SEARCH · Search NASA

Results for “false alarm rate”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 55 records · Page 3

All sources NASA NTRS DOE OSTI

NASA NTRS2014

MAG4 Versus Alternative Techniques for Forecasting Active-Region Flare Productivity

MAG4 is a technique of forecasting an active region's rate of production of major flares in the coming few days from a free-magnetic-energy proxy. We present a statistical method of measuring the difference in performance between MAG4 and comparable alternative techniques that forecast an active region's major-flare productivity from alternative observed aspects of the active region. We demonstrate the method by measuring the difference in performance between the "Present MAG4" technique and each of three alternative techniques, called "McIntosh Active-Region Class," "Total Magnetic Flux," and "Next MAG4." We do this by using (1) the MAG4 database of magnetograms and major-flare histories of sunspot active regions, (2) the NOAA table of the major-flare productivity of each of 60 McIntosh active-region classes of sunspot active regions, and (3) five technique-performance metrics (Heidke Skill Score, True Skill Score, Percent Correct, Probability of Detection, and False Alarm Rate) evaluated from 2000 random two-by-two contingency tables obtained from the databases. We find that (1) Present MAG4 far outperforms both McIntosh Active-Region Class and Total Magnetic Flux, (2) Next MAG4 significantly outperforms Present MAG4, (3) the performance of Next MAG4 is insensitive to the forward and backward temporal windows used, in the range of one to a few days, and (4) forecasting from the free-energy proxy in combination with either any broad category of McIntosh active-region classes or any Mount Wilson active-region class gives no significant performance improvement over forecasting from the free-energy proxy alone (Present MAG4).

Falconer, David A.↗

NASA NTRS1972

Demonstration of the use of ADAPT to derive predictive maintenance algorithms for the KSC central heat plant

The Avco Data Analysis and Prediction Techniques (ADAPT) were employed to determine laws capable of detecting failures in a heat plant up to three days in advance of the occurrence of the failure. The projected performance of algorithms yielded a detection probability of 90% with false alarm rates of the order of 1 per year for a sample rate of 1 per day with each detection, followed by 3 hourly samplings. This performance was verified on 173 independent test cases. The program also demonstrated diagnostic algorithms and the ability to predict the time of failure to approximately plus or minus 8 hours up to three days in advance of the failure. The ADAPT programs produce simple algorithms which have a unique possibility of a relatively low cost updating procedure. The algorithms were implemented on general purpose computers at Kennedy Space Flight Center and tested against current data.

Hunter, H. E.↗

NASA NTRS1972

A slope reversal video processor having amplitude and pulse width discrimination.

A timing discriminator whose output is relatively insensitive to input pulse width and amplitude is described. The video-handling technique is known as slope reversal processing and is based on tapped delay line estimation methods. The concept, design, breadboard construction, and preliminary laboratory test results are reviewed. The processor system features (1) a peak input voltage dynamic range of 80x starting at 100 microvolts; (2) a four stage preamplifier/line-driver having a voltage gain of 2400x; (3) a tapped delay-line estimator implemented for slope reversal triggering by differential comparison; (4) a nominal plus or minus 2.5 nsec shift of the output trigger leading edge over the entire input voltage range, (5) up to 7 dB discrimination against pulse widths less than 35 nsec; and (6) up to one order of magnitude reduction in the false alarm rate compared to a constant fraction system.

Hoge, F. E.↗

NASA NTRS1980

Source detection for the infrared astronomical satellite

A recursive algorithm is described which detects and characterizes point sources and extended sources in the data obtained from the Infrared Astronomical Satellite (IRAS) in the presence of non-stationary noise. The analysis of tests using simulated data indicates that the performance of the point source detector is very close to that expected from a matched filter with stationary gaussian noise. The false alarm rate of the extended source detector tends to be higher than expected at a given SNR.

Aumann, H. H.↗

NASA NTRS1981

On the reliability of hook echoes as tornado indicators

A study of radar echoes associated with the tornadoes of the 3 April 1974 outbreak was performed to evaluate the usefulness of echo shape as an indicator of tornadic thunderstorms. The hook shape was usually successful in characterizing an echo as tornadic, with a false alarm rate of 16%. Because hook echoes were relatively rare, however, a less restrictive shape called distinctive was more successful at detecting tornadic thunderstorms, identifying 65% of the tornadic echoes. An echo had a distinctive shape if it possessed a marked appendage on its right rear flank or was in the shape of a spiral, comma or line echo wave pattern (LEWP). Characteristics of the distinctive echo are given.

Forbes, G. S.↗

NASA NTRS1982

An adaptive tracking observer for failure-detection systems

The design problem of adaptive observers applied to linear, constant and variable parameters, multi-input, multi-output systems, is considered. It is shown that, in order to keep the observer's (or Kalman filter) false-alarm rate (FAR) under a certain specified value, it is necessary to have an acceptable proper matching between the observer (or KF) model and the system parameters. An adaptive observer algorithm is introduced in order to maintain desired system-observer model matching, despite initial mismatching and/or system parameter variations. Only a properly designed adaptive observer is able to detect abrupt changes in the system (actuator, sensor failures, etc.) with adequate reliability and FAR. Conditions for convergence for the adaptive process were obtained, leading to a simple adaptive law (algorithm) with the possibility of an a priori choice of fixed adaptive gains. Simulation results show good tracking performance with small observer output errors and accurate and fast parameter identification, in both deterministic and stochastic cases.

