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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 73 records · Page 4
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NASA NTRS1984

Electromagnetic bias of 10-GHz radar altimeter measurements of MSL

Electromagnetic bias, the small difference that exists between the radar measured mean sea level and the geometric mean sea level is an important issue in high precision satellite altimetry. Present day satellite altimetry has achieved, with SEASAT-1, a precision of 5 cm rms in the range measurement. Future altimeter designs are expected to improve the range measurement precision to cm rms. In order to exploit the capability of these precise radar altimeters are marine geodesy and oceanography, it is necessary to understand and account for all of the known biases in the range measurement. The electromagnetic bias or the EM bias, which has been attributed to the observed fact that ocean wave troughs tend to be better reflectors of nadir viewing microwave radar energy than ocean wave crests, can be observed with high resolution airborne radar. This report presents the results of the EM bias measurements made by NRL using an airborne radar altimeter operating at 10 GHz with a 1 ns range resolution. Data were taken for various sea states and wind conditions. The experimental results are compared with current theories.

Choy, L. W.↗
NASA NTRS1987

Report of the Special Panel on statistical particle bias problems in laser anemometry

An account is given of the findings contained in a concensus document compiled by a group of experts on laser anemometry concerning statistical particle bias and its possible remedies. Emphasis is placed on the systematic character of this bias, rather than its magnitude. Since bias errors are a function of flow velocity and turbulence intensity, the measured results may contain apparent trends due solely to the measurement process. Attention is given to the panel's attempt to clear up terminological confusions in the matter of rates, scales, and magnitudes, as well as to its suggested processing methods for the elimination of velocity bias and the remedy of angle bias.

Edwards, Robert V.↗
NASA NTRS1990

A laboratory study of the electromagnetic bias of rough surface scattering by water waves

The design, development, and use of a focused-beam radar to measure the electromagnetic bias introduced by the scattering of radar waves by a roughened water surface are discussed. The bias measurements were made over wide ranges of environmental conditions in a wavetank laboratory. Wave-elevation data were provided by standard laboratory capacitance probes. Backscattered radar power measurements coincident in time and space with the elevation data were produced by the radar. The two data sets are histogrammed to produce probability density functions for elevation and radar reflectivity, from which the electromagnetic bias is computed. The experimental results demonstrate that the electromagnetic bias is quite variable over the wide range of environmental conditions that can be produced in the laboratory. The data suggest that the bias is dependent upon the local wind field and on the amplitude and frequency of any background wave field that is present.

Parsons, Chester L.↗
NASA NTRS1991

Frequency dependence of electromagnetic bias in radar altimeter sea surface range measurements

Range measurements made by satellite radar altimeters experience a bias toward the troughs of ocean waves. A series of aircraft flights during February-April 1989 measured this electromagnetic (EM) bias at three radar frequencies and the UV under a variety of wind and wave conditions, and provided the first airborne open-ocean measurements at the 13.6-GHz and 5.3-GHz operating frequencies of the NASA altimeter on the TOPEX/Poseidon satellite. The data suggest that the mean EM bias decreases linearly with increasing radar frequency between 5.3 and 36 GHz, according to the expression: EM bias (percent of significant wave height) = (3.0-0.0617 F)(1 +/-0.5), where F is in gigahertz. EM bias is fairly constant over a mesoscale region on a given day but can fluctuate significantly from one day to another. It shows a strong increase at all radar frequencies with increasing wind speed, although other sea state conditions, such as the wind direction relative to the wave direction, are also factors.

Walsh, E. J.↗
NASA NTRS1991

A laboratory investigation of electromagnetic bias in sea level measurements by microwave altimeters

To contribute to a better understanding of the electromagnetic bias in radar altimetry, a series of experiments was conducted using a focused beam radar set at 13.5-GHz frequency. For pure wind wave fields, the authors found the bias to be a quadratic function of each of the commonly used parameters, namely, the significant wave height, the wind speed, the water elevation skewness, and significant slope. The bias divided by the significant wave height is a linear function of these parameters. The coefficients in bias representation as a function of either the significant wave height or the wind speed are significantly different from values obtained in field experiments. This led to the conclusion that none of the latter parameters can be taken solely to account for all observed bias variations. Instead, dimensionless parameters such as the wave skewness or a dimensionless wave height are shown to be more appropriate.

