Publications
Impact of weather event uncertainty upon an optimum ground-holding strategy
January 1, 1993
Journal Article
Published in:
Air Traffic Control Q., Vol. 1, No. 1, January 1993, pp. 59-84.
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Summary
When weather events are expected to produce significant delays at destination airports, the traffic flow management system in the United States holds departing aircraft on the ground in an attempt to reduce delay costs to the operator and to alleviate airborne congestion. Selecting the correct amount of ground holding is made difficult because of uncertainty in predicting weather events that produce congestion. In general, decision-makers must strike a balance between the amount of predicted delay absorbed on the ground and the amount absorbed in the air. This paper first addresses the question of how uncertainty in the required delay should influence the amount of ground holding. It then establishes the relationship between delay uncertainty and uncertainties in predicting the onset and duration of weather events. Delay costs are minimized under an assumption that there is a fixed ratio between the cost of a unit of ground delay and a unit of airborne delay and that the landing sequence employed at the destination terminal is based upon the originally scheduled landing order. The analysis indicates that uncertainty in the delay prediction must be considered in selecting the optimum amount of ground holding for an individual flight. In predicting delays, it is desirable to keep the ratio of the standard error to the mean delay (σ / μ) well below 1.0 in order to avoid loss of benefits. A corresponding figure of merit for weather systems is shown to be the ratio of the uncertainty in onset/termination times to the duration of the weather event. Weather prediction systems must keep this ratio well below one-third to avoid significant loss of ground-holding benefits. The analysis indicates that reductions in the delay uncertainty through improved weather forecasting and traffic management systems can result in better decision-making and significant cost savings.
Summary
When weather events are expected to produce significant delays at destination airports, the traffic flow management system in the United States holds departing aircraft on the ground in an attempt to reduce delay costs to the operator and to alleviate airborne congestion. Selecting the correct amount of ground holding is...
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The Terminal Doppler Weather Radar (TDWR) Moving Target Simulator (MTS) at Orlando, Florida
August 20, 1992
Project Report
Published in:
MIT Lincoln Laboratory Report ATC-188
Summary
Monitoring the performance of Doppler weather radars presents special problems since target returns cannot be verified by reference to other systems (e,g ., as ASR-9 aircraft reports can be compared with beacon replies). The Terminal Doppler Weather Radar (TDWR) system includes a Moving Target Simulator (MTS) which provides a point target equivalent to a 50 dBZ reflectivity weather return with an apparent radial velocity of 5 m/s. This report describes the installation results for a prototype MTS using the TDWR testbed radar in Orlando, FL. Procedures were developed for improved aiming of the MTS, using aiming of the MTS, using azimuth and elevation adjustments, which are recommended to be incorporated in the production MTS installation procedure. Initial data analyses indicate that the MTS returns from a typical radio tower would be useful for integrity monitoring in fair weather using typical TDWR filters. The use of the MTS when high -reflectivity weather or anomalous propagation (AP) is present needs further study.
Summary
Monitoring the performance of Doppler weather radars presents special problems since target returns cannot be verified by reference to other systems (e,g ., as ASR-9 aircraft reports can be compared with beacon replies). The Terminal Doppler Weather Radar (TDWR) system includes a Moving Target Simulator (MTS) which provides a point...
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Storm tracking for TDWR: a correlation algorithm design and evaluation
July 14, 1992
Project Report
Published in:
MIT Lincoln Laboratory Report ATC-182
Summary
Storm Movement Prediction (SMP) is a proposed (future) product for Terminal Doppler Weather Radar (TDWR), aiding controllers by tracking storms approaching and passing through the terminal environment. Because the scan strategy (data acquisition) of TDWR has been critically designed to meet the needs of its primary function, which is the detection of hazardous low-altitude wind shear, there is the question of whether reliable storm tracking can be obtained from the TDWR data set. The objectives of storm tracking involve a scope (spatial range) much larger than that required for the wind-shear algorithms where volume coverage is confined (in off-airport sited radars) to a sector covering the important approach and departure corridors and the only 360-degree scans are near-surface scans for gust-front detection. This report examines the application of a correlation based method of detecting storm motion, testing the notion that reliable storm motion can be inferred from existing TDWR data. In particular, storm motion derived from an analysis of the TDWR Precipitation product (PCP) is studied. A summary description of the algorithm is presented along with an analysis of its performance using data from MIT Lincoln Laboratory's TDWR testbed operations in Denver (1988) and Kansas City (1989). The primary focus of the present analysis is on the reliability of tracking, since the algorithm is expected to operate in an autonomous environment. Some attention is given to the idea of prediction, in the form of storm extrapolation, considering 15, 30, and 60 minute predictions. Specific areas for improvement are identified, and application of hte algorithm track vectors for long-term prediction (30-60 minutes) is discussed with reference to example PCP images.
