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A Trilateration Scheme for Relative Positioning

We introduce a trilateration scheme that evaluates the 3-dimensional (3-D) relative position between a reference spacecraft and a target spacecraft using raw-range measurements from a distance baseline of known locations, which we call “anchors”. The anchors can be antennas of a ground-based network (e.g., Deep Space Network (DSN) or Near Earth Network (NEN) stations), or satellites of a spacebased network (e.g., global positioning system (GPS) or tracking and data relay satellite (TDRS)). We define raw-range as the range that includes all the systematic errors that occur during range measurements. A unique feature of this approach is that accurate relative position is derived from a “differencing function” of raw-range measurements of the reference spacecraft and target spacecraft, thereby eliminating most of the systematic errors, such as media effects, ephemeris errors, instrument delays, clock bias, etc. There can be an arbitrary number of target spacecraft, and relative positioning of target spacecraft with respect to the reference spacecraft can be done simultaneously. In this paper, we first assume an idealized system in which clocks on the reference and target spacecraft are synchronized, with clocks of the anchors synchronized as well. We develop a novel iterative algorithm that computes the relative position of the target spacecraft with respect to the reference spacecraft. We illustrate the relative positioning method using the scenario of a network of three ground stations (i.e., the anchors) at Goldstone, California, USA, Madrid, Spain, and Marlargue, Argentina tracking two spacecraft at geosynchronous orbit distance. We demonstrate that the algorithm converges to submeter accuracy in estimating the relative position, in the presence of random errors and systematic errors in raw-range measurements, and in the presence of angular errors in estimating the pointing vectors between the anchors and the reference spacecraft. Next, we relax the requirement of perfect time synchronization between spacecraft, and show that by using an additional anchor, one can estimate and remove the clock biases between the reference and target spacecraft. We add a ground station at Kourou to the above example of three ground stations of Goldstone, Madrid, and Marlargue, and demonstrate that the updated algorithm also converges to meter-level accuracy (submeter in some cases) in the presence of clock biases in addition to the random errors, systematic errors, and angular errors as shown in the above case. We compare this scheme with a similar trilateration scheme for relative positioning scheme first proposed by Montenbruck in 2002.

Cheung, Kar-Ming

Characterization of OCO-2 and ACOS-GOSAT biases and errors for flux estimates

We characterize the magnitude of seasonally and spatially varying biases in the National Aeronautics and Space Administration (NASA) Orbiting Carbon Observatory-2 (OCO-2) Version 8 (v8) and the Atmospheric CO2 Observations from Space (ACOS) Greenhouse Gas Observing SATellite (GOSAT) version 7.3 (v7.3) satellite CO2 retrievals by comparisons to measurements collected by the Total Carbon Column Observing Network (TCCON), Atmospheric Tomography (ATom) experiment, and National Oceanic and Atmospheric Administration (NOAA) Earth System Research Laboratory (ESRL) and U. S. Department of Energy (DOE) aircraft, and surface stations. Although the ACOS-GOSAT estimates of the column averaged carbon dioxide (CO2) dry air mole fraction (XCO2) have larger random errors than the OCO-2 XCO2 estimates, and the space-based estimates over land have larger random errors than those over ocean, the systematic errors are similar across both satellites and surface types, 0.6 ± 0.1 ppm. We find similar estimates of systematic error whether dynamic versus geometric coincidences or ESRL/DOE aircraft versus TCCON are used for validation (over land), once validation and co-location errors are accounted for. We also find that areas with sparse throughput of good quality data (due to quality flags and preprocessor selection) over land have ~double the error of regions of high-throughput of good quality data. We characterize both raw and bias-corrected results, finding that bias correction improves systematic errors by a factor of 2 for land observations and improves errors by ~0.2 ppm for ocean. We validate the lowermost tropospheric (LMT) product for OCO-2 and ACOS-GOSAT by comparison to aircraft and surface sites, finding systematic errors of ~1.1 ppm, while having 2-3 times the variability of XCO2. We characterize the time and distance scales of correlations for OCO-2 XCO2 errors, and find error correlations on scales of 0.3 degrees, 5-10 degrees, and 60 days. We find comparable scale lengths for the bias correction term. Assimilation of the OCO-2 bias correction term is used to estimate flux errors resulting from OCO-2 seasonal biases, finding annual flux errors on the order of 0.3 and 0.4 PgC/yr for Transcom-3 ocean and land regions, respectively.

