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All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Dark energy survey year 3 results: High-precision measurement and modeling of galaxy-galaxy lensing

We present and characterize the galaxy-galaxy lensing signal measured using the first three years of data from the Dark Energy Survey (DES Y3) covering 4132 deg 2 . These galaxy-galaxy measurements are used in the DES Y3 3 × 2 pt cosmological analysis, which combines weak lensing and galaxy clustering information. We use two lens samples: a magnitude-limited sample and the redmagic sample, which span the redshift range ∼ 0.2 – 1 with 10.7 and 2.6 M galaxies, respectively. For the source catalog, we use the metacalibration shape sample, consisting of ≃ 100 M galaxies separated into four tomographic bins. Our galaxy-galaxy lensing estimator is the mean tangential shear, for which we obtain a total SNR of ∼ 148 for maglim ( ∼ 120 for redmagic), and ∼ 67 ( ∼ 55 ) after applying the scale cuts of 6 Mpc / h . Thus we reach percent-level statistical precision, which requires that our modeling and systematic-error control be of comparable accuracy. The tangential shear model used in the 3 × 2 pt cosmological analysis includes lens magnification, a five-parameter intrinsic alignment model, marginalization over a point mass to remove information from small scales and a linear galaxy bias model validated with higher-order terms. We explore the impact of these choices on the tangential shear observable and study the significance of effects not included in our model, such as reduced shear, source magnification, and source clustering. We also test the robustness of our measurements to various observational and systematics effects, such as the impact of observing conditions, lens-source clustering, random-point subtraction, scale-dependent metacalibration responses, point spread function residuals, and B modes.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2014

A critical evaluation of worst case optimization methods for robust intensity-modulated proton therapy planning

Purpose: To critically evaluate and compare three worst case optimization methods that have been previously employed to generate intensity-modulated proton therapy treatment plans that are robust against systematic errors. The goal of the evaluation is to identify circumstances when the methods behave differently and to describe the mechanism behind the differences when they occur. Methods: The worst case methods optimize plans to perform as well as possible under the worst case scenario that can physically occur (composite worst case), the combination of the worst case scenarios for each objective constituent considered independently (objectivewise worst case), and the combination of the worst case scenarios for each voxel considered independently (voxelwise worst case). These three methods were assessed with respect to treatment planning for prostate under systematic setup uncertainty. An equivalence with probabilistic optimization was used to identify the scenarios that determine the outcome of the optimization. Results: If the conflict between target coverage and normal tissue sparing is small and no dose-volume histogram (DVH) constraints are present, then all three methods yield robust plans. Otherwise, they all have their shortcomings: Composite worst case led to unnecessarily low plan quality in boundary scenarios that were less difficult than the worst case ones. Objectivewise worst case generally led to nonrobust plans. Voxelwise worst case led to overly conservative plans with respect to DVH constraints, which resulted in excessive dose to normal tissue, and less sharp dose fall-off than the other two methods. Conclusions: The three worst case methods have clearly different behaviors. These behaviors can be understood from which scenarios that are active in the optimization. No particular method is superior to the others under all circumstances: composite worst case is suitable if the conflicts are not very severe or there are DVH constraints whereas voxelwise worst case is advantageous if there are severe conflicts but no DVH constraints. The advantages of composite and voxelwise worst case outweigh those of objectivewise worst case.

60 APPLIED LIFE SCIENCES↗
NASA NTRS1994

Variation of Great Lakes Water Levels Derived from Geosat Altimetry

A technique for using satellite radar altimetry data to estimate the temporal variation of the water level in moderate to large lakes and enclosed seas is described. Great Lakes data from the first 2 years of the U.S. Navy's Geosat Exact Repeat Mission (November 1986 to November 1988), for which there is an improved orbit, are used to demonstrate the technique. The Geosat results are compared to the lake level data collected by the Great Lakes Section, National Ocean Service, National Oceanic and Atmospheric Administration, and are found to reproduce the temporal variations of the five major lakes with Root-Mean-Square error (RMS) ranging from 9.4 to 13.8 cm and a combined average of 11.1 cm. Geosat data are also analyzed for Lake St. Clair, representing a moderate-sized lake, with a resulting rms of 17.0 cm. During this study period, the water level in the Great Lakes varied in a typical annual cycle of about 0.2 m (0.5 in for Lake Ontario) superimposed on a general decline of approximately 0.5 m. The altimeter data reproduced the general decline reasonably well for all the lakes, but the annual cycle was obscured in some lakes due to systematic errors in the altimeter data. Current and future altimetry missions will have markedly improved accuracy which will permit many moderate (25 km diameter) or larger lakes or enclosed seas to be routinely monitored.

