The Effects of Multipath on the Measurement of Antenna Time Delays
This paper describes the errors associated with measuring time delays of signals propagating through the primary path of a large Cassegrain antenna.
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This paper describes the errors associated with measuring time delays of signals propagating through the primary path of a large Cassegrain antenna.
Solar contamination, due to moonlight and atmospheric scattering of sunlight, can cause systematic errors in stellar radial velocity (RV) measurements that significantly detract from the ∼10 cm s{sup −1} sensitivity required for the detection and characterization of terrestrial exoplanets in or near habitable zones of Sun-like stars. The addition of low-level spectral contamination at variable effective velocity offsets introduces systematic noise when measuring velocities using classical mask-based or template-based cross-correlation techniques. Here we present simulations estimating the range of RV measurement error induced by uncorrected scattered sunlight contamination. We explore potential correction techniques, using both simultaneous spectrometer sky fibers and broadband imaging via coherent fiber imaging bundles, that could reliably reduce this source of error to below the photon-noise limit of typical stellar observations. We discuss the limitations of these simulations, the underlying assumptions, and mitigation mechanisms. We also present and discuss the components designed and built into the NEID (NN-EXPLORE Exoplanet Investigations with Doppler spectroscopy) precision RV instrument for the WIYN 3.5 m telescope, to serve as an ongoing resource for the community to explore and evaluate correction techniques. We emphasize that while “bright time” has been traditionally adequate for RV science, the goal of 10 cm s{sup −1} precision on the most interesting exoplanetary systems may necessitate access to darker skies for these next-generation instruments.
This software allows one to down-sample a measured surface map for model validation, not only without introducing any re-sampling errors, but also eliminating the existing measurement noise and measurement errors. The software tool of the current two new techniques can be used in all optical model validation processes involving large space optical surfaces
Solar contamination, due to moonlight and atmospheric scattering of sunlight, can cause systematic errors in stellar radial velocity (RV) measurements that significantly detract from the ~10 cm/s sensitivity required for the detection and characterization of terrestrial exoplanets in or near habitable zones of Sun-like stars. The addition of low-level spectral contamination at variable effective velocity offsets introduces systematic noise when measuring velocities using classical mask-based or template-based cross-correlation techniques. Here we present simulations estimating the range of RV measurement error induced by uncorrected scattered sunlight contamination. We explore potential correction techniques, using both simultaneous spectrometer sky fibers and broadband imaging via coherent fiber imaging bundles, that could reliably reduce this source of error to below the photon-noise limit of typical stellar observations. We discuss the limitations of these simulations, the underlying assumptions, and mitigation mechanisms. We also present and discuss the components designed and built into the NEID (NN-EXPLORE Exoplanet Investigations with Doppler spectroscopy) precision RV instrument for the WIYN 3.5m telescope, to serve as an ongoing resource for the community to explore and evaluate correction techniques. We emphasize that while “bright time” has been traditionally adequate for RV science, the goal of 10 cm/s precision on the most interesting exoplanetary systems may necessitate access to darker skies for these next generation instruments.
Doppler Global Velocimetry (DGV) is a new diagnostic tool that offers potential for flow field measurements in flight by acquiring three-component velocity data in near real-time during flight maneuvers. The feasibility of implementation of a flight DGV system aboard NASA's High-Angle-of-Attack Research Vehicle (HARV) was addressed in this work by identifying the essential characteristics of a flight measurement system and by performing calibration and error tests. Results from this work were: an outline that establishes a preliminary basis for system configurations by analyzing measurement errors, installation issues, and operating requirements; measurement of the accuracy of the DGV technique using a laboratory breadboard DGV system based on a frequency-doubled Nd: YAG laser and iodine Absorption Line Filter (ALF), which showed excellent agreement between the DGV data and pilot measurements on a laminar flow jet with velocities of up to 150 m/sec; a survey of DGV system components and technologies that are relevant to the design of a flight measurement system, including a survey of cameras for the next generation DGV receivers; an assessment of the candidate lasers and absorption line filters for the flight system, resulting in a near-term recommendation of Nd: host lasers and an iodine ALF for both flight and wind tunnel applications.