Susan S Kulawik

Random and systematic measurement errors in acoustic impedance as determined by the transmission line method

The effect of random and systematic errors associated with the measurement of normal incidence acoustic impedance in a zero-mean-flow environment was investigated by the transmission line method. The influence of random measurement errors in the reflection coefficients and pressure minima positions was investigated by computing fractional standard deviations of the normalized impedance. Both the standard techniques of random process theory and a simplified technique were used. Over a wavelength range of 68 to 10 cm random measurement errors in the reflection coefficients and pressure minima positions could be described adequately by normal probability distributions with standard deviations of 0.001 and 0.0098 cm, respectively. An error propagation technique based on the observed concentration of the probability density functions was found to give essentially the same results but with a computation time of about 1 percent of that required for the standard technique. The results suggest that careful experimental design reduces the effect of random measurement errors to insignificant levels for moderate ranges of test specimen impedance component magnitudes. Most of the observed random scatter can be attributed to lack of control by the mounting arrangement over mechanical boundary conditions of the test sample.

Parrott, T. L.

A measurement of the Hubble constant from the X-ray properties and the Sunyaev-Zel'dovich effect of Abell 2218

The distance of the cluster of galaxies Abell 2218, and hence the value of the Hubble constant, has been measured by comparing the X-ray properties and the Sunyaev-Zel'dovich effect of the cluster. The result for the Hubble constant is H(sub zero) = 65 +/- 25 km/s/MPC, where the error includes the random and systematic errors, combined in quadrature, and the largest contributions to the overall error come from systematic errors in the Sunyaev-Zel'dovich effect data and in the X-ray spectrum of the cluster. The X-ray and Sunyaev-Zel'dovich effect data are consistent with the same model for the intergalactic medium in Abell 2218 (an isothermal Beta-model with Beta is about 0.65 and cluster core radius about 1.0 min). A prevous report of a smaller Hubble constant, found by applying the same method on the same cluster, is shown to be based on a model for the cluster gas that is inconsistent with the Einstein IPC data. The present result for the Hubble constant is consistent with the value found earlier for the cluster Abell 665: by combining the results of the method for both clusters we conclude that the value of the Hubble constant is H(sub zero) = 55 +/- 17 km/s/MPC.

Birkinshaw, M.

Algorithms for isolating worst case systematic data errors

Two separate algorithms are derived for testing filter sensitivity to systematic data errors. One algorithm provides the absolute minimum Euclidean norm data error for a given estimate component error. The second algorithm can be used to find the minimum norm data error which can be generated by restricted degree Legendre polynomials. A specific very long baseline interferometry (VLBI) baseline estimation is analyzed with the algorithm. It is found that the local vertical is the most sensitive component to error in the data space. The efficiency of a data error sequence linear in elevation angle is within 7% that of the absolute worst case sequence. Elevation angle dependent errors are explored and the special case of a mismodeled troposphere is treated.

Curkendall, D. W.

A 1 percent measurement of the temperature of the cosmic microwave radiation at lambda = 1.2 centimeters

Results are reported of a direct measurement of the cosmic microwave radiation temperature using a special Dicke radiometer (wavelength = 1.2 cm) designed to minimize the usual systematic errors. The experiment was performed at balloon altitudes to avoid atmospheric emission. The first flight gives a cosmic microwave radiation temperature of 2.783 + or - 0.025 K, where the error is due to several errors (mostly systematic) added by quadrature. This is the most accurate direct measurement (by a factor of 3) yet reported.

Johnson, David G.

Intercomparison of UT1 measurements during the MERIT campaign period

Universal time (UT1) measurements obtained using VLBI, lunar laser ranging (LLR), and BIH optical astronomy are compared. The JPL Kalman filter for the earth rotation and the polar motion is utilized to smooth one data set or combine data sets for intercomparison. The differences between raw UT1 data and independently smoothed data are employed to assess the accuracy of the measured series and the sufficiency of the error budget. Systematic errors in periodic signatures and length of day estimates are analyzed. The data reveal that the techniques of LLR and VLBI agree to within their formal errors. It is determined that the residual error for the LLR is too large and the residual error estimated for the BIH data is too small.

Spieth, M. A.

