Publications
A preliminary assessment of thunderstorm outflow wind measurement with airport surveillance radars
May 15, 1987
Project Report
Published in:
MIT Lincoln Laboratory Report ATC-140
Summary
Modern airport surveillance radars (ASR), situated on or near most major air terminals, feature coherent pulse-Doppler processing, a vertical-fan beam and rapid azimuthal antenna scanning for detection and tracking of aircraft. These radars might serve an additional useful role by making radial wind measurements in the immediate vicinity of an airport so as to provide data on thunderstorm outflow winds. This report presents a preliminary analysis of the capabilities and limitations of ASRs in measuring outflow winds. Principal results are: (10) radar sensitivity is adequate to measure winds associated with weakly reflecting (5-20 dBZ) thunderstorm outflows at ranges less than 20 km provided that appropriate operating parameters are chosen; (2) overhanging precipitation, often moving at a markedly different radial velocity than the outflow, will be a significant source of interference owing to the verrtical-fan antenna pattern. If radar reflectivity is approximately constant with altitude, this interference will limit the maximum range for reliable outflow velocity measurements to about 20 km for an outflow that extends 1000 m above the surface and to 7 km for an outflow that extends only 300 m above the surface; (3) At two example major air terminals (Memphis International and Denver Stapleton) ground clutter suppression of approximately 40 dB, combined with the use of unter-clutter visibility techniques, would result in ad adequate signal-to-interference ratio for thunderstorm outflow velocity measurement over the significant approach/departure corridors. This result applies when the radar reflectivity factor in the outflow is 20 dBZ or greater and the associated winds extend at least 300 m above the surface.
Summary
Modern airport surveillance radars (ASR), situated on or near most major air terminals, feature coherent pulse-Doppler processing, a vertical-fan beam and rapid azimuthal antenna scanning for detection and tracking of aircraft. These radars might serve an additional useful role by making radial wind measurements in the immediate vicinity of an...
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Gust front characteristics as detected by Doppler radar
May 1, 1987
Journal Article
Published in:
Mon. Weather Rev., Vol. 115, No. 5, May 1987, pp. 905-918.
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Summary
Gust fronts produce low altitude wind shear that can be hazardous to aircraft operations, especially during takeoff and landing. Radar meteorologists have long been able to identify gust front signatures in Doppler radar data, but in order to use the radar efficiently, automatic detection of such hazards is essential. In a study designed to accumulate statistics on the gust frontal signature in Doppler radar data, nine gust front cases were analyzed. Data were collected on those characteristics thought to be most important in developing rules for automatic gust-front detection such as gust front length and height, maximum and minimum values of reflectivity, velocity and spectrum width, and estimates of radical shear. To provide the reader with a concrete example, photographs of the Doppler radar displays of just two (in the interest of brevity) of the nine gust fronts are presented and discussed, as well as summary data for all cases. For these cases, outflows could be detected most reliably in the velocity field. Line features in the spectrum width and reflectivity fields associated with some of the gust fronts could also be identified, although somewhat less reliably than in a Doppler velocity.
Summary
Gust fronts produce low altitude wind shear that can be hazardous to aircraft operations, especially during takeoff and landing. Radar meteorologists have long been able to identify gust front signatures in Doppler radar data, but in order to use the radar efficiently, automatic detection of such hazards is essential. In...
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Preliminary Memphis FAA/Lincoln Laboratory operational weather studies results
April 22, 1987
Project Report
Published in:
MIT Lincoln Laboratory Report ATC-141
Summary
During 1984 and 1985 M.I.T. Lincoln Laboratory, under the sponsorship of the Federal Aviation Administration (FAA) conducted a measurement program in the Memphis, Tennessee, area to study low-level wind shear events and other weather phenomena that are potentially hazardous to aircraft operations, with particular emphasis on those issues related to the Terminal Doppler Weather Radar (TDWR). The principal sensor for the measurement program was the S-band FAA-Lincoln Laboratory Testbed Doppler Weather Radar (FL2) which incorporates many of the functional features of the TDWR. Both FL2 and a C-band Doppler Weather Radar operated by the University of North Dakota (UND) obtained reflectivity, mean velocity and spectrum width measurements with a radar geometry and scan sequences to facilitate determining the surface outflow features of microbursts at the anticipated TDWR ranges. A 30-station network of automatic weather stations (mesonet) collected I-min averages of temperature, humidity, pressure, wind speed and direction, and total rainfall, plus the peak wind speed during each minute; this system operated from about March through November 1984 and 1985. Finally, the UND Citation aircraft operated two 3-week periods during 1985, collecting thermodynamical, kinematical and microphysical data within and around selected storms in the area as well as providing in situ truth for locations and intensity of turbulence. This report describes the principal initial results from the Memphis operations, stressing the results from 1985 when the FL2 radar was fully operational. These results are compared to those from previous studies of wind-shear programs, e.g., NIMROD near Chicago, JAWS and CLAWS near Denver. During 1985, 102 microbursts were identified in real time along with 81 gust fronts. One of the dominant results is that most microbursts in the mid-south are wet; that is, they are accompanied by significant rainfall. This is in contrast, for example, to the results from Denver where more than half of all microbursts have little or no appreciable rain reaching the ground. Aside from this major difference, microbursts near Memphis were similar to those found elsewhere in the country in terms of wind shear magnitude. The report also gives more representative results from the aircraft operations and discusses the effectiveness of the ground-clutter filters used on the FL2 radar.
