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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.

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All sourcesNASA NTRSDOE OSTI
NASA NTRS2009

Neural Network Target Identification System for False Alarm Reduction

A multi-stage automated target recognition (ATR) system has been designed to perform computer vision tasks with adequate proficiency in mimicking human vision. The system is able to detect, identify, and track targets of interest. Potential regions of interest (ROIs) are first identified by the detection stage using an Optimum Trade-off Maximum Average Correlation Height (OT-MACH) filter combined with a wavelet transform. False positives are then eliminated by the verification stage using feature extraction methods in conjunction with neural networks. Feature extraction transforms the ROIs using filtering and binning algorithms to create feature vectors. A feed forward back propagation neural network (NN) is then trained to classify each feature vector and remove false positives. This paper discusses the test of the system performance and parameter optimizations process which adapts the system to various targets and datasets. The test results show that the system was successful in substantially reducing the false positive rate when tested on a sonar image dataset.

ATR↗
NASA NTRS2001

Atlantic Tropical Cyclone Monitoring with AMSU-A: Estimation of Maximum Sustained Wind Speeds

The first Advanced Microwave Sounding Unit temperature sounder (AMSU-A) was launched on the NOAA-15 satellite on 13 May 1998. The AMSU-A's higher spatial and radiometric resolutions provide more useful information on the strength of the middle and upper tropospheric warm cores associated with tropical cyclones than have previous microwave temperature sounders. The gradient wind relationship suggests that the temperature gradient near the core of tropical cyclones increases nonlinearly with wind speed. We recast the gradient wind equation to include AMSU-A derived variables. Stepwise regression is used to determine which of these variables is most closely related to maximum sustained winds (V(sub max)). The satellite variables investigated include the radially averaged gradients at two spatial resolutions of AMSU-A channels 1 through 10 T(sub b) data (delta(sub r)T(sub b)), the squares of these gradients, a channel 15 based scattering index (SI-89), and area averaged T(sub b). Calculations of Tb and delta(sub r)T(sub b) from mesoscale model simulations of Andrew reveal the effects of the AMSU spatial sampling on the cyclone warm core presentation. Stepwise regression of 66 AMSU-A terms against National Hurricane Center (NHC) V(sub max) estimates from the 1998 and 1999 Atlantic hurricane season confirms the existence of a nonlinear relationship between wind speed and radially averaged temperature gradients near the cyclone warm core. Of six regression terms, four are dominated by temperature information, and two are interpreted as correcting for hydrometeor contamination. Jackknifed regressions were performed to estimate the algorithm performance on independent data. For the 82 cases that had in situ measurements of V(sub max), the average error standard deviation was 4.7 m/s. For 108 cases without in situ wind data, the average error standard deviation was 7.5 m/s. Operational considerations, including the detection of weak cyclones and false alarm reduction are also discussed.

Spencer, Roy↗
NASA NTRS2001

Atlantic Tropical Cyclone Monitoring with AMSU-A: Estimation of Maximum Sustained Wind Speeds

The first Advanced Microwave Sounding Unit temperature sounder (AMSU-A) was launched on the NOAA-15 satellite on 13 May 1998. The AMSU-A's higher spatial and radiometric resolutions provide more useful information on the strength of the middle- and upper-tropospheric warm cores associated with tropical cyclones than have previous microwave temperature sounders. The gradient wind relationship suggests that the temperature gradient near the core of tropical cyclones increases nonlinearly with wind speed. The gradient wind equation is recast to include AMSU-A-derived variables, Stepwise regression is used to determine which of these variables is most closely related to maximum sustained winds (V(sub max)). The satellite variables investigated include the radially averaged gradients at two spatial resolutions of AMSU-A channels 1-10 T(sub b) data (delta(sub r)T(sub B)), the squares of these gradients, a channel-15-based scattering index (SI(sub 89)), and area-averaged T(sub B). Calculations of T(sub B) and delta(sub r)T(sub B) from mesoscale model simulations of Andrew reveal the effects of the AMSU spatial sampling on the cyclone warm core presentation. Stepwise regression of 66 AMSU-A terms against National Hurricane Center V(sub max) estimates from the 1998 and 1999 Atlantic hurricane season confirms the existence of a nonlinear relationship between wind speed and radially averaged temperature gradients near the cyclone warm core. Of six regression terms, four are dominated by temperature information, and two are interpreted as correcting for hydrometeor contamination. Jackknifed regressions were performed to estimate the algorithm performance on independent data. For the 82 cases that had in situ measurements of V(sub max), the average error standard deviation was 4.7 m/s. For 108 cases without in situ wind data, the average error standard deviation was 7.5 m/s Operational considerations, including the detection of weak cyclones and false alarm reduction, are also discussed.

