SEARCH · Search NASA
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.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
Methods for obtaining the probability density function of random signal combustions are discussed. These methods provide a realistic criteria for the design of control systems subjected to external noise with several important applications for aerospace problems.
Signal enhancement techniques are described using recently developed digital adaptive filtering equipment. Adaptive filtering concepts are not new; however, as a result of recent advances in microprocessor-based electronics, hardware has been developed that has stable characteristics and of a size exceeding 1000th order. Selected data processing examples are presented illustrating spectral line enhancement, adaptive noise cancellation, and transfer function estimation in the presence of corrupting noise.
The noise due to finite-word-length effects is analyzed for digital-signal power processors using Welch's power-spectrum estimation technique to measure the power of Gaussian random signals over a frequency band of interest. The input of the digital signal processor contains a finite-length time interval in which the true Gaussian signal is contaminated by Gaussian noise. The roundoff noise-to-signal ratio in the measurement of the signal power is derived, and computer simulations which validate the analytical results are presented. These results can be used in tradeoff studies of hardware design, such as the number of bits required at each processing stage. The results presented in this paper are currently being used in the design of a digital Doppler processor (Chi et al., 1986) for a radar scatterometer.
Absorption bands between 300 nm and 315 nm were observed in spectral scans of the atmospheric albedo made by the Solar Backscatter Ultraviolet (SBUV) spectrometer following the eruption of El Chichon. It is shown that those bands coincide with peaks in the absorption coefficient spectrum of SO sub 2. The magnitude of the absorption is used to the column content of present SO sub 2. These observations confirm that the differential absorption between 312.5 nm and 317.5 nm in Total Ozone Mapping Spectrometer (TOMS) data can be used to measure SO sub 2 with high spatial resolution. A maximum concentration of SO sub 2 of 15 matm-cm was observed by SBUV on April 15, 1982. The measurement based on direct measurement of band intensity can be used to calibrate the TOMS algorithm for deriving SO sub 2 amounts.
Explore the source record for details and available documents.
An instrument for measuring the lifetime of luminescence (fluorescence or phosphorescence) includes a digital signal processor (DSP) as the primary means of control, generation of excitation signals, and analysis of response signals. The DSP hardware in the present instrument makes it possible to switch among a variety of operating modes by making changes in software only.
Explore the source record for details and available documents.
Explore the source record for details and available documents.
As the number of Phasor Measurement Units (PMUs) deployed in power systems increases, so do the archives of synchrophasor measurements stored by utilities. Significant value can be extracted from these archives by using them to support studies such as frequency response analysis, small-signal stability analysis, and power plant model validation. To better enable utilities to perform these studies, the open-source Archive Walker tool was developed. This tool examines PMU data for grid disturbances and periods of interest. Once identified, the data can be further analyzed inside Archive Walker or exported to specialty tools. In this paper, the various disturbance detectors available in Archive Walker are described, and its interactions with other openly-available tools are highlighted.
We present AviSense, an SDR-based real-time, versatile system for monitoring aviation bands. AviSense detects and characterizes signal activities to enable practical and effective anomaly detection. We identify and tackle the challenges posed by a diverse set of critical aviation bands and technologies. We evaluate our methodology with real-world aviation signal measurements and demonstrate that we can classify aviation signals as normal with 99% accuracy. We also provide an exhaustive evaluation of our anomalous signal detection capability and show that we can accurately classify anomalous signals with 99% accuracy, with few exceptions. We also demonstrate that AviSense can effectively distinguish between different types of anomalies. We build a prototype implementation of AviSense for distributed monitoring.
Abstract not provided.
This report was a followup to, Collection and Analysis of Specific ELINT Signal Parameters, DTIC A166507, 23 June 1985. The programs and hardware assembled for the above mentioned report were used to analyze two types of radar, the PPS-6 and the HOOD radars. The typical ELINT parameters of frequency, pulse width, and pulse repetition rate were collected and analyzed.
