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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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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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An improved gust front detection algorithm for the TDWR
June 24, 1991
Conference Paper
Published in:
25th Int. Conf. on Radar Meteorology, Paris, France, 24-28 June 1991, pp. J37-J42.
Summary
Gust fronts are associated with potentially hazardous wind shears and cause sustained wind shifts after passage. Terminal Air Traffic Control (ATC) is concerned about the safety hazard associated with shear regions and prediction of the wind shift for runway reconfiguration. The Terminal Doppler Weather Radar (TDWR) system has a gust front detection algorithm which has provided an operationally useful capability for both safety and planning. However, this algorithm's performance is sensitive to the orientation of the gust front with respect to the radar radial. Due to this sensitivity, the algorithm is unable to detect about 50% of gust fronts that cross the airport. This paper describes a new algorithm which provides improved performance by using additional radar signatures of gust fronts. The performance of the current TDWR gust front algorithm for the various operational demonstrations has been documented in Klingle-Wilson et al. (1989) and Evans (1990). These analyses highlighted deficiencies in the current algorithm, which is designed to detect radial convergent shears only. When gust fronts or portions of gust fronts become aligned nearly parallel to a radial, the radial component of the shear is not as readily evident. In addition, gust fronts that are near or over the radar exhibit little radial convergence along their lengths and ground clutter can obscure the gust front near the radar. Thus, special handling is needed for fronts that approach the radar. Figure 1 illustrates the various components of a gust front as viewed by Doppler radar. The portion of the gust front in the figure labelled radial convergence is detectable with the current algorithm. Fronts, or portions of fronts, that are aligned along the radar radial and those that pass over the radar are examples of events which can exhibit little or no radial shear signature. These events are often detectable by variations in the radial velocities from azimuth to azimuth (i.e., azimuthal shear)., and/or by radar reflectivity thins lines. The new algorithm improves the detection and prediction of gust fronts by merging radial convergence features with azimuthal shear features, thin line features, and the predicted locations of gust fronts which are passing over the radar. The next four sections of this paper describe the individual components of the improved algorithm. Section 6 describes the rule base used to combine detections from the four components into single gust front detections and Section 7 discusses the output of the algorithm.
Summary
Gust fronts are associated with potentially hazardous wind shears and cause sustained wind shifts after passage. Terminal Air Traffic Control (ATC) is concerned about the safety hazard associated with shear regions and prediction of the wind shift for runway reconfiguration. The Terminal Doppler Weather Radar (TDWR) system has a gust...
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Divergence detection in wind fields estimated by an airport surveillance radar
October 15, 1990
Project Report
Published in:
MIT Lincoln Laboratory Report ATC-172
Summary
This report assesses a technique for automatic detection of hazardous divergence in velocity fields estimated by an Airport Surveillance Radar (SAR). We evaluate a least-squares approach to radial divergence estimation through a performance analysis based on simulated data. That approach is compared to an existing decision-based radial shear finding method used for the Terminal Doppler Weather Radar (TDWR). Empirical results derived by the application of two techniques to data collected at ASR testbeds in Huntsville, Alabama and in Kansas City, Missouri are presented. Results indicate that a simple, least-squares divergence estimator combined with time association logic to increase temporal continuity of algorithm output is an equally effective means of detecting divergent wind shear in velocity fields estimated from ASR signals.
Summary
This report assesses a technique for automatic detection of hazardous divergence in velocity fields estimated by an Airport Surveillance Radar (SAR). We evaluate a least-squares approach to radial divergence estimation through a performance analysis based on simulated data. That approach is compared to an existing decision-based radial shear finding method...
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Dual-beam autocorrelation based wind estimates from airport surveillance radar signals
June 21, 1989
Project Report
Published in:
MIT Lincoln Laboratory Report ATC-167
Summary
This report describes an efficient, autocorrelation based algorithm for estimating low altitude radial winds using signals from the two receiving beams of an airport surveillance radar (ASR). The approach seeks to achieve the accuracy demonstrated previously for spectral domain dual beam velocity estimators with significantly reduced computational requirements. Fundamental to the technique is the assumption that the power spectrum measured with an airport surveillance radar's broad elevation beam can be fitted by a two component Gaussian model. The parameters of this model are estimated using measured low-order autocorrelation lags from the low and high beam received signals. The desired near surface radial velocity estimate is obtained directly as one of these parameters -- the center frequency of the "low altitude" Gaussian spectrum component. Simualted data and field measurements from Lincoln Laboratory's experimental ASR-8 in Huntsville, Alabama were used to evaluate the accuracy of the autocorrelation based velocity estimates. Monte Carlo simulations indicate that biases relative to the near surface outflow velocity in a microburst would be less than 2.5 m/s unless the microburst were distant (range > 12 km) or very shallow (depth of maximum wind speed layer < 50 m). Estimate standard deviations averaged 0.5 m/s after the spatial filtering employed in our processing sequence. The algorithm's velocity estimate accuracy was sufficient to allow for automatic detection of measured microbursts during 1988 with a detection probability exceeding 0.9 and a false alarm probability less than 0.05. Our analyses indicates that the dual-beam autocorrelation based velocity estimator should support ASR with shear detection at approximately the same level of confidence as the low-high beam spectral differencing algorithm evaluated by Weber and Noyes (1988).
