Publications
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.
Topic:
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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 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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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 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
Published in:
Proc. Neural Information Processing Systems, NIPS, 29 November - 2 December 1993.
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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 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
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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ADS-Mode S system overview
October 25, 1993
Conference Paper
Published in:
AIAA/IEEE Digital Avionics Systems Conf., 25-28 October 1993, pp. 104-109.
Summary
ADS-Mode S is a system concept that merges the capabilities of Automatic Dependent Surveillance and the Mode S beacon radar. The result is an integrated system for seamless surveillance and data link that permits equipped aircraft to participate in ADS or beacon ground environments. This offers many possibilities for transitioning from a beacon to an ADS based surveillance system. The ADS-Mode S squitter. The current Mode S squitter is a spontaneous, periodic (once per second) 56-bit broadcast message containing the Mode S 24-bit address. This broadcast is provided by all Mode S transponders and is used by the Traffic Alert and Collision Avoidance System (TCAS) to acquire nearby Mode S equipped aircraft. For ADS-Mode S use, this squitter broadcast would be extended to 112 bits to provide for the transmission of a 56-bit ADS message field. The ADS squitter would be transmitted in addition to the current TCAS squitter in order to maintain compatibility with current TCAS equipment during transition.
Summary
ADS-Mode S is a system concept that merges the capabilities of Automatic Dependent Surveillance and the Mode S beacon radar. The result is an integrated system for seamless surveillance and data link that permits equipped aircraft to participate in ADS or beacon ground environments. This offers many possibilities for transitioning...
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ADS-Mode S
October 24, 1993
Conference Paper
Published in:
Proc. 38th Annual Air Traffic Control Association Convention, 24-28 October 1993, pp. 230-236.
Summary
The International Civil Aviation Organization (ICAO) has defined a concept for communications, navigation, and surveillance for the next century known as the Future Air Navigation System (FANS). A cornerstone, of the FANS is an increasing reliance on satellite-based position-determining systems such as the Global Positioning System (GPS). In the case of, surveillance, aircraft position information is automatically downlinked to ground controllers. This technique is known as Automatic Dependent Surveillance (ADS). ADS-Mode S is an ADS system concept utilizing the frequencies and formats of the Mode S system for downlinking position information and also uplinking differential GPS (DGPS) corrections. The result is an integrated concept for surveillance that permits aircraft equipped with a Mode S transponder and a GPS receiver to participate in both ADS and beacon ground environments. This makes possible a smooth transition of the National Airspace System (NAS) secondary surveillance system from a beacon-based to an ADS-based environment. In addition, several other benefits from ADS-Mode S accrue to the Traffic Alert and Collision Avoidance System (TCAS) and to the Mode S Data Link system.
Summary
The International Civil Aviation Organization (ICAO) has defined a concept for communications, navigation, and surveillance for the next century known as the Future Air Navigation System (FANS). A cornerstone, of the FANS is an increasing reliance on satellite-based position-determining systems such as the Global Positioning System (GPS). In the case...
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ASR-9 Microburst Detection Algorithm
October 22, 1993
Project Report
Published in:
MIT Lincoln Laboratory Report ATC-197
Summary
The ASR-9 Wind Shear Processor (WSP) is intended as an economical alternative for those airports that have not been slated to receive a Terminal Doppler Weather Radar (TDWR) but have, or will be receiving, an ASR-9 radar. Lincoln Laboratory has developed a prototype ASR-9 WSP system which has been demonstrated during the summer months of the past three year in Orlando, Florida. During the operational test period, microburst and gust front warnings, as well as storm motion indications, were provided to the Air Traffic Control in real time. The ASR-9 Microburst Detection Algorithm (AMDA) is based on the earlier TDWR Microburst Detection Algorithm but has been substantially modified to match better the particular strengths and weaknesses of the ASR-9 rapid-scanning fan-beam radar. The most significant additions included a capability to detect overhead microbursts, a reflectivity processing step used to help detect velocity signatures that have been biased by overhanging precipitation, and a modification to some of the shear segment grouping and thresholding parameters to accommodate better the typical on-air siting of the ASR-9. In addition, the AMDA has been designed to be as efficient as possible to allow it to run at the radar's 4.8 seconds/scan antennas rotation rate on a single-board computer. A detailed description of AMDA, as well as the performance evaluation strategy and results, are presented in this report.
Summary
The ASR-9 Wind Shear Processor (WSP) is intended as an economical alternative for those airports that have not been slated to receive a Terminal Doppler Weather Radar (TDWR) but have, or will be receiving, an ASR-9 radar. Lincoln Laboratory has developed a prototype ASR-9 WSP system which has been demonstrated...
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