An overview is given of the data acquisition, signal processing, and data analysis techniques that are currently in use with high power MST/ST (mesosphere stratosphere troposphere/stratosphere troposphere) radars. This review supplements the works of Rastogi (1983) and Farley (1984) presented at previous MAP workshops. A general description is given of data acquisition and signal processing operations and they are characterized on the basis of their disparate time scales. Then signal coding, a brief description of frequently used codes, and their limitations are discussed, and finally, several aspects of statistical data processing such as signal statistics, power spectrum and autocovariance analysis, outlier removal techniques are discussed.
Results are presented of analysis of satellite signal characteristics as influenced by ocean surface roughness and an investigation of sea truth data requirements. The first subject treated is that of postflight waveform reconstruction for the Skylab S-193 radar altimeter. Sea state estimation accuracies are derived based on analytical and hybrid computer simulation techniques. An analysis of near-normal incidence, microwave backscattering from the ocean's surface is accomplished in order to obtain the minimum sea truth data necessary for good agreement between theoretical and experimental scattering results. Sea state bias is examined from the point of view of designing an experiment which will lead to a resolution of the problem. A discussion is given of some deficiencies which were found in the theory underlying the Stilwell technique for spectral measurements.
This document will describe the principles of the Signal Variation Flow Technique, and the uncertainty models generated using it. We focus on the capture of the variation between the ideal signal and the measured signal. The ideal signal is defined to represent the signal output of a system whose full state behavior is known, with no variation in environment or during operation, and whose photons trajectories are not modified by the object. A CT uncertainty analysis is the result of two main steps. First, the radiography regime extends from the source to the collected image, which is 2D in the case of standard CT. This maps all upstream uncertainties into the variation observed on the radiograph and captures all variation in the physical domain. Second, the reconstruction regime extends from the captured images to the reconstructed 3D image. This regime is purely in the mathematical domain and corrects reconstruction algorithm artifacts/anomalies. The present work focuses on building the model through the radiography regime. The reconstruction regime is expected to be largely a study of algorithmic sensitivity, requiring the definition of a range of standardized tests through which the algorithms would be run. Radiographic variation would then be mapped through reconstruction sensitivities to predict the signal variation in the final image. An incomplete list for the reconstructed image variation output basis includes voxel density, edge blur and length variation, in analogous fashion to the basis functions presented in this work. The signal variation occurs in several forms at the radiograph. These forms are gathered into a complete basis set of functions describing all variation on the radiograph. The scale of each basis function is calculated independently via a specific SVFG. This includes 0D pixel noise (0DI), 0D energy noise (0DE), 1D blur (1DB), 1D length (1DL) or 2D position (2DP). These models are orthogonal in that they each explore a space in the signal variation domain that cannot be reached by the other basis functions. The variation basis functions, and associated SVFG models are split by output dimensionality, a term loosely used for categorization, and explained further below.
The signal-to-noise ratio performance of the Hadamard imaging technique is analyzed and an experimental evaluation of a laboratory Hadamard imager is presented. A comparison between the performances of Hadamard and conventional imaging techniques shows that the Hadamard technique is superior only when the imaging objective lens is required to have an effective F (focus) number of about 2 or slower.
Work on the reduction and analysis of Dynamics Explorer (DE) satellite magnetometer data with special emphasis on the ULF fluctuations and waves evident in such data is described. Research focused on the following: (1) studies of Pc 1 wave packets near the plasmapause; (2) satellite-ground pulsation study; (3) support for studies of ion energization processes; (4) search for Pc 1 wave events in 1981 DE 1 data; (5) study of Pc 3-5 events observed simultaneously by DE 1 and by AMPTE CCE; (6) support for studies of electromagnetic transients on DE 1; and (7) analysis of wave events induced by sudden impulses.
A theoretical analysis is presented for the evaluation of correlation functions of many spatially separated noise sources in a jet. A one-dimensional model is considered in which the noise sources are located on the axis of the jet downstream of the nozzle. The theory for extracting the spatial distribution from far field cross-correlations by signal analysis is derived. The advantage of this method is that difficult numerical inversions are not needed.