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Discussion of the impact of data contamination on TDWR algorithm performance
November 13, 1996
Conference Paper
Published in:
Workshop on Wind Shear and Wind Shear Alert Systems, 13-15 November, 1996.
Summary
The Federal Aviation Administration (FAA) is currently deploying Terminal Doppler Weather Radars (TDWRs) at key airports in the continental U.S. that experience high volumes of traffic and high frequencies of thunderstorm impact. The TDWR is designed to display the location and intensity of storm cells as well as the location and intensity of wind shear events in the airport vicinity. The TDWR system uses clutter filters and four data quality editing techniques: point target removal, clutter residue editing maps (CREMs), range obscuration editing, and velocity dealiasing in an attempt to reduce base data contamination prior to wind shear algorithm processing. The performance of the wind shear detection algorithms is directly related to the quality of the base data. In particular, failures of the data quality editors can seriously degrade the wind shear detection algorithm's performance. It will be shown that these failures can lead to both undetected and false events. In addition, clutter contamination from nonmeteorological sources such as birds can produce false wind shear signatures in the radar data. This paper will examine the impact of data contamination on algorithm performance at key TDWR sites where base and products data have been collected. The severity of these failures will be discussed, along with possible solutions to the most significant problems.
Summary
The Federal Aviation Administration (FAA) is currently deploying Terminal Doppler Weather Radars (TDWRs) at key airports in the continental U.S. that experience high volumes of traffic and high frequencies of thunderstorm impact. The TDWR is designed to display the location and intensity of storm cells as well as the location...
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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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ASR-9 processor augmentation card scan-scan correlator algorithms
April 2, 1996
Project Report
Published in:
MIT Lincoln Laboratory Report ATC-245
Summary
This report documents the Scan-Scan correlator algorithms for the ASR-9 Processor Augmentation Card (9-PAC) project. The 9-PAC is a processor card that serves as a processing enhancement to the existing ASR-9's post-processor system. It provides increased speed and memory capabilities to the processor, which allows for the introduction of more complex scan-scan correlator algorithms. These more complex algorithms improve the ASR-9's system performance through decreased false alarms, and increased detection of aircraft. The 9-PAC Scan-Scan correlator, also known as the Tracker, consists of three basic processing tasks: initialization, input/output, and the actual Tracker. The Tracker can be broken down further into four main processing functions: report-to track association, report-to-track correlation, track update, and track initiation.
Summary
This report documents the Scan-Scan correlator algorithms for the ASR-9 Processor Augmentation Card (9-PAC) project. The 9-PAC is a processor card that serves as a processing enhancement to the existing ASR-9's post-processor system. It provides increased speed and memory capabilities to the processor, which allows for the introduction of more...
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Automated microburst wind-shear prediction
September 1, 1994
Journal Article
Published in:
Lincoln Laboratory Journal, Vol. 7, No. 2, Fall 1994, pp. 399-426.
Summary
We have developed an algorithm that automatically and reliably predicts microburst wind shear. The algorithm, developed as part of the FAA Integrated Terminal Weather System (ITWS), can provide warnings several minutes in advance of hazardous low-altitude wind-shear conditions. Our approach to the algorithm emphasizes fundamental principles of thunderstorm evolution and downdraft development and incorporates heuristic and statistical methods as needed for refinement. In the algorithm, machine-intelligent image processing and data-fusion techniques are applied to Doppler radar data to detect those regions of growing thunderstorms and intensifying downdrafts which lead to microbursts. The algorithm then uses measurements of the ambient temperature/humidity structure in the atmosphere to aid in predicting a microburst's peak outflow strength. The algorithm has been tested in real time as part of the ITWS operational test and evaluation at Memphis, Tennessee, and Orlando, Florida, in 1994.
Summary
We have developed an algorithm that automatically and reliably predicts microburst wind shear. The algorithm, developed as part of the FAA Integrated Terminal Weather System (ITWS), can provide warnings several minutes in advance of hazardous low-altitude wind-shear conditions. Our approach to the algorithm emphasizes fundamental principles of thunderstorm evolution and...