Heterogeneous reactions of HNO3(g) + NaCl(s) yields HCl(g) + NaNO3(s) and N2O5(g) + NaCl(s) yields ClNO2(g) + NaNO3(s)

The heterogeneous reactions of HNO3(g) + NaCl(s) yields HCl(g) + NaNO3(s) (eq 1) and N2O5(g) + NaCl(s) yields ClNO2(g) + NaNO3(S) (eq 2) were investigated over the temperature range 223-296 K in a flow-tube reactor coupled to a quadrupole mass spectrometer. Either a chemical ionization mass spectrometer (CIMS) or an electron-impact ionization mass spectrometer (EIMS) was used to provide suitable detection sensitivity and selectivity. In order to mimic atmospheric conditions, partial pressures of HNO3 and N2O5 in the range 6 x 10(exp -8) - 2 x 10(exp -6) Torr were used. Granule sizes and surface roughness of the solid NaCl substrates were determined by using a scanning electron microscope. For dry NaCl substrates, decay rates of HNO3 were used to obtain gamma(1) = 0.013 +/- 0.004 (1sigma) at 296 K and > 0.008 at 223 K, respectively. The error quoted is the statistical error. After all corrections were made, the overall error, including systematic error, was estimated to be about a factor of 2. HCl was found to be the sole gas-phase product of reaction 1. The mechanism changed from heterogeneous reaction to predominantly physical adsorption when the reactor was cooled from 296 to 223 K. For reaction 2 using dry salts, gamma(2) was found to be less than 1.0 x 10(exp -4) at both 223 and 296 K. The gas-phase reaction product was identified as ClNO2 in previous studies using an infrared spectrometer. An enhancement in reaction probability was observed if water was not completely removed from salt surfaces, probably due to the reaction of N2O5(g) + H2O(s) yields 2HNO3(g). Our results are compared with previous literature values obtained using different experimental techniques and conditions. The implications of the present results for the enhancement of the hydrogen chloride column density in the lower stratosphere after the El Chichon volcanic eruption and for the chemistry of HCl and HNO3 in the marine troposphere are discussed.

Leu, Ming-Taun

Modeling the Proton Radiation Belt With Van Allen Probes Relativistic Electron-Proton Telescope Data

An empirical model of the proton radiation belt is constructed from data taken during 2013-2017 by the Relativistic Electron-Proton Telescopes on the Van Allen Probes satellites. The model intensity is a function of time, kinetic energy in the range 18-600 megaelectronvolts, equatorial pitch angle, and L shell of proton guiding centers. Data are selected, on the basis of energy deposits in each of the nine silicon detectors, to reduce background caused by hard proton energy spectra at low L. Instrument response functions are computed by Monte Carlo integration, using simulated proton paths through a simplified structural model, to account for energy loss in shielding material for protons outside the nominal field of view. Overlap of energy channels, their wide angular response, and changing satellite orientation require the model dependencies on all three independent variables be determined simultaneously. This is done by least squares minimization with a customized steepest descent algorithm. Model uncertainty accounts for statistical data error and systematic error in the simulated instrument response. A proton energy spectrum is also computed from data taken during the 8 January 2014 solar event, to illustrate methods for the simpler case of an isotropic and homogeneous model distribution. Radiation belt and solar proton results are compared to intensities computed with a simplified, on-axis response that can provide a good approximation under limited circumstances.

Selesnick, R. S.

Examination of L-Band Brightness Temperature Forecasts in the SMAP Level-4 Soil Moisture Analysis