Branger, H.↗
NASA NTRS1992

On the nature of bias and defects in the software specification process

Implementation bias in a specification is an arbitrary constraint in the solution space. This paper describes the problem of bias. Additionally, this paper presents a model of the specification and design processes describing individual subprocesses in terms of precision/detail diagrams and a model of bias in multi-attribute software specifications. While studying how bias is introduced into a specification we realized that software defects and bias are dual problems of a single phenomenon. This was used to explain the large proportion of faults found during the coding phase at the Software Engineering Laboratory at NASA/GSFC.

Straub, Pablo A.↗
NASA NTRS1993

Electromagnetic bias in sea surface range measurements at frequencies of the TOPEX/POSEIDON satellite

Measurements of EM bias at the 13.6 GHz and 5.3 GHz operating frequencies of the NASA altimeter on the TOPEX/POSEIDON satellite in a series of 11 aircraft flights from January 17, 1991 through March 4, 1991, during the Surface Wave Dynamics Experiment, are reported. The data are consistent with an earlier set of airborne measurements and indicate that EM bias is slightly higher at 5.3 GHz than at 13.6 GHz, and that the magnitudes of both biases increase with increasing wind speed, as does their difference. With some exceptions, EM bias shows little variation over a mesoscale region on a given day or within 1 or 2 h, but it can change significantly over a 6-h period. Recent tower, airborne, and satellite measurements exhibit a consistency in the characteristics of the wind speed dependence but suggest that there may be a height dependence in the determinations, with the bias decreasing with increasing altitude.

Hevizi, Laszlo G.↗
NASA NTRS1994

Power spectrum, correlation function, and tests for luminosity bias in the CfA redshift survey

We describe and apply a method for directly computing the power spectrum for the galaxy distribution in the extension of the Center for Astrophysics Redshift Survey. Tests show that our technique accurately reproduces the true power spectrum for k greater than 0.03 h Mpc(exp -1). The dense sampling and large spatial coverage of this survey allow accurate measurement of the redshift-space power spectrum on scales from 5 to approximately 200 h(exp -1) Mpc. The power spectrum has slope n approximately equal -2.1 on small scales (lambda less than or equal 25 h(exp -1) Mpc) and n approximately -1.1 on scales 30 less than lambda less than 120 h(exp -1) Mpc. On larger scales the power spectrum flattens somewhat, but we do not detect a turnover. Comparison with N-body simulations of cosmological models shows that an unbiased, open universe CDM model (OMEGA h = 0.2) and a nonzero cosmological constant (CDM) model (OMEGA h = 0.24, lambda(sub zero) = 0.6, b = 1.3) match the CfA power spectrum over the wavelength range we explore. The standard biased CDM model (OMEGA h = 0.5, b = 1.5) fails (99% significance level) because it has insufficient power on scales lambda greater than 30 h(exp -1) Mpc. Biased CDM with a normalization that matches the Cosmic Microwave Background (CMB) anisotropy (OMEGA h = 0.5, b = 1.4, sigma(sub 8) (mass) = 1) has too much power on small scales to match the observed galaxy power spectrum. This model with b = 1 matches both Cosmic Background Explorer Satellite (COBE) and the small-scale power spect rum but has insufficient power on scales lambda approximately 100 h(exp -1) Mpc. We derive a formula for the effect of small-scale peculiar velocities on the power spectrum and combine this formula with the linear-regime amplification described by Kaiser to compute an estimate of the real-space power spectrum. Two tests reveal luminosity bias in the galaxy distribution: First, the amplitude of the pwer spectrum is approximately 40% larger for the brightest 50% of galaxies in volume-limited samples that have M(sub lim) greater than M*. This bias in the power spectrum is independent of scale, consistent with the peaks-bias paradigm for galaxy formation. Second, the distribution of local density around galaxies shows that regions of moderate and high density contain both very bright (M less than M* = -19.2 + 5 log h) and fainter galaxies, but that voids preferentially harbor fainter galaxies (approximately 2 sigma significance level).