Spencer, Roy W.↗
NASA NTRS1990

Current Emergency Locator Transmitter (ELT) deficiencies and potential improvements utilizing TSO-C91a ELTs

An analysis was conducted of current ELT problems and potential improvements that could be made by employing the TSO-C91a ELTs to replace the current TSO-C91 ELTs. The scope of the study included the following: (1) validate the problems; (2) determine specific failure causes; (3) determine false alarm causes; (4) estimate improvements from TSO-C91a; (5) estimate benefits from replacement of the current ELTs; and (6) determine need and benefits for improved ELT inspection and maintenance. A detailed comparison between the two requirements documents (TSO-C91 and -91a) was made to assess improved performance of the ELT in each category of failure cause and each cause of false alarms. The comparison and analysis resulted in projecting a success of operation rate approximately 3 times the current rate and a reduction in false alarms to 0.25 of those generated by TSO-C91 ELTs. These improvements led to a projection of benefits of approximately 25 additional lives to be saved each year with TSO-C91a ELTs and an improved inspection and maintenance program.

Trudell, Bernard J.↗
NASA NTRS1979

Capabilities of radar as they might relate to entomological studies

A tutoral background of radar capabilities and its potential for insect research is provided. The basic principles and concepts of radar were reviewed. Information on current radar equipment was examined. Specific issues related to insect research included; target cross-section, radar frequency, tracking target recognition and false alarms, clutter reduction, radar transmitter power, and ascertained atmospheric processes.

Skolnik, M. I.↗
NASA NTRS2012

Optimization of Support Vector Machine (SVM) for Object Classification

The Support Vector Machine (SVM) is a powerful algorithm, useful in classifying data into species. The SVMs implemented in this research were used as classifiers for the final stage in a Multistage Automatic Target Recognition (ATR) system. A single kernel SVM known as SVMlight, and a modified version known as a SVM with K-Means Clustering were used. These SVM algorithms were tested as classifiers under varying conditions. Image noise levels varied, and the orientation of the targets changed. The classifiers were then optimized to demonstrate their maximum potential as classifiers. Results demonstrate the reliability of SVM as a method for classification. From trial to trial, SVM produces consistent results.

support vector machice (SVM)↗
NASA NTRS2009

Optimization of OT-MACH Filter Generation for Target Recognition

An automatic Optimum Trade-off Maximum Average Correlation Height (OT-MACH) filter generator for use in a gray-scale optical correlator (GOC) has been developed for improved target detection at JPL. While the OT-MACH filter has been shown to be an optimal filter for target detection, actually solving for the optimum is too computationally intensive for multiple targets. Instead, an adaptive step gradient descent method was tested to iteratively optimize the three OT-MACH parameters, alpha, beta, and gamma. The feedback for the gradient descent method was a composite of the performance measures, correlation peak height and peak to side lobe ratio. The automated method generated and tested multiple filters in order to approach the optimal filter quicker and more reliably than the current manual method. Initial usage and testing has shown preliminary success at finding an approximation of the optimal filter, in terms of alpha, beta, gamma values. This corresponded to a substantial improvement in detection performance where the true positive rate increased for the same average false positives per image.

false alarm reduction↗
DOE OSTI2025

The System for Classification of Low-Pressure Systems (SyCLoPS): An All-In-One Objective Framework for Large-Scale Data Sets

We propose the first unified objective framework (SyCLoPS) for detecting and classifying all types of low-pressure systems (LPSs) in a given data set. We use the state-of-the-art automated feature tracking software TempestExtremes (TE) to detect and track LPS features globally in ERA5 and compute 16 parameters from commonly found atmospheric variables for classification. A Python classifier is implemented to classify all LPSs at once. The framework assigns 16 different labels (classes) to each LPS data point and designates four different types of high-impact LPS tracks, including tracks of tropical cyclone (TC), monsoonal system, subtropical storm and polar low. The classification process involves disentangling high-altitude and drier LPSs, differentiating tropical and non-tropical LPSs using novel criteria, and optimizing for the detection of the four types of high-impact LPS. A comparison of our labels with those in the International Best Track Archive for Climate Stewardship (IBTrACS) revealed an overall accuracy of 95% in distinguishing between tropical systems, extratropical cyclones, and disturbances. SyCLoPS produces a better TC detection skill compared to the previous algorithms, highlighted by an approximately 6% reduction in the false alarm rate compared to the previous TE algorithm. The vertical cross section composite of the four types of high-impact LPS we detect each shows distinct structural characteristics. Finally, we demonstrate that SyCLoPS is valuable for investigating various aspects of LPSs in climate data, such as the evolution of a single LPS track, patterns of LPS frequencies, and precipitation or wind influence associated with a particular LPS class.