Summary
During 1984 and 1985 M.I.T. Lincoln Laboratory, under the sponsorship of the Federal Aviation Administration (FAA) conducted a measurement program in the Memphis, Tennessee, area to study low-level wind shear events and other weather phenomena that are potentially hazardous to aircraft operations, with particular emphasis on those issues related to...
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Spatial and temporal analysis of weather radar reflectivity images
April 9, 1987
Conference Paper
Published in:
Proc. IEEE Int. Conf. on Acoustics, Speech and Signal Processing, ICASSP, 6-9 April 1987, pp. 606-609.
Summary
This paper illustrates the use of a primitive symbolic description of an image to obtain more robust identification of amorphous objects than would be possible with more conventional edge or gradient-based segmentation techniques. An algorithm is described which uses a simple multi-level thresholding operation to form a symbolic representation of weather radar reflectivity images. This representation allows the use of detailed rules for the detection and quantification of the image features. A method is described for using this information to identify significant intensity peaks in an image, and examples of its performance are shown.
Summary
This paper illustrates the use of a primitive symbolic description of an image to obtain more robust identification of amorphous objects than would be possible with more conventional edge or gradient-based segmentation techniques. An algorithm is described which uses a simple multi-level thresholding operation to form a symbolic representation of...
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A block diagram compiler for a digital signal processing MIMD computer
April 9, 1987
Conference Paper
Published in:
Proc. IEEE Int. Conf. on Acoustics, Speech and Signal Processing, ICASSP, Vol. 4, 6-9 April 1987, pp. 1867-1870.
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Summary
A Block Diagram Compiler (BOC) has been designed and implemented for converting graphic block diagram descriptions of signal processing tasks into source code to be executed on a Multiple Instruction Stream - Multiple Data Stream (MIMD) array computer. The compiler takes as input a block diagram of a real-time DSP application, entered on a graphics CAE workstation, and translates it into efficient real-time assembly language code for the target multiprocessor array. The current implementation produces code for a rectangular grid of Texas Instruments TMS32010 signal processors built at Lincoln Laboratory, but the concept could be extended to other processors or other geometries in the same way that a good assembly language programmer would write it. This report begins by examining the current implementation of the BOC including relevant aspects of the target hardware. Next, we describe the task-assignment module, which uses a simulated annealing algorithm to assign the processing tasks of the DSP application to individual processors in the array. Finally, our experiences with the current version of the BOC software and hardware are reported.
Summary
A Block Diagram Compiler (BOC) has been designed and implemented for converting graphic block diagram descriptions of signal processing tasks into source code to be executed on a Multiple Instruction Stream - Multiple Data Stream (MIMD) array computer. The compiler takes as input a block diagram of a real-time DSP...
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Mixed-phase deconvolution of speech based on a sine-wave model
April 9, 1987
Conference Paper
Published in:
Proc. IEEE Int. Conf. on Acoustics, Speech and Signal Processing, ICASSP, Vol. 2, 6-9 April 1987, pp. 649-652.
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Summary
This paper describes a new method of deconvolving the vocal cord excitation and vocal tract system response. The technique relies on a sine-wave representation of the speech waveform and forms the basis of an analysis-synthesis method which yields synthetic speech essentially indistinguishable from the original. Unlike an earlier sinusoidal analysis-synthesis technique that used a minimum-phase system estimate, the approach in this paper generates a "mixed-phase" system estimate and thus an improved decomposition of excitation and system components. Since a mixed-phase system estimate is removed from the speech waveform, the resulting excitation residual is less dispersed than the previous sinusoidal-based excitation estimate of the more commonly used linear prediction residual. A method of time-varying linear filtering is given as an alternative to sinusoidal reconstruction, similar to conventional time-domain synthesis used in certain vocoders, but without the requirement of pitch and voicing decisions. Finally, speech modification with a mixed-phase system estimate is shown to be capable of more closely preserving waveform shape in time-scale and pitch transformations than the earlier approach.
Summary
This paper describes a new method of deconvolving the vocal cord excitation and vocal tract system response. The technique relies on a sine-wave representation of the speech waveform and forms the basis of an analysis-synthesis method which yields synthetic speech essentially indistinguishable from the original. Unlike an earlier sinusoidal analysis-synthesis...