The NASA Soil Moisture Active Passive (SMAP) mission [4] has been providing L-band (1.4 GHz) passive microwave brightness temperature (Tb) observations since April 2015. By assimilating the Tb observations into the NASA Catchment land surface model [5] using a spatially distributed ensemble Kalman filter, the NASA Global Modeling and Assimilation Office generates the SMAP Level-4 Soil Moisture (L4_SM) product, which provides global, 3-hourly, 9-km resolution estimates of surface (0-5 cm) and root-zone (0-100 cm) soil moisture with ~2.5-day latency for use in research and applications [6]. The L4_SM product also includes estimates of soil temperature, land surface fluxes, and assimilation diagnostics such as the model forecast and observed Tb values [7]. The output from the L4_SM system is routinely monitored by the L4_SM team. Such monitoring provides valuable information; instances of unusually large Tb observation-minus-forecast (O-F) residuals can indicate events during which soil moisture conditions are poorly described in the land modeling system [7,8]. For example, repeated occurrences of very large Tb O-F values in central Australia were traced back to deficiencies in the gauge-based precipitation product used in the land modeling system through L4_SM Version 5; this discovery prompted the use, beginning in Version 6, of satellite- and gauge-based precipitation observations outside of North America [9]. Recently, a statistical analysis of the Tb O-F residuals revealed systematic errors in the “tau-omega” L-band radiative transfer model that converts the land-model simulated soil moisture and temperature into the forecast Tb prior to the L4_SM analysis. The L4_SM analysis is built on the ensemble Kalman filter and assumes unbiased forecast errors. The presence of systematic Tb forecast errors could thus adversely impact the quality of the analyzed soil moisture. In this paper, we examine the Tb O-F residuals of the latest Version 7 L4_SM data (Science Version ID Vv7030 and Vv7032) [10,11,12]. In the L4_SM Version 7 algorithm, key parameters of the L-band radiative transfer model, including soil roughness, scattering albedo, and a (seasonally varying) climatology of vegetation opacity, are obtained from the SMAP Level-2 Radiometer retrieval product (Version 5) [1]. Additionally, we also use ground measurements of surface soil moisture and soil temperature from the SMAP core validation sites as in situ reference of soil conditions [2,3]. As part of the L4_SM system calibration, the seasonally-varying bias between the model forecast Tb and the observed values is removed prior to the assimilation of the SMAP Tb observations [7]. That is, the L4_SM system is designed to only correct errors in synoptic-scale and interannual variations from the long-term mean seasonal cycle while maintaining the model’s (potentially erroneous) climatology. The Tb O-F residuals examined here are thus computed using SMAP Tb observations after they are rescaled to the mean seasonal cycle of Tb from the modeling system without SMAP data assimilation. Consequently, the long-term average of the Tb O-F residuals has a global mean of only 0.13 K and locally small values, ranging from -1 to 3 K. Despite the small time-average values of the Tb O-F residuals, the model forecast Tb was nevertheless found to exhibit undesirable systematic errors. At some locations, the time-average Tb O-F values strongly depend on surface soil moisture (SM). At the Yanco SMAP core validation site, for example, the Tb O-F residuals typically range from 5 to 15 K under dry soil moisture conditions (SM < 0.15 m3 m-3) yet are predominantly negative under wet soil moisture conditions (SM > 0.25 m3 m-3), with values ranging from 0 to -40 K. This results in soil moisture analysis increments that persistently make the soil drier under dry SM conditions and persistently make the soil wetter under wet SM conditions, suggesting an error in the dynamic range of the simulated Tb, soil moisture or soil temperature. In this paper, we describe the higher-order systematic Tb forecast errors in more detail, examine their impact on the L4_SM product quality, and explore potential avenues to further improve the L4_SM algorithm.

Rolf Reichle

Global Warming Estimation from MSU

Microwave Sounding Unit (MSU) radiometer observations in Ch 2 (53.74 GHz) from sequential, sun-synchronous, polar-orbiting NOAA satellites contain small systematic errors. Some of these errors are time-dependent and some are time-independent. Small errors in Ch 2 data of successive satellites arise from calibration differences. Also, successive NOAA satellites tend to have different Local Equatorial Crossing Times (LECT), which introduce differences in Ch 2 data due to the diurnal cycle. These two sources of systematic error are largely time independent. However, because of atmospheric drag, there can be a drift in the LECT of a given satellite, which introduces time-dependent systematic errors. One of these errors is due to the progressive chance in the diurnal cycle and the other is due to associated chances in instrument heating by the sun. In order to infer global temperature trend from the these MSU data, we have eliminated explicitly the time-independent systematic errors. Both of the time-dependent errors cannot be assessed from each satellite. For this reason, their cumulative effect on the global temperature trend is evaluated implicitly. Christy et al. (1998) (CSL). based on their method of analysis of the MSU Ch 2 data, infer a global temperature cooling trend (-0.046 K per decade) from 1979 to 1997, although their near nadir measurements yield near zero trend (0.003 K/decade). Utilising an independent method of analysis, we infer global temperature warmed by 0.12 +/- 0.06 C per decade from the observations of the MSU Ch 2 during the period 1980 to 1997.

Prabhakara, C.

A constant altitude flight survey method for mapping atmospheric ambient pressures and systematic radar errors

The flight test technique described uses controlled survey runs to determine horizontal atmospheric pressure variations and systematic altitude errors that result from space positioning measurements. The survey data can be used not only for improved air data calibrations, but also for studies of atmospheric structure and space positioning accuracy performance. The examples presented cover a wide range of radar tracking conditions for both subsonic and supersonic flight to an altitude of 42,000 ft.

Larson, T. J.