Advanced hemodynamic monitoring systems have provided less invasive methods for estimating pressure-derived measurements such as pressure-derived cardiac output (CO) measurements. These devices apply algorithms to arterial pressure waveforms recorded via pressure recording components that transmit the pressure signal to a pressure monitor. While standards have been developed for pressure monitoring equipment, it is unclear how the equipment-induced error can affect secondary measurements from pressure waveforms. We propose an approach for modelling different components of a pressure monitoring system and use this model-based approach to investigate the effect of different pressure recording configurations on pressure-derived hemodynamic measurements. The proposed model-based approach is a three-step process. (1) Modelling the response of pressure recording components using bench tests; (2) verifying the identified models through nonparametric equivalence tests; and (3) assessing the effects of pressure recording components on pressure-derived measurements. To delineate the application of this approach, we performed a series of model-based analyses to quantify the combined effect of a wide range of tubing configurations with various damping ratios and natural frequencies and monitors with different bandwidths on pressure waveforms and CO measurements by six pulse contour algorithms. Model-based results show the error in pressure-derived CO measurements because of tubing configurations with different natural frequencies and damping ratios. Tubing configurations with low natural frequencies (<23 Hz) altered characteristics of pressure waveforms in a way that affected the CO measurement, some by as much as 20%. Our method can serve as a tool to quantify the performance of pressure recording systems with different dynamic properties. In conclusion, this approach can be applied to investigate the effects of physiologic signal recording configurations on various pressure-derived hemodynamic measurements.
Obtaining bulk T requires measuring apparent sample interface T surface , knowledge of any window conditions T window , and knowledge of thermal transport from the sample to the window. To obtain bulk T with uncertainties below 5% requires relatively small uncertainties in each of these areas, and large uncertainties in one area require smaller uncertainties in others to maintain the error budget. For example, if T window is known to 10%, a 5% total uncertainty can be obtained if T surface is known to 1% and combined transport uncertainties are known to 20%. If T surface can only be measured to 2%, combined transport uncertainties must be 17% to reach the same overall uncertainty. As the form of transport is unknown at high pressure, and window temperatures are difficult to measure by their very nature, reducing surface T uncertainties is the practical first step. Here we will discuss various error sources in the measurement of apparent T surface , and which ones must be correctly obtained prior to the experiment.
Apollo spacecraft earth parking orbit error analysis using range rate and angle measurements
Theoretical and experimental determinations of the emittance of soils and leaves are reviewed, and an error analysis of emittance and spectral emittance measurements is developed as an aid to remote sensing applications. In particular, an equation for the upper bound of the absolute error in an emittance determination is derived. The absolute error is found to decrease with an increase in contact temperature and to increase with an increase in environmental integrated radiant flux density. The difference between temperature and band radiance temperature is plotted as a function of emittance for the wavelength intervals 4.5 to 5.5 microns, 8 to 13.5 microns and 10.2 to 12.5 microns.
Recent studies show that data from the Gravity Recovery and Climate Experiment (GRACE) is promising for basin- to global-scale water cycle research. This study provides varied assessments of errors associated with GRACE water storage estimates. Thirteen monthly GRACE gravity solutions from August 2002 to December 2004 are examined, along with synthesized GRACE gravity fields for the same period that incorporate simulated errors. The synthetic GRACE fields are calculated using numerical climate models and GRACE internal error estimates. We consider the influence of measurement noise, spatial leakage error, and atmospheric and ocean dealiasing (AOD) model error as the major contributors to the error budget. Leakage error arises from the limited range of GRACE spherical harmonics not corrupted by noise. AOD model error is due to imperfect correction for atmosphere and ocean mass redistribution applied during GRACE processing. Four methods of forming water storage estimates from GRACE spherical harmonics (four different basin filters) are applied to both GRACE and synthetic data. Two basin filters use Gaussian smoothing, and the other two are dynamic basin filters which use knowledge of geographical locations where water storage variations are expected. Global maps of measurement noise, leakage error, and AOD model errors are estimated for each basin filter. Dynamic basin filters yield the smallest errors and highest signal-to-noise ratio. Within 12 selected basins, GRACE and synthetic data show similar amplitudes of water storage change. Using 53 river basins, covering most of Earth's land surface excluding Antarctica and Greenland, we document how error changes with basin size, latitude, and shape. Leakage error is most affected by basin size and latitude, and AOD model error is most dependent on basin latitude.
Report discusses errors in range measurements in GPS system due to multipath transmissions originating at satellites. Large uncertainties in sizes of multipath errors limit precision of GPS measurements. Experiments proposed to determine systematic multipath errors under various operating conditions.
A nuclear power plant is instrumented with a variety of sensors that monitor its variables to estimate the state and initiate safety actions, if needed. We address the problem of estimating drifts or errors in sensor measurements due to factors such as calibration changes. We propose an information fusion method that uses measurements from other sensors to generate an estimate of a sensor measurement, and its difference from an actual measurement provides an error estimate. We present two fusers based on the ensemble of trees and support vector machine that are trained using sensor measurements collected at an emulated test loop of a pressurized water reactor under no-drift conditions. We present error estimates for a differential pressure sensor of the heat exchanger of the primary coolant system, under twenty controlled scenarios using the test loop. Both positive and negative errors are captured by both methods in scenarios involving calibration drifts, blocking, air gap and electromagnetic interference. The root mean square errors of estimated drifts are typically within 2% percent of the maximum.