Summary
Storm Movement Prediction (SMP) is a proposed (future) product for Terminal Doppler Weather Radar (TDWR), aiding controllers by tracking storms approaching and passing through the terminal environment. Because the scan strategy (data acquisition) of TDWR has been critically designed to meet the needs of its primary function, which is the...
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Birds mimicking microbursts on 2 June 1990 in Orlando, Florida
July 10, 1992
Project Report
Published in:
MIT Lincoln Laboratory Report ATC-184
Summary
During 1990 and 1991, the Terminal Doppler Weather Radar (TDWR) testbed collected Doppler radar measurements in Orlando, Florida in support of the TDWR Project. The main focus of the project is to develope algorithms that automatically detect wind shears such as microbursts anti gust fronts. While the primary goal of the TDWR is to detect scattering from raindrops, the sensitivity of the system allows for the detection of biological echoes as well. Previous research has shown that under certain conditions the scattering from birds and insects will lead to divergent signatures that mimic microbursts. This type, of pattern has been documented in Alabama (Rinehart, 1986), Illinois (Larkin and Quine, 1989), and Missouri (Evans, 1990). In the Alabama and Illinois events, a divergent pattern similar to a microburst was produced when a large number of birds departed in the early morning hours from an overnight roosting site. On 2 June 1990 in Orlando, Florida, there were 11 surface divergent signatures similar to microbursts detected by the TDWR testbed radar. The maximum differential velocity of these events ranged from 11 to 36 m/s, while the maximum reflectivity varied from 0 to 44 dBz. There was light rain in the area and low-reflectivity returns aloft; however, the reflectivity was more like low-reflectivity microbursts in Denver than high-reflectivity microbursts that generally are observed in Orlando. These divergences were not detected by the microburst algorithm since the TDWR site adaptation parameters have been adjusted to avoid issuing alarms for signatures such as those on 2 June. Detailed investigation was conducted of two events to verify that these were not actual microbursts. Single Doppler radar features identified in earlier observations of divergence signatures caused by birds in Alabama and Missouri, as well as features suggested by NEXRAD researchers, were considered. The results of the radar data analysis could not unequivocally determine that birds caused the divergent signatures. A microburst prediction model developed by Wolfson was applied to the data using sounding results from Cape Canaveral, Florida to determine whether the apparent velocities were consistent with current theories of microburst generation. This model analysis clearly indicated a nonweather-related cause for the divergent signatures observed on 2 June. We conclude from the microburst prediction analysis and certain oddities in the divergence radar signatures that birds probably accounted for these divergences.
Summary
During 1990 and 1991, the Terminal Doppler Weather Radar (TDWR) testbed collected Doppler radar measurements in Orlando, Florida in support of the TDWR Project. The main focus of the project is to develope algorithms that automatically detect wind shears such as microbursts anti gust fronts. While the primary goal of...
