Publications
Terminal Weather Message Demonstration at Orlando, FL, Summer 1993
March 4, 1994
Project Report
Published in:
MIT Lincoln Laboratory Report ATC-210
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Summary
A successful demonstration of providing a text-based message via VHF data link (ACARS) was carried out at Orlando, FL during the summer of 1993. Five airlines participated in the three-month demonstration, which included an average of 145 Terminal Weather message requests per day. During a heavily-impacted weather day, a total of 220 Terminal Weather requests were made. The format of the Terminal Weather message was developed by an ad hoc committee of pilots, dispatchers, controllers and researchers. The format required a balance between the need for including important information and the need to fit the information into a limited number of characters. The approach was to divide the message into several blocks and to prioritize the potential message elements by importance and immediacy. The most important and timely elements are listed first, and the others appear only if more important elements are not present or else were deleted altogether. Pilot reaction to the demonstration was assessed from questionnaire responses. Overall, pilots thought that the system should be deployed operationally and found that it increased situational awareness. They felt that it provided some help in decision making and did not adversely affect cockpit workload. They also strongly endorsed the need for a graphical version of the Terminal Weather service. Controllers were initially concerned that the data link demonstration would result in increased radio traffic and concomitant controller workload. Prior to the demonstration, changes were made in the Terminal Weather message format to help allay these concerns. Consequently, controllers were surprosed to find that requests for weather information actually decreases over what they normally would expect during a period of heavy weather impact. Thus, evidence was obtained that delivery of Terminal Weather information by data link could decrease controller workload. Dispatchers took a strong and unanticipated interest in the Terminal Weather message. The dispatchers for one airline used the Terminal Weather message to monitor weather conditions at Orlando during a period of heavy weather impact. Special messages also were sent to dispatchers to alert them when wind shear or microburst hazards initially impacted the Orlando airport. Additional demonstration of the Terminal Weather message service are planned for the summer of 1994 at Memphis, TN and Orlando, FL. Results of hte summer 1993 demonstration are being used to make improvements to the message content. A demonstration of a grpahical version of the Terminal Weather message is also planned.
Summary
A successful demonstration of providing a text-based message via VHF data link (ACARS) was carried out at Orlando, FL during the summer of 1993. Five airlines participated in the three-month demonstration, which included an average of 145 Terminal Weather message requests per day. During a heavily-impacted weather day, a total...
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Digital signal processing applications in cochlear-implant research
March 1, 1994
Journal Article
Published in:
Lincoln Laboratory Journal, Vol. 7, No. 1, Spring 1994, pp. 31-62.
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We have developed a facility that enables scientists to investigate a wide range of sound-processing schemes for human subjects with cochlear implants. This digital signal processing (DSP) facility-named the Programmable Interactive System for Cochlear Implant Electrode Stimulation (PISCES)-was designed, built, and tested at Lincoln Laboratory and then installed at the Cochlear Implant Research Laboratory (CIRL) of the Massachusetts Eye and Ear Infirmary (MEEI). New stimulator algorithms that we designed and ran on PISCES have resulted in speech-reception improvements for implant subjects relative to commercial implant stimulators. These improvements were obtained as a result of interactive algorithm adjustment in the clinic, thus demonstrating the importance of a flexible signal-processing facility. Research has continued in the development of a laboratory-based, sohare-controlled, real-time, speech processing system; the exploration of new sound-processing algorithms for improved electrode stimulation; and the design of wearable stimulators that will allow subjects full-time use of stimulator algorithms developed and tested in a laboratory setting.
Summary
We have developed a facility that enables scientists to investigate a wide range of sound-processing schemes for human subjects with cochlear implants. This digital signal processing (DSP) facility-named the Programmable Interactive System for Cochlear Implant Electrode Stimulation (PISCES)-was designed, built, and tested at Lincoln Laboratory and then installed at the...