Sidar, M.↗

NASA NTRS1982

Design of analytical failure detection using secondary observers

The problem of designing analytical failure-detection systems (FDS) for sensors and actuators, using observers, is addressed. The use of observers in FDS is related to the examination of the n-dimensional observer error vector which carries the necessary information on possible failures. The problem is that in practical systems, in which only some of the components of the state vector are measured, one has access only to the m-dimensional observer-output error vector, with m or = to n. In order to cope with these cases, a secondary observer is synthesized to reconstruct the entire observer-error vector from the observer output error vector. This approach leads toward the design of highly sensitive and reliable FDS, with the possibility of obtaining a unique fingerprint for every possible failure. In order to keep the observer's (or Kalman filter) false-alarm rate under a certain specified value, it is necessary to have an acceptable matching between the observer (or Kalman filter) models and the system parameters. A previously developed adaptive observer algorithm is used to maintain the desired system-observer model matching, despite initial mismatching or system parameter variations. Conditions for convergence for the adaptive process are obtained, leading to a simple adaptive law (algorithm) with the possibility of an a priori choice of fixed adaptive gains. Simulation results show good tracking performance with small observer output errors, while accurate and fast parameter identification, in both deterministic and stochastic cases, is obtained.

Sisar, M.↗

NASA NTRS1984

Sensitive detection of narrowband signals

It is pointed out that an effective search for extraterrestrial intelligence (SETI) presents a signal processing task with unusual requirements. In the first place, algorithms with a very low false alarm probability are needed. This implies, that the interpretation of noise as a signal must be rare. Secondly in a SETI, attention must be given to signals having narrow-band or pulsed features. Theoretical considerations are discussed along with aspects of pulse detector motivation, independent pulse trains and the false alarm rate, and software considerations.

Cullers, D. K.↗

NASA NTRS1984

A new technique to infer convective rainfall from satellite infrared cloud observations

GLAS-2, a modified version of the GLAS-1 technique developed by Negri et al. (1984) for estimating convective precipitation from GEO-satellite IR data, is introduced and demonstrated on the data set for the Florida Area Cumulus Experiment in 1980. In GLAS-2, rain cells are located by identification of all local blackbody-temperature minima below 253 K in an array of GOES digital data, and rain parameters are assigned on the basis of the one-dimensional cloud model of Adler and Mack (1984). The demonstration results are presented in graphs and tables and compared with those of GLAS-1 and a number of other methods as well as radar and rain-gage measurements. The false-alarm rate for GLAS-2 is found to be 0.54, somewhat better than that of other satellihte methods; further improvements are suggested.

Negri, A. J.↗

NASA NTRS1986

Narrowband signal detection in the SETI field test

Various methods for detecting narrow-band signals are evaluated. The characteristics of synchronized and unsynchronized pulses are examined. Synchronous, square law, regular pulse, and the general form detections are discussed. The CW, single pulse, synchronous, and four pulse detections are analyzed in terms of false alarm rate and threshold relative to average noise power. Techniques for saving memory and retaining sensitivity are described. Consideration is given to nondrifting CW detection, asynchronous pulse detection, interpolative and extrapolative pulse detectors, and finite and infinite pulses.

Cullers, D. Kent↗

NASA NTRS1990

Framework for a space shuttle main engine health monitoring system

A framework developed for a health management system (HMS) which is directed at improving the safety of operation of the Space Shuttle Main Engine (SSME) is summarized. An emphasis was placed on near term technology through requirements to use existing SSME instrumentation and to demonstrate the HMS during SSME ground tests within five years. The HMS framework was developed through an analysis of SSME failure modes, fault detection algorithms, sensor technologies, and hardware architectures. A key feature of the HMS framework design is that a clear path from the ground test system to a flight HMS was maintained. Fault detection techniques based on time series, nonlinear regression, and clustering algorithms were developed and demonstrated on data from SSME ground test failures. The fault detection algorithms exhibited 100 percent detection of faults, had an extremely low false alarm rate, and were robust to sensor loss. These algorithms were incorporated into a hierarchical decision making strategy for overall assessment of SSME health. A preliminary design for a hardware architecture capable of supporting real time operation of the HMS functions was developed. Utilizing modular, commercial off-the-shelf components produced a reliable low cost design with the flexibility to incorporate advances in algorithm and sensor technology as they become available.