Park, Changbom↗
NASA NTRS1994

Estimating urban temperature bias using polar-orbiting satellite data

Urban temperature bias, defined to be the difference between a shelter temperature reading of unknown but suspected urban influence and some appropriate rural reference temperature, is estimated through the use of polar-orbiting satellite data. Predicted rural temperatures, based on a method developed using sounding data, are shown to be of reasonable accuracy in many cases for urban bias assessments using minimum temperature data from selected urban regions in the United States in July 1989. Assessments of predicted urban bias were based on comparisons with observed bias, as well as independent measures of urban heat island influence, such as population statistics and urban-rural differences in a vegetation index. This technique provides a means of determining urban bias in regions where few if any rural reference stations are available, or where inhomogeneities exist in land surface characteristics or rural station locations.

Johnson, Gregory L.↗
NASA NTRS1994

Bias properties of extragalactic distance indicators. 3: Analysis of Tully-Fisher distances for the Mathewson-Ford-Buchhorn sample of 1355 galaxies

The observational selection bias properties of the large Mathewson-Ford-Buchhorn (MFB) sample of axies are demonstrated by showing that the apparent Hubble constant incorrectly increases outward when determined using Tully-Fisher (TF) photometric distances that are uncorreted for bias. It is further shown that the value of H(sub 0) so determined is also multivlaued at a given redshift when it is calculated by the TF method using galaxies with differenct line widths. The method of removing this unphysical contradiction is developed following the model of the bias set out in Paper II. The model developed further here shows that the appropriate TF magnitude of a galaxy that is drawn from a flux-limited catalog not only is a function of line width but, even in the most idealistic cases, requires a triple-entry correction depending on line width, apparent magnitude, and catalog limit. Using the distance-limited subset of the data, it is shown that the mean intrinsic dispersion of a bias-free TF relation is high. The dispersion depends on line width, decreasing from sigma(M) = 0.7 mag for galaxies with rotational velocities less than 100 km s(exp-1) to sigma(M) = 0.4 mag for galaxies with rotational velocities greater than 250 km s(exp-1). These dispersions are so large that the random errors of the bias-free TF distances are too gross to detect any peculiar motions of individual galaxies, but taken together the data show again the offset of 500 km s(exp-1) fond both by Dressler & Faber and by MFB for galaxies in the direction of the putative Great Attractor but described now in a different way. The maximum amplitude of the bulk streaming motion at the Local Group is approximately 500 km s(exp-1) but the perturbation dies out, approaching the Machian frame defined by the CMB at a distance of approximately 80 Mpc (v is approximately 4000 km s(exp -1)). This decay to zero perturbation at v is approximately 4000 km s(exp -1) argues against existing models with a single attraction at approximately 4500 km s(exp -1) (the Great Attactor model) pulling the local region. Rather, the cause of the perturbation appears to be the well-known clumpy mass distribution within 4000 km s(exp -1) in the busy directions of Hydra, Centaurus, Antila and Dorado, as postulated earlier (Tammann & Sandage 1985).

Federspiel, Martin↗
NASA NTRS1996

An Evaluation of Attitude-Independent Magnetometer-Bias Determination Methods

Although several algorithms now exist for determining three-axis magnetometer (TAM) biases without the use of attitude data, there are few studies on the effectiveness of these methods, especially in comparison with attitude dependent methods. This paper presents the results of a comparison of three attitude independent methods and an attitude dependent method for computing TAM biases. The comparisons are based on in-flight data from the Extreme Ultraviolet Explorer (EUVE), the Upper Atmosphere Research Satellite (UARS), and the Compton Gamma Ray Observatory (GRO). The effectiveness of an algorithm is measured by the accuracy of attitudes computed using biases determined with that algorithm. The attitude accuracies are determined by comparison with known, extremely accurate, star-tracker-based attitudes. In addition, the effect of knowledge of calibration parameters other than the biases on the effectiveness of all bias determination methods is examined.

