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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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At least 19 records

Star Confusion Effect on SIM PlanetQuest Astrometric Performance

SIM PlanetQuest will measure star positions to an accuracy of a few microarcseconds using precise white light fringe measurements. One challenge for SIM observation scenario is "star confusion," where multiple stars are present in the instrument field of view. This is especially relevant for observing dim science targets because the density of number of stars increases rapidly with star magnitude. We study the effect of star confusion on the SIM astrometric performance due to systematic fringe errors caused by the extra photons from the confusion star(s}. Since star confusion from multiple stars may be analyzed as a linear superposition of the effect from single star confusion, we quantify the astrometric errors due to single star confusion surveying over many spectral types, including AOV, FOV, K5III, and MOV, and for various visual magnitude differences. To the leading order, the star confusion effect is characterized by the magnitude difference, spectral difference, and the angular separation between the target and confusion stars.Strategies for dealing with star confusion are presented. For example, since the presence of additional sources in the field of view leads to inconsistent delay estimates from different channels, with sufficient signal to noise ratio, the star confusion can be detected using chi-square statistics of fringe measurements from multiple spectral channels. An interesting result is that the star confusion can be detected even though the interferometer cannot resolve the separation between the target and confusion stars when their spectra are sufficiently different. Other strategies for mitigating the star confusion effect are also discussed.

crowded field↗

A Formal Methods Approach to the Analysis of Mode Confusion

The goal of the new NASA Aviation Safety Program (AvSP) is to reduce the civil aviation fatal accident rate by 80% in ten years and 90% in twenty years. This program is being driven by the accident data with a focus on the most recent history. Pilot error is the most commonly cited cause for fatal accidents (up to 70%) and obviously must be given major consideration in this program. While the greatest source of pilot error is the loss of situation awareness , mode confusion is increasingly becoming a major contributor as well. The January 30, 1995 issue of Aviation Week lists 184 incidents and accidents involving mode awareness including the Bangalore A320 crash 2/14/90, the Strasbourg A320 crash 1/20/92, the Mulhouse-Habsheim A320 crash 6/26/88, and the Toulouse A330 crash 6/30/94. These incidents and accidents reveal that pilots sometimes become confused about what the cockpit automation is doing. Consequently, human factors research is an obvious investment area. However, even a cursory look at the accident data reveals that the mode confusion problem is much deeper than just training deficiencies and a lack of human-oriented design. This is readily acknowledged by human factors experts. It seems that further progress in human factors must come through a deeper scrutiny of the internals of the automation. It is in this arena that formal methods can contribute. Formal methods refers to the use of techniques from logic and discrete mathematics in the specification, design, and verification of computer systems, both hardware and software. The fundamental goal of formal methods is to capture requirements, designs and implementations in a mathematically based model that can be analyzed in a rigorous manner. Research in formal methods is aimed at automating this analysis as much as possible. By capturing the internal behavior of a flight deck in a rigorous and detailed formal model, the dark corners of a design can be analyzed. This paper will explore how formal models and analyses can be used to help eliminate mode confusion from flight deck designs and at the same time increase our confidence in the safety of the implementation. The paper is based upon interim results from a new project involving NASA Langley and Rockwell Collins in applying formal methods to a realistic business jet Flight Guidance System (FGS).

Butler, Ricky W.↗

Analytic Confusion Matrix Bounds for Fault Detection and Isolation Using a Sum-of-Squared- Residuals Approach

Given a system which can fail in 1 or n different ways, a fault detection and isolation (FDI) algorithm uses sensor data in order to determine which fault is the most likely to have occurred. The effectiveness of an FDI algorithm can be quantified by a confusion matrix, which i ndicates the probability that each fault is isolated given that each fault has occurred. Confusion matrices are often generated with simulation data, particularly for complex systems. In this paper we perform FDI using sums of squares of sensor residuals (SSRs). We assume that the sensor residuals are Gaussian, which gives the SSRs a chi-squared distribution. We then generate analytic lower and upper bounds on the confusion matrix elements. This allows for the generation of optimal sensor sets without numerical simulations. The confusion matrix bound s are verified with simulated aircraft engine data.

Simon, Dan↗

(abstract) An All Sky Cirrus Confusion Noise Map for WIRE

The Wide Field Infrared Explorer (WIRE) is a Small Explorer (SMEX) satellite scheduled for launch in 1998 which will carry out a sky survey of at least 100 square degrees in the wavelength regions of 9-15(micro)m and 21-27(micro)m with spatial resolution of approximately 20 arcsec and sensitivity exceeding 0.6mJy. At this sensitivity level WIRE observations can be seriously affected by the confusion noise contribution from the infrared cirrus emission, so the WIRE survey must be planned with some knowledge of the expected level of cirrus confusion. Production of a cirrus confusion noise map with 0.5 degree resolution based on the spatial power spectral density of the cirrus emission in the IRAS ISSA data is in progess using the method described by Gauthier, et al. Spectrally resolved power spectra density data is obtained from the ISSA maps with a wavelet transform technique.