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Evaluation of runway-assignment and aircraft-sequencing algorithms in terminal area automation
September 1, 1994
Journal Article
Published in:
Lincoln Laboratory Journal, Vol. 7, No. 2, Fall 1994, pp. 215-238.
Summary
The Federal Aviation Administration has responded to the steady growth of air traffic and the ensuing increase in delays at airports by initiating new programs for increasing the efficiency of existing air traffic control facilities. The Terminal Air Traffic Control Automation (TATCA) program is intended to increase efficiency by providing controllers with planning aids and advisories to help them in vectoring, sequencing, and spacing traffic arriving at busy airports. Two important algorithms in this system allocate arrivals to multiple runways and set up the best sequences for landing aircraft. This article evaluates the potential for such algorithms to achieve higher throughput with less delay. The results show that, at airports with multiple active runways, the introduction of algorithms for systematic allocation of runways increases throughput considerably. These algorithms are in fact more effective than algorithms that aim at generating optimal landing sequences based on aircraft weight-class inputs. This result is fortuitous because algorithms for optimal sequencing are significantly more difficult to implement in practice than are algorithms for runway allocation. This study also provides a scientific basis for estimating future benefits of terminal automation by using traffic models patterned on actual recorded traffic-flow data, and by proposing a unified method for assessing performance.
Summary
The Federal Aviation Administration has responded to the steady growth of air traffic and the ensuing increase in delays at airports by initiating new programs for increasing the efficiency of existing air traffic control facilities. The Terminal Air Traffic Control Automation (TATCA) program is intended to increase efficiency by providing...
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Documentation of 9-PAC Beacon Target Detector processing function
July 26, 1994
Project Report
Published in:
MIT Lincoln Laboratory Report ATC-220
Summary
This project report documents the algorithms and flow of the Beacon Target Detector (BTD) processing function incorporated as part of the ASR-9 Processor Augmentation Card (9-PAC). The BTD function combines replies that arise from the same aircraft to form beacon targets, and sends these beacon targets to the 9-PAC merge process where they are combined with primary radar reports. The 9-PAC BTD process was designed to solve two problems with the ASR-9 Array Signal Processor (ASP) BTD: identifying and removing false beacon targets due to reflections, and preventing merging or splitting of targets due to reply overlap and garble. The BTD reflection processing algorithm marks each beacon target as either real or false, and provides this information to the 9-PAC merge process. Discrete Mode A reflection false targets are identified when duplicate code reports satisfying stringent conditions are located. In order to find non-discrete Mode A code reflection false targets, the BTD builds an automated, dynamic reflector database based on the geography of pairs of discrete real and false targets.
Summary
This project report documents the algorithms and flow of the Beacon Target Detector (BTD) processing function incorporated as part of the ASR-9 Processor Augmentation Card (9-PAC). The BTD function combines replies that arise from the same aircraft to form beacon targets, and sends these beacon targets to the 9-PAC merge...
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Target detection using radar images of an airport surface
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. 338-356.
Summary
Automation aids which increase the efficiency of the controller and enhance safety are being sought by the Federal Aviation Administration (FAA). This paper describes the target detection algorithms developed by the MIT Lincoln Laboratory as part of the airport surface traffic automation (ASTA) and runway surface safety light system (RSLS) programs sponsored by the FAA that were demonstrated at Logan International Airport in Boston, Mass. from September 1992 through December 1993. A companion paper to this conference describes the ASTA and RSLS system demonstration. Another companion paper describes the tracking algorithms. Real-time, parallel processing implementations of these surveillance algorithms are written in C++ on a Silicon Graphics Inc. Unix multiprocessor. The heavy reliance on commercial hardware, standard operating systems, object oriented design, and high-level computer languages allows a rapid transition from a research environment to a production environment.
Summary
Automation aids which increase the efficiency of the controller and enhance safety are being sought by the Federal Aviation Administration (FAA). This paper describes the target detection algorithms developed by the MIT Lincoln Laboratory as part of the airport surface traffic automation (ASTA) and runway surface safety light system (RSLS)...
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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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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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