Search NASA⌕ Search

SEARCH · Search NASA

Results for “Sensing error”

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.

At least 361 records · Page 20
All sourcesNASA NTRSDOE OSTI
NASA NTRS2001

The Vertical Error Characteristics of GOES-derived Winds: Description and Impact on Numerical Weather Prediction

Errors in the height assignment of some satellite-derived winds exist because the satellites sense radiation emitted from a finite layer of the atmosphere rather than a specific level. Potential problems in data assimilation may arise because the motion of a measured layer is often represented by a single-level value. In this research, cloud and water vapor motion winds that are derived from the Geostationary Operational Environmental Satellites (GOES winds) are compared to collocated rawinsonde observations (RAOBs). An important aspect of this work is that in addition to comparisons at each assigned height, the GOES winds are compared to the entire profile of the collocated RAOB data to determine the vertical error characteristics of the GOES winds. The impact of these results on numerical weather prediction is then investigated. The comparisons at individual vector height assignments indicate that the error of the GOES winds range from approx. 3 to 10 m/s and generally increase with height. However, if taken as a percentage of the total wind speed, accuracy is better at upper levels. As expected, comparisons with the entire profile of the collocated RAOBs indicate that clear-air water vapor winds represent deeper layers than do either infrared or water vapor cloud-tracked winds. This is because in cloud-free regions the signal from water vapor features may result from emittance over a thicker layer. To further investigate characteristics of the clear-air water vapor winds, they are stratified into two categories that are dependent on the depth of the layer represented by the vector. It is found that if the vertical gradient of moisture is smooth and uniform from near the height assignment upwards, the clear-air water vapor wind tends to represent a relatively deep layer. The information from the comparisons is then used in numerical model simulations of two separate events to determine the forecast impacts. Four simulations are performed for each case: 1) A control simulation that assimilates no satellite wind data, 2) assimilation of all GOES winds according to their assigned single level height, 3) assimilation of all GOES winds spread over multiple levels, and 4) assimilation of all GOES winds spread over multiple levels, but with variations in the vertical influence of clear-air water vapor winds based on the moisture profile in the model. In the first case, a strong mid-latitude cyclone is present and the use of the satellite data results in improved storm tracks during the initial approx. 36 h forecast period. This is because the satellite data improves the analysis of the environment into which the storm progresses. Statistics for mean wind vector and height differences show that, with the exception of the height field at later times in the first case, the use of GOES winds improves the simulation with time. The simulation results suggest that it is beneficial to spread the GOES wind information over multiple levels, particularly when the moisture profile is used to define the vertical influence.

Rao, P. Anil↗
DOE OSTI2020

Integrating Radio-Over-Fiber Communication System and BOTDR Sensor System

In this paper, we propose and experimentally demonstrate for the first time, the integration of a radio-over-fiber (RoF) communication system and a Brillouin optical time-domain reflectometry (BOTDR) distributed sensor system using a single optical fiber link. In this proof-of-concept integrated system, the communication system is composed of three modulation formats of quadrature phase-shift keying (QPSK), 16-quadrature amplitude modulation (16-QAM) and 64-QAM, which are modulated onto an orthogonal frequency division multiplexing (OFDM) signal. Whereas, the BOTDR sensor system is used for strain and/or temperature monitoring over the fiber distance with a spatial resolution of 5 m using a 25 km single-mode silica fiber. The error vector magnitude (EVM) is analyzed in three modulation formats in the presence of various BOTDR input pump powers. Using QPSK modulation, optimized 18 dBm sensing and 10 dBm data power, the measured EVM values with and without bandpass filter are 3.5% and 14.5%, respectively. The proposed system demonstrates a low temperature measurement error (±0.49 °C at the end of 25 km) and acceptable EVM values, which were within the 3GPP requirements. The proposed integrated system can be effectively applied for practical applications, which significantly reduces the fiber infrastructure cost by effective usage of a single optical fiber link.