Wide Field Infrared Explorer WIRE infrared sky sur↗

The confusion limits to the sensitivity of submillimeter telescopes

The two major sources of confusion that limit the sensitivity of continuum observations at submillimeter wavelengths outside the galactic plane are discussed. One of the sources is the spatial structure of the thermal emission from dust in the Milky Way. The crowding of extragalactic sources at faint levels is the second source of confusion. Estimates of the noise expected from these two types of confusion as a function of wavelength and beam size on the sky are presented and compared to detector and photon noise estimates for proposed spaceborne telescopes.

Helou, George↗

Detecting Mode Confusion Through Formal Modeling and Analysis

Aircraft safety has improved steadily over the last few decades. While much of this improvement can be attributed to the introduction of advanced automation in the cockpit, the growing complexity of these systems also increases the potential for the pilots to become confused about what the automation is doing. This phenomenon, often referred to as mode confusion, has been involved in several accidents involving modern aircraft. This report describes an effort by Rockwell Collins and NASA Langley to identify potential sources of mode confusion through two complementary strategies. The first is to create a clear, executable model of the automation, connect it to a simulation of the flight deck, and use this combination to review of the behavior of the automation and the man-machine interface with the designers, pilots, and experts in human factors. The second strategy is to conduct mathematical analyses of the model by translating it into a formal specification suitable for analysis with automated tools. The approach is illustrated by applying it to a hypothetical, but still realistic, example of the mode logic of a Flight Guidance System.

Miller, Steven P.↗

Analyzing Mode Confusion via Model Checking

Mode confusion is one of the most serious problems in aviation safety. Today's complex digital flight decks make it difficult for pilots to maintain awareness of the actual states, or modes, of the flight deck automation. NASA Langley leads an initiative to explore how formal techniques can be used to discover possible sources of mode confusion. As part of this initiative, a flight guidance system was previously specified as a finite Mealy automaton, and the theorem prover PVS was used to reason about it. The objective of the present paper is to investigate whether state-exploration techniques, especially model checking, are better able to achieve this task than theorem proving and also to compare several verification tools for the specific application. The flight guidance system is modeled and analyzed in Murphi, SMV, and Spin. The tools are compared regarding their system description language, their practicality for analyzing mode confusion, and their capabilities for error tracing and for animating diagnostic information. It turns out that their strengths are complementary.

Luettgen, Gerald↗

Spectral Confusion for Cosmological Surveys of Redshifted C II Emission

Far-infrared cooling lines are ubiquitous features in the spectra of star-forming galaxies. Surveys of redshifted fine-structure lines provide a promising new tool to study structure formation and galactic evolution at redshifts including the epoch of reionization as well as the peak of star formation. Unlike neutral hydrogen surveys, where the 21 cm line is the only bright line, surveys of redshifted fine-structure lines suffer from confusion generated by line broadening, spectral overlap of different lines, and the crowding of sources with redshift. We use simulations to investigate the resulting spectral confusion and derive observing parameters to minimize these effects in pencilbeam surveys of redshifted far-IR line emission. We generate simulated spectra of the 17 brightest far-IR lines in galaxies, covering the 150-1300 μm wavelength region corresponding to redshifts 0 < z < 7, and develop a simple iterative algorithm that successfully identifies the 158 μm [C II] line and other lines. Although the [C II] line is a principal coolant for the interstellar medium, the assumption that the brightest observed lines in a given line of sight are always [C II] lines is a poor approximation to the simulated spectra once other lines are included. Blind line identification requires detection of fainter companion lines from the same host galaxies, driving survey sensitivity requirements. The observations require moderate spectral resolution 700 < R < 4000 with angular resolution between 20″ and 10′, sufficiently narrow to minimize confusion yet sufficiently large to include a statistically meaningful number of sources.

galactic evolution at redshifts↗

A calculation of confusion noise due to infrared cirrus

General expressions are developed for the statistical errors to be expected in photometric measurements due to confusion in a background of fluctuating surface brightness. Backgrounds actually observed in the far IR by the IRAS satellite are used to calculate tables of these error expressions for two simple measurement techniques. The confusion-noise-limited sensitivities for NASA's planned Space IR Telescope Facility and the ESA's IR Space Observatory are estimated at a wavelength of 100 microns from these tables.

Gautier, T. N., III↗

Confusion Noise Level Due to Galactic and Extragalactic Binaries

We have revised our earlier rough estimate of the combined galactic and extragalactic binary confusion noise level curve for gravitational waves. This was done to correct some numerical errors and to allow for roughly three frequency bins worth of information about weaker sources being lost for each galactic binary signal that is removed from the data. The results are still based on the spectral amplitude estimates for different types of galactic binaries reported by Hils et al in 1990, and assume that the gravitational wave power spectral densities for other galaxies are proportional to the optical luminosities. The estimated confusion noise level drops to the LISA instrumental noise level at between roughly 3 and 8 MHz.