Standing wave ultrasonic techniques for the measurement of very small changes in acoustic attenuation and phase velocity are discussed. Enhanced sensitivity to these small changes was achieved by making the specimen part of a composite ultrasonic resonator. It was found that a point of maximum sensitivity on the response of such an ultrasonic resonator need not coincide with a point of maximum signal-to-error ratio. A model is presented and analyzed which takes into account error due to long term (low frequency) noise effects such as gain drifts and dc level shifts. This model yields a quantitative value for the signal-to-error ratio in which the signal is defined as the ideal change in the monitored response and the error as the difference between the experimentally measured change and the signal. The specific frequency dependent forms for the ultrasonic response and the sensitivity enhancement factor were used to predict the operating point on a mechanical resonance corresponding to maximum signal-to-error ratio.
An outline is presented of a method in which a sensor under design can be evaluated by comparison with an existing sensor of similar spectral response, providing certain performance characteristics are known. An approach for calculating errors in radiance measurements is discussed, giving attention to calibration, error caused by resolution factors, noise effects on accuracy, and combined radiance level accuracies for several scanner designs. The derivation of error caused by the modulation transfer function is also considered.
The statistical error of the pointing angle estimation technique is determined as a function of the effective receiver signal to noise ratio. Other sources of error are addressed and evaluated with inadequate calibration being of major concern. The impact of pointing error on the computation of normalized surface scattering cross section (sigma) from radar and the waveform attitude induced altitude bias is considered and quantitative results are presented. Pointing angle and sigma processing algorithms are presented along with some initial data. The intensive mode clean vs. clutter AGC calibration problem is analytically resolved. The use clutter AGC data in the intensive mode is confirmed as the correct calibration set for the sigma computations.
The Gravity Recovery And Interior Laboratory (GRAIL) mission has constructed a lunar gravity field with unprecedented uniform accuracy on the farside and nearside of the Moon. GRAIL lunar gravity field determination begins with preprocessing of the gravity science measurements by applying corrections for time tag error, general relativity, measurement noise and biases. Gravity field determination requires the generation of spacecraft ephemerides of an accuracy not attainable with the pre-GRAIL lunar gravity fields. Therefore, a bootstrapping strategy was developed, iterating between science data preprocessing and lunar gravity field estimation in order to construct sufficiently accurate orbit ephemerides.This paper describes the GRAIL measurements, their dependence on the spacecraft ephemerides and the role of orbit determination in the bootstrapping strategy. Simulation results will be presented that validate the bootstrapping strategy followed by bootstrapping results for flight data, which have led to the latest GRAIL lunar gravity fields.
Advances in L-band microwave satellite radiometry in the past decade, pioneered by ESA's SMOS and NASA's Aquarius and SMAP missions, have demonstrated an unprecedented capability to observe global sea surface salinity (SSS) from space. Measurements from these missions are the only means to probe the very-near surface salinity (top cm), providing a unique monitoring capability for the interfacial exchanges of water between the atmosphere and the upper-ocean, and delivering a wealth of information on various salinity processes in the ocean, linkages with the climate and water cycle, including land-sea connections, and providing constraints for ocean prediction models. The satellite SSS data are complimentary to the existing in situ systems such as Argo that provide accurate depiction of large-scale salinity variability in the open ocean but under-sample mesoscale variability, coastal oceans and marginal seas, and energetic regions such as boundary currents and fronts. In particular, salinity remote sensing has proven valuable to systematically monitor the open oceans as well as coastal regions up to approximately 40 km from the coasts. This is critical to addressing societally relevant topics, such as land-sea linkages, coastal-open ocean exchanges, research in the carbon cycle, near-surface mixing, and air-sea exchange of gas and mass. In this paper, we provide a community perspective on the major achievements of satellite SSS for the aforementioned topics, the unique capability of satellite salinity observing system and its complementarity with other platforms, uncertainty characteristics of satellite SSS, and measurement versus sampling errors in relation to in situ salinity measurements. We also discuss the need for technological innovations to improve the accuracy, resolution, and coverage of satellite SSS, and the way forward to both continue and enhance salinity remote sensing as part of the integrated Earth Observing System in order to address societal needs.
In interferometry measurement, the retrace error often limits its high-precision metrology applications. Retrace error calibration with tilted flats can give a relation between the retrace error and the introduced tilt angles, but there is still an ambiguity between the introduced tilt angles and the tilt terms in the created retrace error. Here, we propose a novel, to the best of our knowledge, two-step calibration method to resolve this tilt ambiguity. It involves additional measurements of spherical mirror(s) with known curvature(s). The experiment shows that the curvature deviation due to the tilt ambiguity can be significantly reduced after applying the proposed method.