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Airport Surveillance Radar (ASR-9) Wind Shear Processor - 1991 Test at Orlando, Florida
June 1, 1992
Project Report
Published in:
MIT Lincoln Laboratory Report ATC-189
Summary
An operational test of a Wind Shear Processor (WSP) add-on to the Federal Aviation Administration's airport surveillance radar (ASR-9) took place at Orlando International Airport during July and August 1991. The test allowed for both quantitative assessment of the WSP's signal processing and wind shear detection algorithms and for feedback from air traffic controllers and their supervisors on the strengths and weaknesses of the system. Thunderstorm activity during the test period was intense; low-altitude wind shear impacted the runways or approach/departure corridors on 40 of the 53 test days. As in previous evaluations of the WSP in the southeastern United States, microburst detection performance was very reliable. Over 95% of the strong microbursts that affected the Orlando airport during the test period were detected by the system. Gust front detection during the test, while operationally useful, was not as reliable as it should have been, given the quality of gust front signatures in the base reflectivity and radial velocity data from the WSP. Subsequent development of a Machine Intelligent gust front algorithm has resulted in significantly improved detection capability. Results from the operational test are being utilized in ongoing refinement of the WSP.
Summary
An operational test of a Wind Shear Processor (WSP) add-on to the Federal Aviation Administration's airport surveillance radar (ASR-9) took place at Orlando International Airport during July and August 1991. The test allowed for both quantitative assessment of the WSP's signal processing and wind shear detection algorithms and for feedback...
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A comparison of the performance of two gust front detection algorithms using a length-based scoring technique
May 8, 1992
Project Report
Published in:
MIT Lincoln Laboratory Report ATC-185
Summary
The Terminal Doppler Weather Radar (TDWR) Gust Front Algorithm provides, as products, estimates of the current locations of gust fronts, their future locations, the wind speed and sirection behind the gust fronts, and the wind shear hazard to landing or departing aircraft. These products are used by air traffic controllers and supervisors to warn pilots of potentially hazardous wind shears during take-off and landing and to plan runway reconfigurations. Until recently, an event-based scoring system was used to evaluate the performance of the algorithm. With the event-based scoring scheme, if any part of a gust front length was detected, a valid detection was declared. Unfortunately, this scheme gave no indication of how much of the gust front length was detected; nor could the probabilities be easily related to the probability of issuing a wind shear alert for a specific approach or departure path which was being impacted by a gust front. To make the scoring metric more nearly reflect the operational use of the product, a new length-based scoring scheme was devised. This scheme computes the length of the gust front detected by the algorithm. When computed over a large number of gust fronts, this length-based scoring scheme yields the probability that any part of the gust front will be detected. As improvements to the algorithm increase the length detected, the probability of detecting any part of a gust front increases. In particular, an improved algorithm means an increased probability of correctly issuing wind shear alerts for the runways impacted by a gust front, and length-based scoring is a more accurate technique for assessing this probability of detection. This paper describes the length-based scoring scheme and compares it with event-based scoring of the algorithm's gust front detection and forecast performance. The comparison of the scoring methods shows that recent enhancements to the gust front algorithm provide a substantial, positive impact on performance.
Summary
The Terminal Doppler Weather Radar (TDWR) Gust Front Algorithm provides, as products, estimates of the current locations of gust fronts, their future locations, the wind speed and sirection behind the gust fronts, and the wind shear hazard to landing or departing aircraft. These products are used by air traffic controllers...
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Summary of triple Doppler data, Orlando 1991
April 7, 1992
Project Report
Published in:
MIT Lincoln Laboratory Report ATC-186
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Summary
Under Federal Aviation Administration (FAA) sponsorship, Lincoln Laboratory conducted an aviation weather hazard measurement and operational demonstration program during the summer of 1991 near the Orlando International Airport. Three Doppler radars were sited in a triangle around the airport, allowing triple Doppler coverage of thunderstorms and microbursts occurring there. This report contains a summary of all of the microburst producing thunderstorms that occurred within the triple Doppler region that were scanned in a coordinated fashion, during the months of June, July, August, and September, 1991. Statistics on the microburst events are presented to give an overall picture of the available data for use in analysis. The bulk of the report consists of detailed information about each triple Doppler day, including the time, location, and strength of microbursts within the triple Doppler period as well as the availability of data from supporting sensors including the ASR-9-WSR Doppler radar, radiosondes, LLWAS, Mesonet, AWOS, instrumented aircraft, ACARS, interferometer, and corona points.
Summary
Under Federal Aviation Administration (FAA) sponsorship, Lincoln Laboratory conducted an aviation weather hazard measurement and operational demonstration program during the summer of 1991 near the Orlando International Airport. Three Doppler radars were sited in a triangle around the airport, allowing triple Doppler coverage of thunderstorms and microbursts occurring there. This...