54 ENVIRONMENTAL SCIENCES↗
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 NTRS1987

A new approach to importance sampling for the simulation of false alarms

In this paper a modified importance sampling technique for improving the convergence of Importance Sampling is given. By using this approach to estimate low false alarm rates in radar simulations, the number of Monte Carlo runs can be reduced significantly. For one-dimensional exponential, Weibull, and Rayleigh distributions, a uniformly minimum variance unbiased estimator is obtained. For Gaussian distribution the estimator in this approach is uniformly better than that of previously known Importance Sampling approach. For a cell averaging system, by combining this technique and group sampling, the reduction of Monte Carlo runs for a reference cell of 20 and false alarm rate of lE-6 is on the order of 170 as compared to the previously known Importance Sampling approach.

Lu, D.↗
NASA NTRS2003

Concepts and Development of Bio-Inspired Distributed Embedded Wired/Wireless Sensor Array Architectures for Acoustic Wave Sensing in Integrated Aerospace Vehicles

This paper discusses the modeling of acoustic emissions in plate structures and their sensing by embedded or surface bonded piezoelectric sensor arrays. Three different modeling efforts for acoustic emission (AE) wave generation and propagation are discussed briefly along with their advantages and disadvantages. Continuous sensors placed at right angles on a plate are being discussed as a new approach to measure and locate the source of acoustic waves. Evolutionary novel signal processing algorithms and bio-inspired distributed sensor array systems are used on large structures and integrated aerospace vehicles for AE source localization and preliminary results are presented. These systems allow for a great reduction in the amount of data that needs to be processed and also reduce the chances of false alarms from ambient noises. It is envisioned that these biomimetic sensor arrays and signal processing techniques will be useful for both wireless and wired sensor arrays for real time health monitoring of large integrated aerospace vehicles and earth fixed civil structures. The sensor array architectures can also be used with other types of sensors and for other applications.

Ghoshal, Anindya↗
NASA NTRS2007

In Situ Multi-Species (O2, N2, Fuel, Other) Fiber Optic Sensor for Fuel Tank Ullage

A rugged and compact fiber optic sensor system for in situ real-time measurement of nitrogen (N2), oxygen (O2), hydrocarbon (HC) fuel vapors, and other gases has been developed over the past several years at Glenn Research Center. The intrinsically-safe, solid-state fiber optic sensor system provides a 1% precision measurement (by volume) of multiple gases in a 5-sec time window. The sensor has no consumable parts to wear out and requires less than 25 W of electrical power to operate. The sensor head is rugged and compact and is ideal for use in harsh environments such as inside an aircraft fuel tank, or as a feedback sensor in the vent-box of an on-board inert gas generation system (OBIGGS). Multiple sensor heads can be monitored with a single optical detection unit for a cost-effective multi-point sensor system. The present sensor technology is unique in its ability to measure N2 concentration directly, and in its ability to differentiate different types of HC fuels. The present sensor system provides value-added aircraft safety information by simultaneously and directly measuring the nitrogen-oxygen-fuel triplet, which provides the following advantages: (1) information regarding the extent of inerting by N2, (2) information regarding the chemical equivalence ratio, (3) information regarding the composition of the aircraft fuel, and (4) by providing a self-consistent calibration by utilizing a singular sensor for all species. Using the extra information made available by this sensor permits the ignitability of a fuel-oxidizer mixture to be more accurately characterized, which may permit a reduction in the amount of inerting required on a real-time basis, and yet still maintain a fire-safe fuel tank. This translates to an increase in fuel tank fire-safety through a better understanding of the physics of fuel ignition, and at the same time, a reduction in compressed bleed air usage and concomitant aircraft operational costs over the long-run. The present fiber optic sensor can also be used as a false-alarm-free engine/hidden/cargo space fire detector (by measuring increased CO2 and CO, and decreased O2), a multi-point in situ measurement and certification system for halogenated-compound fire protection systems, and for the testing and certification of other aircraft safety sensor systems. The technology (LEW-17826-1) developed in the present sensor system is patent pending.

Nguyen, Quang-Viet↗
NASA NTRS1988

Airborne radar technology for windshear detection

The objectives and accomplishments of the two-and-a-half year effort to describe how returns from on-board Doppler radar are to be used to detect the presence of a wind shear are reported. The problem is modeled as one of first passage in terms of state variables, the state estimates are generated by a bank of extended Kalman filters working in parallel, and the decision strategy involves the use of a voting algorithm for a series of likelihood ratio tests. The performance issue for filtering is addressed in terms of error-covariance reduction and filter divergence, and the performance issue for detection is addressed in terms of using a probability measure transformation to derive theoretical expressions for the error probabilities of a false alarm and a miss.

Hibey, Joseph L.↗