42 ENGINEERING↗
NASA NTRS2006

Use of In Situ Cloud Condensation Nuclei, Extinction, and Aerosol Size Distribution Measurements to Test a Method for Retrieving Cloud Condensation Nuclei Profiles From Surface Measurements

If the aerosol composition and size distribution below cloud are uniform, the vertical profile of cloud condensation nuclei (CCN) concentration can be retrieved entirely from surface measurements of CCN concentration and particle humidification function and surface-based retrievals of relative humidity and aerosol extinction or backscatter. This provides the potential for long-term measurements of CCN concentrations near cloud base. We have used a combination of aircraft, surface in situ, and surface remote sensing measurements to test various aspects of the retrieval scheme. Our analysis leads us to the following conclusions. The retrieval works better for supersaturations of 0.1% than for 1% because CCN concentrations at 0.1% are controlled by the same particles that control extinction and backscatter. If in situ measurements of extinction are used, the retrieval explains a majority of the CCN variance at high supersaturation for at least two and perhaps five of the eight flights examined. The retrieval of the vertical profile of the humidification factor is not the major limitation of the CCN retrieval scheme. Vertical structure in the aerosol size distribution and composition is the dominant source of error in the CCN retrieval, but this vertical structure is difficult to measure from remote sensing at visible wavelengths.

Ghan, Stephen J.↗
NASA NTRS2010

A Systematic Approach for Model-Based Aircraft Engine Performance Estimation

A requirement for effective aircraft engine performance estimation is the ability to account for engine degradation, generally described in terms of unmeasurable health parameters such as efficiencies and flow capacities related to each major engine module. This paper presents a linear point design methodology for minimizing the degradation-induced error in model-based aircraft engine performance estimation applications. The technique specifically focuses on the underdetermined estimation problem, where there are more unknown health parameters than available sensor measurements. A condition for Kalman filter-based estimation is that the number of health parameters estimated cannot exceed the number of sensed measurements. In this paper, the estimated health parameter vector will be replaced by a reduced order tuner vector whose dimension is equivalent to the sensed measurement vector. The reduced order tuner vector is systematically selected to minimize the theoretical mean squared estimation error of a maximum a posteriori estimator formulation. This paper derives theoretical estimation errors at steady-state operating conditions, and presents the tuner selection routine applied to minimize these values. Results from the application of the technique to an aircraft engine simulation are presented and compared to the estimation accuracy achieved through conventional maximum a posteriori and Kalman filter estimation approaches. Maximum a posteriori estimation results demonstrate that reduced order tuning parameter vectors can be found that approximate the accuracy of estimating all health parameters directly. Kalman filter estimation results based on the same reduced order tuning parameter vectors demonstrate that significantly improved estimation accuracy can be achieved over the conventional approach of selecting a subset of health parameters to serve as the tuner vector. However, additional development is necessary to fully extend the methodology to Kalman filter-based estimation applications.

Simon, Donald L.↗
DOE OSTI2018

The NSLS-II Components Relative Alignment Deviation Estimate

The alignment of NSLS-II components will be conducted under the constraint of survey control network. The control network system is categorized as outside, primary and secondary control networks, and all of them have random errors due to measurement random errors. In the error propagation point of view, they all will contribute to the final positioning accuracy of each component in global sense. However, as the global positioning requirement is relative loose (i.e. ± 3mm for storage ring), relative positioning accuracy is what we really concern. In this situation, only secondary control network will contribute as only secondary monuments will be employed to direct the adjustment of components. Other error sources include instrument setup error, adjustment residuals and slab movement etc. This article will analyze the maximum relative deviation of 3 positions in one cell’s region, which is a simulation of 1 ID and 2 Vacuum chamber positions.