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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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Analysis of surveillance performance at Chicago O'Hare Airport
January 28, 1994
Project Report
Published in:
MIT Lincoln Laboratory Report ATC-193
Summary
This report describes the results of RF measurements of the 1030 and 1090 MHz environment in the Chicago terminal area conducted by Lincoln Laboratory in October 1991. The measurements were made at the request of the FAA in response to reports by controllers in Chicago that TCAS interrogations are affecting the surveillance performance of the Chicago Secondary Surveillance Radar (SSR). The Airborne Meauserements Facility (AMF), developed at Lincoln Laboratory, was used to gather TCAS and SSR interrogation and reply data in the vicinity of O'Hare Airport during periods of active TCAS operation. Simultaneously, local aircraft track data were collected using the Automated Radar Terminal System (ARTS) data recording facility. Analysis of both the AMF data and the ARTS data show that TCAS interrogations do not cause significant degradation in SSR surveillance performance and that the average Chicago ARTS track performance in the presence of TCAS-equipped aircraft is comparable to earlier measurements of track performance in Chicago as well as at a number of other high-density terminal areas. Specific regions within the CHicago surveillance area were observed to contain concentrations of poor ARTS track performance, and analysis of the data has shown the cause to be differential vertical lobing associated with the SSR antenna and faulty Mode S transponders on certain aircarrier aircraft. Both of these problems have subsequently been corrected.
Summary
This report describes the results of RF measurements of the 1030 and 1090 MHz environment in the Chicago terminal area conducted by Lincoln Laboratory in October 1991. The measurements were made at the request of the FAA in response to reports by controllers in Chicago that TCAS interrogations are affecting...
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Aircraft surveillance based on GPS position broadcasts from mode S beacon transponders
January 1, 1994
Conference Paper
Published in:
Proc. of ION GPS, v 1, 1994, pp. 939-950.
Summary
Flight testing of a new air surveillance concept, GPS-Squitter, is reported. It integrates GPS receivers with the existing secondary surveillance radar beacon equipment carried by most aircraft. Simple, inexpensive, non-scanning ground stations listen for GPS position reports broadcast by the Mode S beacon transponders on the aircraft and send them on to air traffic control facilities. In addition to its surveillance application, GPS-Squitter presents opportunities for enhancing other important functions such as collision avoidance systems and data link services. System tradeoff studies are comparing range and altitude coverage with the cost and number of stations needed. Other issues are data link interference, multipath, total aircraft capacity, and unambiguous reporting range. The baseline system uses commercial off-the-shelf components such as TCAS (Traffic Alerting and Collision Avoidance System) avionics units, omni-directional DME (Distance Measuring Equipment) antennas, and computer workstations in order to ensure low production costs. The cost/performance tradeoff of minimum modifications such as the addition of a 6-sector antenna, multiple receive channels, or higher transmit power, are being evaluated. The omni-directional baseline system is designed for a range of 50 nmi while the 6-sector system is designed for 100 nmi range. Two aircraft have been equipped with Mode S beacon transponders modified to broadcast (i.e., "squitter") their GPS position twice each second. The numerous test flights have accumulated a significant data base including a demonstration of coverage out to over 100 nmi range. Data have been collected to analyze a number of issues: received power margins, performance of bottom versus top aircraft antenna, ground bounce multipath, propagation over water, and parallel runway approach monitoring. In addition, standard squitter data from commercial aircraft have been recorded and correlated with Mode S tracking to show link margins experienced in practice from aircraft in operational service. More tests are planned, including a demonstration of GPS-Squitter air surveillance in the Gulf of Mexico.
Summary
Flight testing of a new air surveillance concept, GPS-Squitter, is reported. It integrates GPS receivers with the existing secondary surveillance radar beacon equipment carried by most aircraft. Simple, inexpensive, non-scanning ground stations listen for GPS position reports broadcast by the Mode S beacon transponders on the aircraft and send them...
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Neural networks, Bayesian a posteriori probabilities, and pattern classification
January 1, 1994
Book Chapter
Published in:
Chapter 4 in From Statistics to Neural Networks: Theory and Pattern Recognition Applications, 1994, pp. 83-104.
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Researchers in the fields of neural networks, statistics, machine learning, and artificial intelligence have followed three basic approaches to developing new pattern classifiers. Probability Density Function (PDF) classifiers include Gaussian and Gaussian Mixture classifiers which estimate distributions or densities of input features separately for each class. Posterior probability classifiers include multilayer perceptron neural networks with sigmoid nonlinearities and radial basis function networks. These classifiers estimate minimum-error Bayesian a posteriori probabilities (hereafter referred to as posterior probabilities) simultaneously for all classes. Boundary forming classifiers include hard-limiting single-layer perceptrons, hypersphere classifiers, and nearest neighbor classifiers. These classifiers have binary indicator outputs which form decision regions that specify the class of any input pattern. Posterior probability and boundary-forming classifiers are trained using discriminant training. All training data is used simultaneously to estimate Bayesian posterior probabilities or minimize overall classification error rates. PDF classifiers are trained using maximum likelihood approaches which individually model class distributions without regard to overall classification performance. Analytic results are presented which demonstrate that many neural network classifiers can accurately estimate posterior probabilities and that these neural network classifiers can sometimes provide lower error rates than PDF classifiers using the same number of trainable parameters. Experiments also demonstrate how interpretation of network outputs as posterior probabilities makes it possible to estimate the confidence of a classification decision, compensate for differences in class prior probabilities between test and training data, and combine outputs of multiple classifiers over time for speech recognition.