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Doppler mean velocity estimation - small sample analysis and a new estimator
March 25, 1992
Technical Report
Published in:
MIT Lincoln Laboratory Report TR-942
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Summary
Optimal Doppler velocity estimation, under the constraint of small sample size, is explored for a standard Gaussian signal measurement model and thematic maximum likelihood (ML) and Bayes estimation. Because the model considered depends on a vector parameter [velocity, spectrum width, and signal-to-noise ratio (SNR)], the exact formulation of an ML or Bayes solution involves a system of equations that is neither uncoupled nor explicit in form. Historically, iterative methods have been the most suggested approach to solving the required equations. In addition to being computationally intensive, it is unclear whether iterative methods can be constructed to perform well given a small-sample size and low signal strength. This report takes a different approach and seeks to construct approximate (ML and Bayes) estimators based on the notion of using constrained adaptive models to deal with nuisance parameter removal. A Monte Carlo simulation is used to determine small-sample estimator statistics and to demonstrate true performance bounds in the case of known nuisance values. Performance comparisons between these optional forms and other standard estimators [pulse pairs (PP) and a frequency domain (WP) method] are presented. Performance sensitivity of the optimal algorithms, with respect to uncertainity in the values of model nuisance parameters, is explored.
Summary
Optimal Doppler velocity estimation, under the constraint of small sample size, is explored for a standard Gaussian signal measurement model and thematic maximum likelihood (ML) and Bayes estimation. Because the model considered depends on a vector parameter [velocity, spectrum width, and signal-to-noise ratio (SNR)], the exact formulation of an ML...
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Initialization for improved IIR filter performance
March 1, 1992
Journal Article
Published in:
IEEE Trans. Signal Process., Vol. 40, No. 3, March 1992, pp. 543-550.
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Summary
A new method for initializing the memory registers of IIR filters is introduced. In addition to providing improved performance as compared to other methods of initialization, this method is unique in that it makes no a priori assumptions regarding the input-signal content. Therefore, this method applies equally well to a variety of IIR filter designs and applications. The method is best suited for signal-processing applications in which "batch" processing of the data is used. However, sequential processing can be accommodated when delays at the beginning of a processing segment can be tolerated.
Summary
A new method for initializing the memory registers of IIR filters is introduced. In addition to providing improved performance as compared to other methods of initialization, this method is unique in that it makes no a priori assumptions regarding the input-signal content. Therefore, this method applies equally well to a...
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Terminal Doppler weather radar/low-level wind shear alert system integration algorithm specification, version 1.1
February 24, 1992
Project Report
Published in:
MIT Lincoln Laboratory Report ATC-187
Summary
There will be a number of airports that receive both a Terminal Doppler Weather Radar (TDWR) windshear detection system and a phase III Low-Level Wind Shear Alert System (LLWAS). At those airports, the two systems will need to he combined into a single windshear detection system. This report specifies the algorithm to be used to integrate the two subsystems. The algorithm takes in the alphanumeric runway alert messages generated by each subsystem and joins them into integrated alert messages. The design goals of this windshear detection system are (1) to maintain the probability of detection for hazardous events while reducing the number of false alerts and microburst overwarnings and 2) to increase the accuracy of the loss/gain estimates. The first design goal is accomplished by issuing an integrated alert for an operational runway whenever either subsystem issues a 'strong' alert for that runway; by canceling a 'weak' windshear alert on an operational runway if only one subsystem is making the declaration; and by reducing a 'weak' microburst alert on an operational runway to a 'strong' windshear alert if only one subsystem is making the declaration. The second design goal is accomplished by using the average of the two loss/gain values, when appropriate. TDWR, windshear, LLWAS, algorithm specification.
Summary
There will be a number of airports that receive both a Terminal Doppler Weather Radar (TDWR) windshear detection system and a phase III Low-Level Wind Shear Alert System (LLWAS). At those airports, the two systems will need to he combined into a single windshear detection system. This report specifies the...
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