43 PARTICLE ACCELERATORS↗
NASA NTRS2011

On the Accuracy of Double Scattering Approximation for Atmospheric Polarization Computations

Interpretation of multi-angle spectro-polarimetric data in remote sensing of atmospheric aerosols require fast and accurate methods of solving the vector radiative transfer equation (VRTE). The single and double scattering approximations could provide an analytical framework for the inversion algorithms and are relatively fast, however accuracy assessments of these approximations for the aerosol atmospheres in the atmospheric window channels have been missing. This paper provides such analysis for a vertically homogeneous aerosol atmosphere with weak and strong asymmetry of scattering. In both cases, the double scattering approximation gives a high accuracy result (relative error approximately 0.2%) only for the low optical path - 10(sup -2) As the error rapidly grows with optical thickness, a full VRTE solution is required for the practical remote sensing analysis. It is shown that the scattering anisotropy is not important at low optical thicknesses neither for reflected nor for transmitted polarization components of radiation.

Korkin, Sergey V.↗
NASA NTRS2001

Effects of the Ionosphere on Passive Microwave Remote Sensing of Ocean Salinity from Space

Among the remote sensing applications currently being considered from space is the measurement of sea surface salinity. The salinity of the open ocean is important for understanding ocean circulation and for modeling energy exchange with the atmosphere. Passive microwave remote sensors operating near 1.4 GHz (L-band) could provide data needed to fill the gap in current coverage and to complement in situ arrays being planned to provide subsurface profiles in the future. However, the dynamic range of the salinity signal in the open ocean is relatively small and propagation effects along the path from surface to sensor must be taken into account. In particular, Faraday rotation and even attenuation/emission in the ionosphere can be important sources of error. The purpose or this work is to estimate the magnitude of these effects in the context of a future remote sensing system in space to measure salinity in L-band. Data will be presented as a function of time location and solar activity using IRI-95 to model the ionosphere. The ionosphere presents two potential sources of error for the measurement of salinity: Rotation of the polarization vector (Faraday rotation) and attenuation/emission. Estimates of the effect of these two phenomena on passive remote sensing over the oceans at L-band (1.4 GHz) are presented.

LeVine, D. M.↗
NASA NTRS1983

Initialization of mesoscale models - The possible impact of remotely sensed data

Little or no improvement appears to have been achieved in mesoscale numerical prediction. This has been blamed on inherent unpredictability, insufficient spatial resolution, inadequate parameterization of important physical processes, and errors in the numerical discretization of the governing hydrodynamic equations. Attention is presently given to the more fundamental difficulty of forecasting when present conditions are not known with sufficient accuracy, and to the matching of remotely sensed sounding-capability satellite and all-weather Doppler radar data with mesoscale numerical models. This matching is not straightforward; simple and variational forms of four-dimensional assimilation, and Kalman filtering, are suggested approaches but their practical testing remains to be accomplished. The most severe problem faced is that of the temperature and humidity profiles' vertical resolution.

Gal-Chen, T.↗
NASA NTRS2004

Target Selection and Imaging Requirements for JWST Fine Phasing

To achieve and maintain the fine alignment of its segmented primary mirror the James Webb Space Telescope (JWST) plans to use focus-diverse wavefront sensing (WFS) techniques with science camera imagery. The optical requirements for JWST are such that the error contribution from the WFS itself must be limited 10nm rms over all the controllable degrees of freedom of the telescope. In this paper, we will explore the requirements on the target selection and imaging requirements necessary to achieve the desired level of WFS accuracy. Using Monte Carlo simulations we explore the WFS error as a function of wavefront aberrations level, defocus-diversity level, optical bandwidth and imaging signal-to-noise ratio to establish the key imaging requirements. By taking into account practical integration time limits along with the distribution of the defocused point-spread functions, we establish the bright and faint star magnitude limits suitable for WFS target selection.

wavefront sensing↗
DOE OSTI2018

New fractional derivatives applied to the Korteweg–de Vries and Korteweg–de Vries–Burger’s equations

In this paper, we extend the model of the Korteweg–de Vries (KDV) and Korteweg–de Vries–Burger’s (KDVB) to new model time fractional Korteweg–de Vries (TFKDV) and time fractional Korteweg–de Vries-Burger’s (TFKDVB) with Liouville–Caputo (LC), Caputo–Fabrizio (CF), and Atangana-Baleanu (AB) fractional time derivative equations, respectively. We utilize the q-homotopy analysis transform method (q-HATM) to compute the approximate solutions of TFKDV and TFKDVB using LC, CF and AB in Liouville–Caputo sense. We study the convergence analysis of q-HATM by computing the Residual Error Function (REF) and finding the interval of the convergence through the h-curves. Also, we find the optimal values of h so that, we assure the convergence of the approximate solutions. The results are very effective and accurate in solving the TFKDV and TFKDVB.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1979

