low-altitude wind shear created by thunderstorm-generated microbursts and gust fronts. The ASR-9 could provide coverage at airports...
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