Summary
This report describes an efficient, autocorrelation based algorithm for estimating low altitude radial winds using signals from the two receiving beams of an airport surveillance radar (ASR). The approach seeks to achieve the accuracy demonstrated previously for spectral domain dual beam velocity estimators with significantly reduced computational requirements. Fundamental to...
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Storm models for end-to-end TDWR signal processing simulation tests
May 1, 1989
Project Report
Published in:
MIT Lincoln Laboratory Report ATC-155
Summary
End-to-end qualification testing of teh Terminal Doppler Weather Radar (TDWR) contractor signal processing system will be accomplished by a signal processing simulation test. Government furnished storm models will be used to provide inputs to the signal processor. The corresponding hazardous weather product results will be compared to hte results determined by the detection algorithm developers. This report examines the role of the end-to-end tests in the context of overall TDWR qualification testing and concludes that the signal waveform/velocity ambiguity resolution should be the principal focus of the signal processing simulation testing. Salient characteristics of the initial pair of storm models (a high reflectivity microburst observed in Huntsville, AL, and a series of low-to-moderate reflectivity microburst storms observed in Denver, CO) are described as well as desirable characteristics of additional storm models to be provided later.
Summary
End-to-end qualification testing of teh Terminal Doppler Weather Radar (TDWR) contractor signal processing system will be accomplished by a signal processing simulation test. Government furnished storm models will be used to provide inputs to the signal processor. The corresponding hazardous weather product results will be compared to hte results determined...
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Gust front detection algorithm for the Terminal Doppler Weather Radar : part 1, current status
February 3, 1989
Conference Paper
Published in:
Proc. Third Int. Conf. on the Aviation Weather System, 30 January - 3 February 1989, pp. 31-34.
Summary
The gust front detection and wind shift algorithm is one of the two main algorithms developed for the Terminal Doppler Weather Radar (TDWR) program. This two-part paper documents some recent enhancements to, and the current status of, the algorithm (Part 1) and presents some results from recent testing of the algorithm during the TDWR Operational Test and Evaluation (OT&E) (Part 2: Klingle-Wilson et al., 1989).
Summary
The gust front detection and wind shift algorithm is one of the two main algorithms developed for the Terminal Doppler Weather Radar (TDWR) program. This two-part paper documents some recent enhancements to, and the current status of, the algorithm (Part 1) and presents some results from recent testing of the...
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Classes of functions with explicit best uniform approximations
January 1, 1982
Journal Article
Published in:
J. Approx. Theory, Vol. 34, No. 3, 1982, pp. 264-276.
Topic:
R&D group:
Summary
This paper concerns the construction of forms of the error function, en(x) = f(x)- p*n(x), where p*n is the best uniform polynomial approximation of degree n to a continuous function f on [-1, +l]. We show that it is always possible and, from the viewpoint of obtaining explicit results, expedient to write the error as en= a cos(n(Theta + phi), where x =cos Theta, |a|= En(f), the uniform norm of en(x), and the phase angle phi is a continuous function of Theta, depending on f and n. Our classes of explicit best approximations arise from a novel method of determining suitable phase angles in this representation of en(x).
Summary
This paper concerns the construction of forms of the error function, en(x) = f(x)- p*n(x), where p*n is the best uniform polynomial approximation of degree n to a continuous function f on [-1, +l]. We show that it is always possible and, from the viewpoint of obtaining explicit results, expedient...
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On best approximation by truncated series
May 1, 1981
Journal Article
Published in:
J. Approx. Theory, Vol. 32, May 1981, pp. 82-84.
Topic:
R&D group:
Summary
Let T, be the Chebyshev polynomial of the first kind of degree k.
Summary
Let T, be the Chebyshev polynomial of the first kind of degree k.
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Active BCAS: design and validation of the surveillance subsystem
December 17, 1980
Project Report
Published in:
MIT Lincoln Laboratory Report ATC-103
Summary
Lincoln Laboratory, under FAA sponsorship, is developing an Active Beacon Collision Avoidance System (BCAS), concentrating primarily on the air-to-air surveillance subsystem. The surveillance functions required are to detect the presence of nearby aircraft (whether they are equipped with ATCRBS transponders or DABS transponders), and then generate a surveillance track on each aircraft, issuing range and altitude reports once per second. The development effort consisted of airborne measurements complemented by simulation studies and analyses. The basic effects of ground-bounce multipath, interference, and power fading were assessed by air-to-air measurements. In other measurements, the BCAS interrogation and reply signal formats were transmitted between aircraft, and the results recorded for later playback and computer processing using the BCAS surveillance algorithms. This is a flexible means of experimentation which allows many of the design parameters to be changed as the effects are noted. In the most recent phase of the program, Lincoln designed and built realtime BCAS Experimental Units (BE Us), flight tested them, and then delivered them to the FAA for more extensive flight testing. In one of these flight tests, a BEU-equipped Boeing 727 flew to New York, Atlanta, and other major terminal areas in the eastern U.S. An analysis of BEU performance during this "Eastern Tour" is given in this report.
Summary
Lincoln Laboratory, under FAA sponsorship, is developing an Active Beacon Collision Avoidance System (BCAS), concentrating primarily on the air-to-air surveillance subsystem. The surveillance functions required are to detect the presence of nearby aircraft (whether they are equipped with ATCRBS transponders or DABS transponders), and then generate a surveillance track on...
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