Ambiguity resolution for satellite Doppler positioning systems

The implementation of satellite-based Doppler positioning systems frequently requires the recovery of transmitter position from a single pass of Doppler data. The least-squares approach to the problem yields conjugate solutions on either side of the satellite subtrack. It is important to develop a procedure for choosing the proper solution which is correct in a high percentage of cases. A test for ambiguity resolution which is the most powerful in the sense that it maximizes the probability of a correct decision is derived. When systematic error sources are properly included in the least-squares reduction process to yield an optimal solution the test reduces to choosing the solution which provides the smaller valuation of the least-squares loss function. When systematic error sources are ignored in the least-squares reduction, the most powerful test is a quadratic form comparison with the weighting matrix of the quadratic form obtained by computing the pseudoinverse of a reduced-rank square matrix. A formula for computing the power of the most powerful test is provided. Numerical examples are included in which the power of the test is computed for situations that are relevant to the design of a satellite-aided search and rescue system.

Argentiero, P.↗
NASA NTRS1983

Flexible Coupling Corrects Shaft Misalinements

Proposed flexible coupling provides nearly error free measurements of shaft rotation in presence of misalinements between shaft and position sensing transducer. Intended to be used in situations in which input or output shaft is mounted on flexible joint. Its function is to insure equal input and output angular velocities by forcing input and output shafts to remain parallel.

Mayo, R. A.↗
NASA NTRS1990

Software compensated multichannel pressure sensing system

A PC-based software system is described which can be used for data acquisition and thermal-error correction of a multichannel pressure-sensor system developed for use in a cryogenic environment. The software incorporates pressure-sensitivity and sensor-offset compensation files into thermal error-correction algorithms, and the sensors are calibrated by simulating the operating conditions. The system is found to be effective in the collecting, storing, and processing of multichannel pressure-sensor data to correct thermally induced offset and sensitivity errors.

Chapman, John J.↗
NASA NTRS2003

Stochastic Models of Tropical Rain-Rate Fields

Because of the extreme variability of rain rate in space and time and the difficulties with remote sensing methods of measuring rain rates, accurate determination of rainfall over large areas and time periods has long been a problem for hydrologists, meteorogists, and climatologists. A number of statistical models of rain have been developed in order to investigate the impact of rain variability on satellite remote sensing methods, validation of satellite rain products, and generation of rain maps with accompanying error estimates. These models may be useful in examining 'sub-grid scale' issues in representing precipitation in numerical mdoels. A stochastic model will first be described which can generate time-dependent high-resolution spatial rain fields with space and time correlations similar to those seen in rain data, as well as representing the presence of areas with zero rain rate and log-normally distributed rain rates where there is rain. A simpler model derived from this, formulated in the spectral domain, seems to imply fractal-like rain statistics at small scales when fit to rain data.

Bell, Thomas L.↗
NASA NTRS2017

WFIRST coronagraph optical modeling

End-to-end numerical optical modeling of the WFIRST coronagraph incorporating wavefront sensing and control is used to determine the performance of the coronagraph with realistic errors, including pointing jitter and polarization. We present the performance estimates of the current flight designs as predicted by modeling. We also describe the release of a new version of the PROPER optical propagation library, our primary modeling tool, which is now available for Python and Matlab in addition to IDL.