Hashmall, J. A.↗
NASA NTRS1992

Queries for Bias Testing

Selecting a good bias prior to concept learning can be difficult. Therefore, dynamic bias adjustment is becoming increasingly popular. Current dynamic bias adjustment systems, however, are limited in their ability to identify erroneous assumptions about the relationship between the bias and the target concept. Without proper diagnosis, it is difficult to identify and then remedy faulty assumptions. We have developed an approach that makes these assumptions explicit, actively tests them with queries to an oracle, and adjusts the bias based on the test results.

Gordon, Diana F.↗
NASA NTRS1998

Adaptive Variable Bias Magnetic Bearing Control

Most magnetic bearing control schemes use a bias current with a superimposed control current to linearize the relationship between the control current and the force it delivers. With the existence of the bias current, even in no load conditions, there is always some power consumption. In aerospace applications, power consumption becomes an important concern. In response to this concern, an alternative magnetic bearing control method, called Adaptive Variable Bias Control (AVBC), has been developed and its performance examined. The AVBC operates primarily as a proportional-derivative controller with a relatively slow, bias current dependent, time-varying gain. The AVBC is shown to reduce electrical power loss, be nominally stable, and provide control performance similar to conventional bias control. Analytical, computer simulation, and experimental results are presented in this paper.

Johnson, Dexter↗
NASA NTRS2001

Investigating Uncertainty in Predicting Carbon Dynamics in North American Biomes: Putting Support-Effect Bias in Perspective

A fundamental strategy in NASA's Earth Observing System's (EOS) monitoring of vegetation and its contribution to the global carbon cycle is to rely on deterministic, process-based ecosystem models to make predictions of carbon flux over large regions. These models are parameterized (that is, the input variables are derived) using remotely sensed images such as those from the Moderate Resolution Imaging Spectroradiometer (MODIS), ground measurements and interpolated maps. Since early applications of these models, investigators have noted that results depend partly on the spatial support of the input variables. In general, the larger the support of the input data, the greater the chance that the effects of important components of the ecosystem will be averaged out. A review of previous work shows that using large supports can cause either positive or negative bias in carbon flux predictions. To put the magnitude and direction of these biases in perspective, we must quantify the range of uncertainty on our best measurements of carbon-related variables made on equivalent areas. In other words, support-effect bias should be placed in the context of prediction uncertainty from other sources. If the range of uncertainty at the smallest support is less than the support-effect bias, more research emphasis should probably be placed on support sizes that are intermediate between those of field measurements and MODIS. If the uncertainty range at the smallest support is larger than the support-effect bias, the accuracy of MODIS-based predictions will be difficult to quantify and more emphasis should be placed on field-scale characterization and sampling. This talk will describe methods to address these issues using a field measurement campaign in North America and "upscaling" using geostatistical estimation and simulation.

Dungan, Jennifer L.↗
NASA NTRS2002

A Coupled Nonlinear Spacecraft Attitude Controller and Observer with an Unknown Gyro Misalignment and Gyro Bias

A nonlinear control scheme for attitude control of a spacecraft is combined with a nonlinear gyro misalignment and bias observer for the case of constant gyro misalignment and bias. A persistency of excitation analysis shows the observer gyro bias estimates converge to the true bias values exponentially fast. The convergence of the misalignment estimates is also presented. Then; the resulting coupled, closed loop dynamics are proven by a Lyapunov analysis to be globally stable, with asymptotically perfect tracking. The analysis is extended to consider the effects of noise in addition to the gyro misalignment and bias. A simulation of the proposed observer-controller design is given for a rigid spacecraft tracking a specified, time-varying attitude sequence to illustrate the theoretical claims.