Bender, Peter L.↗

Econometric models for predicting confusion crop ratios

Results for both the United States and Canada show that econometric models can provide estimates of confusion crop ratios that are more accurate than historical ratios. Whether these models can support the LACIE 90/90 accuracy criterion is uncertain. In the United States, experimenting with additional model formulations could provide improved methods models in some CRD's, particularly in winter wheat. Improved models may also be possible for the Canadian CD's. The more aggressive province/state models outperformed individual CD/CRD models. This result was expected partly because acreage statistics are based on sampling procedures, and the sampling precision declines from the province/state to the CD/CRD level. Declining sampling precision and the need to substitute province/state data for the CD/CRD data introduced measurement error into the CD/CRD models.

Umberger, D. E.↗

Eta Car: The Good, the Bad and the Ugly of Nebular and Stellar Confusion

Observations in the far-UV provide a unique opportunity to investigate the very massive star Eta Car and its hot binary companion, Eta Car B. Eta Car was observed with FUSE over a large portion of the 5.54 year spectroscopic period before and after the 2003.5 minimum. The observed spectrum is defined by strong stellar wind signatures, primarily from Eta Car A, complicated by the strong absorptions of the ejecta surrounding Eta Car plus interstellar absorption. The Homunculus and Little Homunculus are massive bipolar ejecta historically associable with LBV outbursts in the 1840s and the 1890s and are linked to absorptions at -513 and -146 km/s, respectively. The FUSE spectra are confused by the extended nebulosity and thermal drifting of the FUSE co-pointed instruments. Interpretation is further complicated by two B-stars sufficiently close to h Car to be included most of the time in the large FUSE aperture. Followup observations partially succeeded in obtaining spectra of at least one of these B-stars through the smaller apertures, allowing potential separation of the B-star contributions and h Car. A complete analysis of all available spectra is currently underway. Our ultimate goals are to directly detect the hot secondary star if possible with FUSE and to identify the absorption contributions to the overall spectrum especially of the stellar members and the massive ejecta.

Gull, T.R.↗

Some confusion factors in radar image interpretation

Geologic interpretation of radar imagery for land use applications is discussed with reference to its dependence on classification of the radar return into categories related to some training area within the image. It is shown that such interpretation relies on the assumption that surface characteristics of areas with similar returns are truly similar. It is further shown that this may not always be true over water surfaces due to the influence of system parameters on the radar return. In imagery over land, both system parameters and scene parameters may lead to ambiguous returns which can ultimately lead to misinterpretation.

Blanchard, B. J.↗

A temporal/spectral analysis of small grain crops and confusion crops

Spectral data from the LANDSAT-2 satellite were used to study the growth cycles of fields of wheat, barley, alfalfa, corn, sunflowers, soybeans, rye, flax, oats, millet, grass, and hay. Signatures of pastures, trees, and idle fallow were also studied. The growth cycles were portrayed in the form of temporal plots of the greeness-brightness transformation vector applied to average channel pixel values within the fields, all of which were in three counties in North Dakota. The plots of each crop reveal characteristics which can be used in crop classification procedures.

Johnson, W. R.↗

Einstein observations of the confused 2A 2315-428 region

Four distinct X-ray sources have been detected by the Einstein Observatory imaging proportional counter in the 2A2315-428 field. The strongest source in the 0.2-3.8 keV band is associated with the Sersic 159-03 cluster, which contains a cD galaxy, and may account for as much as 40% of the observed 2A flux. The rest of the flux is suspected to issue from the weaker but more heavily cut-off galaxy NGC 7582. It is suggested that such a large X-ray absorption column density in NGC 7582 may account for the absence of a broad H-alpha emission component, as has been observed in other narrow-line X-ray galaxies. The weak X-ray flux from NGC 7552 shows together with a reanalysis of previous observations, that the source is not variable, that its X-ray emission is not likely to result from a compact nucleus, and that it may be a starburst galaxy.

Charles, P. A.↗

A simulation study of scene confusion factors in sensing soil moisture from orbital radar

Simulated C-band radar imagery for a 124-km by 108-km test site in eastern Kansas is used to classify soil moisture. Simulated radar resolutions are 100 m by 100 m, 1 km by 1km, and 3 km by 3 km. Distributions of actual near-surface soil moisture are established daily for a 23-day accounting period using a water budget model. Within the 23-day period, three orbital radar overpasses are simulated roughly corresponding to generally moist, wet, and dry soil moisture conditions. The radar simulations are performed by a target/sensor interaction model dependent upon a terrain model, land-use classification, and near-surface soil moisture distribution. The accuracy of soil-moisture classification is evaluated for each single-date radar observation and also for multi-date detection of relative soil moisture change. In general, the results for single-date moisture detection show that 70% to 90% of cropland can be correctly classified to within +/- 20% of the true percent of field capacity. For a given radar resolution, the expected classification accuracy is shown to be dependent upon both the general soil moisture condition and also the geographical distribution of land-use and topographic relief. An analysis of cropland, urban, pasture/rangeland, and woodland subregions within the test site indicates that multi-temporal detection of relative soil moisture change is least sensitive to classification error resulting from scene complexity and topographic effects.

Ulaby, F. T.↗