Hawman, Michael W.↗

NASA NTRS1990

Echo size and asymmetry - Impact on NEXRAD storm identification

The effects of echo shape and radar viewing angle on detecting small thunderstorms with the NEXRAD storm identification algorithms are examined. The amorphous low-level echo shapes are modeled as ellipses with major axes ranging from 5-15 km and minor axes varying between 2-5 km. The model echoes are then used to create a 'probability of detection' chart that demonstrates the impact of storm asymmetry on cell identification. The algorithm performance on small thunderstorms observed near Huntsville, Alabama and Kennedy Space Center, Florida is examined. A new algorithm based on the analysis of 15 storms observed in Florida, Alabama, and New Mexico is proposed that would identify storms as having lightning if 40 dBZ reflectivity is present at the -10 C level and the echo top exceeds 9 km. This algorithm would have a 100 percent probability of detecting lightning producing storms 4-33 min before the first flash, a 7 percent false alarm rate and a critical success index of 93 percent.

Buechler, Dennis E.↗

NASA NTRS1991

Calculation of aerosol backscatter from airborne continuous wave focused CO2 Doppler lidar measurements. II - Algorithm performance

This paper examines the performance of the Rothermel et al. (1991) algorithm for calculating aerosol backscatter coefficients from measurements by an airborne continuous wave focused CO2 Doppler lidar by using the algorithm to analyze measurements by the Laser True Airspeed System. The results show that, under optimum signal conditions, backscatter signals are detected unambiguously and the aerosol backscatter coefficients are determined accurately. However, under marginal or subthreshold conditions under which the system sensitivity is degraded, noise can be mistaken for signals. As determined from parametric studies, the 'false-alarm' rate under these conditions depends on the size of the search window and the SNR threshold for valid signals.

Rothermel, Jeffry↗

NASA NTRS1991

Tables of square-law signal detection statistics for Hann spectra with 50 percent overlap

The Search for Extraterrestrial Intelligence, currently being planned by NASA, will require that an enormous amount of data be analyzed in real time by special purpose hardware. It is expected that overlapped Hann data windows will play an important role in this analysis. In order to understand the statistical implication of this approach, it has been necessary to compute detection statistics for overlapped Hann spectra. Tables of signal detection statistics are given for false alarm rates from 10(exp -14) to 10(exp -1) and signal detection probabilities from 0.50 to 0.99; the number of computed spectra ranges from 4 to 2000.

Deans, Stanley R.↗

NASA NTRS1992

Lock detection in Costas loops

Previous analyses of lock detector algorithms for Costas loops have ignored the effects of the inherent correlation between samples of the phase error process. In this paper, both analysis and simulations are used to quantify the effects of phase correlation on lock detection for the 'square law' and 'absolute value' type detectors. Results are obtained which depict the lock detection probability as a function of loop signal-to-noise ratio for a given false alarm rate. It is shown that the square law detector experiences less degradation due to phase jitter than the absolute value detector and that the degradation in detector signal-to-noise ratio is more pronounced for squarewave than for sinewave signals.

Mileant, A.↗

NASA NTRS1992

An analysis of I/O efficient order-statistic-based techniques for noise power estimation in the HRMS sky survey's operational system

Noise power estimation in the High-Resolution Microwave Survey (HRMS) sky survey element is considered as an example of a constant false alarm rate (CFAR) signal detection problem. Order-statistic-based noise power estimators for CFAR detection are considered in terms of required estimator accuracy and estimator dynamic range. By limiting the dynamic range of the value to be estimated, the performance of an order-statistic estimator can be achieved by simpler techniques requiring only a single pass of the data. Simple threshold-and-count techniques are examined, and it is shown how several parallel threshold-and-count estimation devices can be used to expand the dynamic range to meet HRMS system requirements with minimal hardware complexity. An input/output (I/O) efficient limited-precision order-statistic estimator with wide but limited dynamic range is also examined.

Zimmerman, G. A.↗

NASA NTRS1994

Aided targeting system simulation evaluation

Simulation research was conducted at the Crew Station Research and Development Facility on the effectiveness and ease of use of three targeting systems. A manual system required the aviator to scan a target array area with a simulated second generation forward looking infrared (FLIR) sensor, locate and categorize targets, and construct a target hand-off list. The interface between the aviator and the system was like that of an advanced scout helicopter (manual mode). Two aided systems detected and categorized targets automatically. One system used only the FLIR sensor and the second used FLIR fused with Longbow radar. The interface for both was like that of an advanced scout helicopter aided mode. Exposure time while performing the task was reduced substantially with the aided systems, with no loss of target hand-off list accuracy. The fused sensor system showed lower time to construct the target hand-off list and a slightly lower false alarm rate than the other systems. A number of issues regarding system sensitivity and criterion, and operator interface design are discussed.

Demaio, Joe↗

NASA NTRS1994

Hidden Markov models and neural networks for fault detection in dynamic systems

Neural networks plus hidden Markov models (HMM) can provide excellent detection and false alarm rate performance in fault detection applications, as shown in this viewgraph presentation. Modified models allow for novelty detection. Key contributions of neural network models are: (1) excellent nonparametric discrimination capability; (2) a good estimator of posterior state probabilities, even in high dimensions, and thus can be embedded within overall probabilistic model (HMM); and (3) simple to implement compared to other nonparametric models. Neural network/HMM monitoring model is currently being integrated with the new Deep Space Network (DSN) antenna controller software and will be on-line monitoring a new DSN 34-m antenna (DSS-24) by July, 1994.

Smyth, Padhraic↗