Thienel, Julie↗
NASA NTRS2006

Biases in Total Precipitable Water Vapor Climatologies from Atmospheric Infrared Sounder and Advanced Microwave Scanning Radiometer

We examine differences in total precipitable water vapor (PWV) from the Atmospheric Infrared Sounder (AIRS) and the Advanced Microwave Scanning Radiometer (AMSR-E) experiments sharing the Aqua spacecraft platform. Both systems provide estimates of PWV over water surfaces. We compare AIRS and AMSR-E PWV to constrain AIRS retrieval uncertainties as functions of AIRS retrieved infrared cloud fraction. PWV differences between the two instruments vary only weakly with infrared cloud fraction up to about 70%. Maps of AIRS-AMSR-E PWV differences vary with location and season. Observational biases, when both instruments observe identical scenes, are generally less than 5%. Exceptions are in cold air outbreaks where AIRS is biased moist by 10-20% or 10-60% (depending on retrieval processing) and at high latitudes in winter where AIRS is dry by 5-10%. Sampling biases, from different sampling characteristics of AIRS and AMSR-E, vary in sign and magnitude. AIRS sampling is dry by up to 30% in most high-latitude regions but moist by 5-15% in subtropical stratus cloud belts. Over the northwest Pacific, AIRS samples conditions more moist than AMSR-E by a much as 60%. We hypothesize that both wet and dry sampling biases are due to the effects of clouds on the AIRS retrieval methodology. The sign and magnitude of these biases depend upon the types of cloud present and on the relationship between clouds and PWV. These results for PWV imply that climatologies of height-resolved water vapor from AIRS must take into consideration local meteorological processes affecting AIRS sampling.

Atmospheric Infrared Sounder (AIRS)↗
NASA NTRS1978

Bias structure to efficiently package a magnetic bubble domain device

A single, compact bias structure to efficiently package a plurality of magnetic bubble domain device chips having different bias requirements. The vertical magnetic field distribution within the bias structure air gap is selectively controlled by a magnetically soft field adjusting assembly suitably attached within the bias structure. The size and configuration of the field adjusting assembly tailors local field variations within the air gap to correspond with the bias requirements of the bubble domain chips disposed therein.

Chen, Thomas T.↗
NASA NTRS2010

Single-Receiver GPS Phase Bias Resolution

Existing software has been modified to yield the benefits of integer fixed double-differenced GPS-phased ambiguities when processing data from a single GPS receiver with no access to any other GPS receiver data. When the double-differenced combination of phase biases can be fixed reliably, a significant improvement in solution accuracy is obtained. This innovation uses a large global set of GPS receivers (40 to 80 receivers) to solve for the GPS satellite orbits and clocks (along with any other parameters). In this process, integer ambiguities are fixed and information on the ambiguity constraints is saved. For each GPS transmitter/receiver pair, the process saves the arc start and stop times, the wide-lane average value for the arc, the standard deviation of the wide lane, and the dual-frequency phase bias after bias fixing for the arc. The second step of the process uses the orbit and clock information, the bias information from the global solution, and only data from the single receiver to resolve double-differenced phase combinations. It is called "resolved" instead of "fixed" because constraints are introduced into the problem with a finite data weight to better account for possible errors. A receiver in orbit has much shorter continuous passes of data than a receiver fixed to the Earth. The method has parameters to account for this. In particular, differences in drifting wide-lane values must be handled differently. The first step of the process is automated, using two JPL software sets, Longarc and Gipsy-Oasis. The resulting orbit/clock and bias information files are posted on anonymous ftp for use by any licensed Gipsy-Oasis user. The second step is implemented in the Gipsy-Oasis executable, gd2p.pl, which automates the entire process, including fetching the information from anonymous ftp

Bertiger, William I.↗