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Multi-style training for robust isolated-word speech recognition
April 9, 1987
Conference Paper
Published in:
Proc. IEEE Int. Conf. on Acoustics, Speech and Signal Processing, ICASSP, Vol. 2, 6-9 April 1987, pp. 705-708.
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Summary
A new training procedure called multi-style training has been developed to improve performance when a recognizer is used under stress or in high noise but cannot be trained in these conditions. Instead of speaking normally during training, talkers use different, easily produced, talking styles. This technique was tested using a speech data base that included stress speech produced during a workload task and when intense noise was presented through earphones. A continuous-distribution talker-dependent Hidden Markov Model (HMM) recognizer was trained both normally (5 normally spoken tones) and with multi-style training (one token each from normal, fast, clear, loud, and question-pitch talking styles). The average error rate under stress and normal conditions fell by more than a factor of two with multi-style training and the average error rate under conditions sampled during training fell by a factor of four.
Summary
A new training procedure called multi-style training has been developed to improve performance when a recognizer is used under stress or in high noise but cannot be trained in these conditions. Instead of speaking normally during training, talkers use different, easily produced, talking styles. This technique was tested using a...
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Two-stage discriminant analysis for improved isolated-word recognition
April 9, 1987
Conference Paper
Published in:
Proc. IEEE Int. Conf. on Acoustics, Speech and Signal Processing, ICASSP, Vol. 2, 6-9 April 1987, pp. 709-712.
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Summary
This paper describes a two-stage isolated word search recognition system that uses a Hidden Markov Model (HMM) recognizer in the first stage and a discriminant analysis system in the second stage. During recognition, when the first-stage recognizer is unable to clearly differentiate between acoustically similar words such as "go" and "no" the second-stage discriminator is used. The second-stage system focuses on those parts of the unknown token which are most effective at discriminating the confused words. The system was tested on a 35 word, 10,710 token stress speech isolated word data base created at Lincoln Laboratory. Adding the second-stage discriminating system produced the best results to date on this data base, reducing the overall error rate by more than a factor of two.
Summary
This paper describes a two-stage isolated word search recognition system that uses a Hidden Markov Model (HMM) recognizer in the first stage and a discriminant analysis system in the second stage. During recognition, when the first-stage recognizer is unable to clearly differentiate between acoustically similar words such as "go" and...
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An introduction to computing with neural nets
April 1, 1987
Journal Article
Published in:
IEEE ASSP Mag., Vol. 4, No. 2, April 1987, pp. 4-22.
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Summary
Artificial neural net models have been studied for many years in the hope of achieving human-like performance in the fields of speech and image recognition. These models are composed of many nonlinear computational elements operating in parallel and arranged in patterns reminiscent of biological neural nets. Computational elements or nodes are connected via weights that are typically adapted during use to improve performance. There has been a recent resurgence in the field of artificial neural nets caused by new net topologies and algorithms, analog VLSI implementation techniques, and the belief that massive parallelism is essential for high performance speech and image recognition. This paper provides an introduction to the field of artificial neural nets by reviewing six important neural net models that can be used for pattern classification. These nets are highly parallel building blocks that illustrate neural net components and design principles and can be used to construct more complex systems. In addition to describing these nets, a major emphasis is placed on exploring how some existing classification and clustering algorithms can be performed using simple neuron-like components. Single-layer nets can implement algorithms required by Gaussian maximum-likelihood classifiers and optimum minimum-error classifiers for binary patterns corrupted by noise. More generally, the decision regions required by any classification algorithm can be generated in a straightforward manner by three-layer feed-forward nets.
Summary
Artificial neural net models have been studied for many years in the hope of achieving human-like performance in the fields of speech and image recognition. These models are composed of many nonlinear computational elements operating in parallel and arranged in patterns reminiscent of biological neural nets. Computational elements or nodes...
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Recognizing low-altitude wind shear hazards from doppler weather radar: an artificial intelligence approach
March 1, 1987
Journal Article
Published in:
J. Atmos. Oceanic Technol., Vol. 4, No. 1, March 1987, pp. 5-18.
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Summary
This paper describes an artificial intelligence-based approach for automated recognition of wind shear hazards. The design of a prototype system for recognizing low-altitude wind shear events from Doppler radar displays is presented. This system, called WXI, consists of a conventional expert system augmented by a specialized capability for processing radar images. The radar image processing component of the system employs numerical and computer vision techniques to extract features from radar data. The expert system carries out symbolic reasoning on these features using a set of heuristic rules expressing meteorological knowledge about wind shear recognition. Results are provided demonstrating the ability of the system to recognize microburst and gust front wind shear events.
Summary
This paper describes an artificial intelligence-based approach for automated recognition of wind shear hazards. The design of a prototype system for recognizing low-altitude wind shear events from Doppler radar displays is presented. This system, called WXI, consists of a conventional expert system augmented by a specialized capability for processing radar...
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