A constant altitude flight survey method for mapping atmospheric ambient pressures and systematic radar errors

The flight test technique described uses controlled survey runs to determine horizontal atmospheric pressure variations and systematic altitude errors that result from space positioning measurements. The survey data can be used not only for improved air data calibrations, but also for studies of atmospheric structure and space positioning accuracy performance. The examples presented cover a wide range of radar tracking conditions for both subsonic and supersonic flight to an altitude of 42,000 ft.

Larson, T. J.

Daily estimates of the earth's pole position with the Global Positioning System

Daily estimates of the earth's pole position have been obtained with measurements from a worldwide network of GPS receivers, obtained during the three week GIG '91 experiment in January-February 1991. For this short-term study, the GPS based polar motion series agrees with the other space based geodetic techniques (Very Long Baseline Interferometry and Satellite Laser Ranging) to about 0.4 mas rms, after the removal of mean biases of order 1-3 mas. The small error in day-to-day variability is not sensitive to the fiducial strategy used, nor are fiducial sites even necessary for monitoring high frequency pole position variability. The small biases indicate that the applied reference frames of the three geodetic techniques are nearly aligned, that the GPS fiducial errors are small, and that systematic errors in GPS are also small (of order 5 ppb). A well determined reference frame is necessary for monitoring the long-term stability of polar motion and for separating it from other long-term signals such as tectonic motion and internal systematic errors.

Lindqwister, Ulf J.

ILRS Analysis Activities After the Adoption of ITRF2020

"The contribution of the International Laser Ranging Service (ILRS) to the most recent realization of the International Terrestrial Reference System (ITRS) was the result of an analysis strategy with two major modifications compared to the operational products: a modeling for stations long-term systematic errors (biases reported in the ILRS Data Handling File) and an updated model of the target signature error (satellite Centre of Mass model). Both refined models were used as input information for the ILRS contribution to the ITRF2020 (International Terrestrial Reference Frame 2020). Thereafter, the ILRS Analysis Standing Committee (ASC) focused its effort on implementing the new reference frame in its operational products, define a strategy to improve the ongoing monitoring of the systematic errors, compute the ILRS contribution to the planned ITRF2020 update, and to include LARES-2 among the considered satellites for the operational products. The ILRS ASC implemented the ITRF2020/SLRF2020 into all its official operational products (TRF, Earth Orientation Parameters, predicted and combined satellite orbits) and its impact was evaluated. The operational products benefit from the continuous monitoring of the station systematic errors and the frequent updates of the Data Handling File whenever a significant change in the station systematic error is observed. In the future, a change-point detection algorithm, jointly estimating the times and the number of discontinuities, will be implemented to detect potential new discontinuities in the range bias series. The inclusion of LARES-2 among the satellites whose data are operationally analyzed will furtherly increase the robustness of the estimated parameters. Finally, the ILRS ASC activities include the benchmarking of a new analysis center (CNES) which will formally begin its own contribution in 2024."

Satellite Laser Ranging

Some statistical analysis techniques for the effect of systematic instrument errors on the results of measurements in a space experiment

Mathematical models of certain systematic telemetry signal errors arising during the passage of the signal through the recording and transmitting blocks of the physical instruments aboard the spacecraft are classified and constructed. Statistical analysis methods are used to determine the background function and relative sensitivity coefficients of the channels of a charged particle detector. Results are presented. A block diagram for a method taking into account the effect of distortions is given.

Kondakov, S. P.

The impact of satellite temperature soundings on the forecasts of a small national meteorological service

The impact of introducing satellite temperature sounding data on a numerical weather prediction model of a national weather service is evaluated. A dry five level, primitive equation model which covers most of the Northern Hemisphere, is used for these experiments. Series of parallel forecast runs out to 48 hours are made with three different sets of initial conditions: (1) NOSAT runs, only conventional surface and upper air observations are used; (2) SAT runs, satellite soundings are added to the conventional data over oceanic regions and North Africa; and (3) ALLSAT runs, the conventional upper air observations are replaced by satellite soundings over the entire model domain. The impact on the forecasts is evaluated by three verification methods: the RMS errors in sea level pressure forecasts, systematic errors in sea level pressure forecasts, and errors in subjective forecasts of significant weather elements for a selected portion of the model domain. For the relatively short range of the present forecasts, the major beneficial impacts on the sea level pressure forecasts are found precisely in those areas where the satellite sounding are inserted and where conventional upper air observations are sparse. The RMS and systematic errors are reduced in these regions. The subjective forecasts of significant weather elements are improved with the use of the satellite data. It is found that the ALLSAT forecasts are of a quality comparable to the SAR forecasts.

Wolfson, N.