Summary
Researchers in the fields of neural networks, statistics, machine learning, and artificial intelligence have followed three basic approaches to developing new pattern classifiers. Probability Density Function (PDF) classifiers include Gaussian and Gaussian Mixture classifiers which estimate distributions or densities of input features separately for each class. Posterior probability classifiers include...
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Predicting the risk of complications in coronary artery bypass operations using neural networks
January 1, 1994
Conference Paper
Published in:
Proc. 7th Int. Conf. on Neural Information Processing Systems, NIPS, 1994, pp. 1055-62.
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Experiments demonstrated that sigmoid multilayer perceptron (MLP) networks provide slightly better risk prediction than conventional logistic regression when used to predict the risk of death, stroke, and renal failure on 1257 patients who underwent coronary artery bypass operations at the Lahey Clinic. MLP networks with no hidden layer and networks with one hidden layer were trained using stochastic gradient descent with early stopping. MLP networks and logistic regression used the same input features and were evaluated using bootstrap sampling with 50 replications. ROC areas for predicting mortality using preoperative input features were 70.5% for logistic regression and 76.0% for MLP networks. Regularization provided by early stopping was an important component of improved performance. A simplified approach to generating confidence intervals for MLP risk predictions using an auxiliary "confidence MLP" was developed. The confidence MLP is trained to reproduce confidence intervals that were generated during training using the outputs of 50 MLP networks trained with different bootstrap samples.
Summary
Experiments demonstrated that sigmoid multilayer perceptron (MLP) networks provide slightly better risk prediction than conventional logistic regression when used to predict the risk of death, stroke, and renal failure on 1257 patients who underwent coronary artery bypass operations at the Lahey Clinic. MLP networks with no hidden layer and networks...
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Encoding approaches for data link transmission of weather graphics
December 10, 1993
Project Report
Published in:
MIT Lincoln Laboratory Report ATC-205
Summary
To provide pilots with necessary information to make informed decisions on the avoidance of hazardous weather and to maintain situational awareness of the weather conditions, the FAA is actively developing the capability to provide real-time graphical weather information to aircraft through the use of bandwidth-limited data links such as Mode S. The information content of weather images and the restricted bandwidth of the transmission channel require that the images be extensively compressed. This paper provides the results of a study concerning the applicability of various data compression algorithms to the weather image problem. Its conclusion is that the Polygon-Ellipse Algorithm developed at Lincoln Laboratory provides the best combination of compression, computational efficiency, and image quality for the encoding of weather images over the Mode S data link or other similarly bit-limited data links.
Summary
To provide pilots with necessary information to make informed decisions on the avoidance of hazardous weather and to maintain situational awareness of the weather conditions, the FAA is actively developing the capability to provide real-time graphical weather information to aircraft through the use of bandwidth-limited data links such as Mode...
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Figure of merit training for detection and spotting
November 29, 1993
Conference Paper
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Proc. Neural Information Processing Systems, NIPS, 29 November - 2 December 1993.
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Spotting tasks require detection of target patterns from a background of richly varied non-target inputs. The performance measure of interest for these tasks, called the figure of merit (FOM), is the detection rate for target patterns when the false alarm rate is in an acceptable range. A new approach to training spotters is presented which computes the FOM gradient for each input pattern and then directly maximizes the FOM using back propagation. This eliminates the need for thresholds during training. It also uses network resources to model Bayesian a posteriori probability functions accurately only for patterns which have a significant effect on the detection accuracy over the false alarm rate of interest. FOM training increased detection accuracy by 5 percentage points for a hybrid radial basis function (RBF) - hidden Markov model (HMM) wordspotter on the credit-card speech corpus.
Summary
Spotting tasks require detection of target patterns from a background of richly varied non-target inputs. The performance measure of interest for these tasks, called the figure of merit (FOM), is the detection rate for target patterns when the false alarm rate is in an acceptable range. A new approach to...
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Machine Intelligent Gust Front Algorithm
November 4, 1993
Project Report
Published in:
MIT Lincoln Laboratory Report ATC-196
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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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