Zhou, Hanying↗
NASA NTRS1991

Reliable fusion of control and sensing in intelligent machines

Although robotics research has produced a wealth of sophisticated control and sensing algorithms, very little research has been aimed at reliably combining these control and sensing strategies so that a specific task can be executed. To improve the reliability of robotic systems, analytic techniques are developed for calculating the probability that a particular combination of control and sensing algorithms will satisfy the required specifications. The probability can then be used to assess the reliability of the design. An entropy formulation is first used to quickly eliminate designs not capable of meeting the specifications. Next, a framework for analyzing reliability based on the first order second moment methods of structural engineering is proposed. To ensure performance over an interval of time, lower bounds on the reliability of meeting a set of quadratic specifications with a Gaussian discrete time invariant control system are derived. A case study analyzing visual positioning in robotic system is considered. The reliability of meeting timing and positioning specifications in the presence of camera pixel truncation, forward and inverse kinematic errors, and Gaussian joint measurement noise is determined. This information is used to select a visual sensing strategy, a kinematic algorithm, and a discrete compensator capable of accomplishing the desired task. Simulation results using PUMA 560 kinematic and dynamic characteristics are presented.

Mcinroy, John E.↗
NASA NTRS1999

Remote Sensing of Aerosol and their Radiative Forcing of Climate

Remote sensing of aerosol and aerosol radiative forcing of climate is going through a major transformation. The launch in next few years of new satellites designed specifically for remote sensing of aerosol is expected to further revolutionized aerosol measurements: until five years ago satellites were not designed for remote sensing of aerosol. Aerosol optical thickness was derived as a by product, only over the oceans using one AVHRR channel with errors of approx. 50%. However it already revealed a very important first global picture of the distribution and sources of aerosol. In the last 5 years we saw the introduction of polarization and multi-view observations (POLDER and ATSR) for satellite remote sensing of aerosol over land and ocean. Better products are derived from AVHRR using its two channels. The new TOMS aerosol index shows the location and transport of aerosol over land and ocean. Now we anticipate the launch of EOS-Terra with MODIS, MISR and CERES on board for multi-view, multi-spectral remote sensing of aerosol and its radiative forcing. This will allow application of new techniques, e.g. using a wide spectral range (0.55-2.2 microns) to derive precise optical thickness, particle size and mass loading. Aerosol is transparent in the 2.2 microns channel, therefore this channel can be used to detect surface features that in turn are used to derive the aerosol optical thickness in the visible part of the spectrum. New techniques are developed to derive the aerosol single scattering albedo, a measure of absorption of sunlight, and techniques to derive directly the aerosol forcing at the top of the atmosphere. In the last 5 years a global network of sun/sky radiometers was formed, designed to communicate in real time the spectral optical thickness from 50-80 locations every day, every 15 minutes. The sky angular and spectral information is also measured and used to retrieve the aerosol size distribution, refractive index, single scattering albedo and the spectral flux reaching the surface. Effort to introduce remote sensing from lidars will literally additional dimension to aerosol remote sensing. The vertical dimension is a critical link between the global satellite observations and modeling of aerosol transport. Lidars are also critical to study aerosol impact on cloud microphysics and reflectance. Both lidar ground networks and satellite systems are in development. This new capability is expected to put remote sensing in the forefront of aerosol and climate studies. Together with field experiments, chemical analysis and chemical transport models we anticipate, in the next decade, to be able to resolve some of the outstanding questions regarding the role of aerosol in climate, in atmospheric chemistry and its influence on human health and life on this planet.

Kaufman, Yoram J.↗
NASA NTRS1991

Probable errors in width distributions of sea ice leads measured along a transect

The degree of error expected in the measurement of widths of sea ice leads along a single transect are examined in a probabilistic sense under assumed orientation and width distributions, where both isotropic and anisotropic lead orientations are examined. Methods are developed for estimating the distribution of 'actual' widths (measured perpendicular to the local lead orientation) knowing the 'apparent' width distribution (measured along the transect), and vice versa. The distribution of errors, defined as the difference between the actual and apparent lead width, can be estimated from the two width distributions, and all moments of this distribution can be determined. The problem is illustrated with Landsat imagery and the procedure is applied to a submarine sonar transect. Results are determined for a range of geometries, and indicate the importance of orientation information if data sampled along a transect are to be used for the description of lead geometries. While the application here is to sea ice leads, the methodology can be applied to measurements of any linear feature.

Key, J.↗