Morris, Charles S.↗
DOE OSTI2024

Intrinsic and extinction colour components in SNe Ia and the determination of R V

Context.The colour fluctuations of type Ia supernovae (SNe Ia) include intrinsic and extrinsic components, which both contribute to the observed variability. Previous works proposed a statistical separation of these two contributions, but the individual intrinsic colour contributions of each SN Ia were not extracted. In addition, a large uncertainty remains on the value of the parameterR V , which characterises the dust extinction formula. Aims.Leveraging the known parameterisation of the extinction formula for dust in our Galaxy, and applying it to the host galaxy of SNe Ia, we propose a new method of separation –valid for each SN– using the correlations between colour fluctuations. This also allows us to derive a well-constrained value of the extinction parameterR V with different, possibly smaller systematic errors. We also define a three-dimensional space of intrinsic colour fluctuations. Methods.The key ingredients in this attempt at separating the intrinsic and extinction colour components for each SN –and subsequently measuringR V – are the assumption of a linearized dependence of magnitude on the extinction component of colour, a one-dimensional extra-intrinsic colour space (in addition to CaII H&Kλ3945 and Si IIλ4131 contributions) over four independent colours, and the absence of correlation between the intrinsic and extrinsic variabilities. Results.We show that a consistent solution is found under the previous assumptions, but the observed systematic trends point to a (small) inadequacy of the extinction formula. Once corrected, all systematic extinction effects can be cancelled by choosing a single scaling of the extinction colour component as well as an appropriate value ofR V = 2.181 ± 0.117. The observed colours are described within an accuracy of 0.025 mag. The resulting magnitude variability is 0.13 over allUBVRIbandpasses, and this fluctuation is shown to be independent of the bandpass to within 0.02 mag.

Astronomy & Astrophysics↗
NASA NTRS1999

Impact of TRMM and SSM/I-derived Precipitation and Moisture Data on the GEOS Global Analysis

Current global analyses contain significant errors in primary hydrological fields such as precipitation, evaporation, and related cloud and moisture in the tropics. The Data Assimilation Office at NASA's Goddard Space Flight Center has been exploring the use of space-based rainfall and total precipitable water (TPW) estimates to constrain these hydrological parameters in the Goddard Earth Observing System (GEOS) global data assimilation system. We present results showing that assimilating the 6-hour averaged rain rates and TPW estimates from the Tropical Rainfall Measuring Mission (TRMM) and Special Sensor Microwave/Imager (SSM/I) instruments improves not only the precipitation and moisture estimates but also reduce state-dependent systematic errors in key climate parameters directly linked to convection such as the outgoing longwave radiation, clouds, and the large-scale circulation. The improved analysis also improves short-range forecasts beyond 1 day, but the impact is relatively modest compared with improvements in the time-averaged analysis. The study shows that, in the presence of biases and other errors of the forecast model, improving the short-range forecast is not necessarily prerequisite for improving the assimilation as a climate data set. The full impact of a given type of observation on the assimilated data set should not be measured solely in terms of forecast skills.

Hou, Arthur Y.↗
NASA NTRS1999

Improved Stratospheric Temperature Retrievals for Climate Reanalysis

The Data Assimilation Office (DAO) is embarking on plans to generate a twenty year reanalysis data set of climatic atmospheric variables. One of the focus points will be in the evaluation of the dynamics of the stratosphere. The Stratospheric Sounding Unit (SSU), flown as part of the TIROS Operational Vertical Sounder (TOVS), is one of the primary stratospheric temperature sensors flown consistently throughout the reanalysis period. Seven unique sensors made the measurements over time, with individual instrument characteristics that need to be addressed. The stratospheric temperatures being assimilated across satellite platforms will profoundly impact the reanalysis dynamical fields. To attempt to quantify aspects of instrument and retrieval bias we are carefully collecting and analyzing all available information on the sensors, their instrument anomalies, forward model errors and retrieval biases. For the retrieval of stratospheric temperatures, we adapted the minimum variance approach of Jazwinski (1970) and Rodgers (1976) and applied it to the SSU soundings. In our algorithm, the state vector contains an initial guess of temperature from a model six hour forecast provided by the Goddard EOS Data Assimilation System (GEOS/DAS). This is combined with an a priori covariance matrix, a forward model parameterization, and specifications of instrument noise characteristics. A quasi-Newtonian iteration is used to obtain convergence of the retrieved state to the measurement vector. This algorithm also enables us to analyze and address the systematic errors associated with the unique characteristics of the cell pressures on the individual SSU instruments and the resolving power of the instruments to vertical gradients in the stratosphere. The preliminary results of the improved retrievals and their assimilation as well as baseline calculations of bias and rms error between the NESDIS operational product and col-located ground measurements will be presented.

Rokke, L.↗
DOE OSTI2014

MO-E-17A-03: Monte Carlo CT Dose Calculation: A Comparison Between Experiment and Simulation Using ARCHER-CT

Purpose: To compare the CT doses derived from the experiments and GPU-based Monte Carlo (MC) simulations, using a human cadaver and ATOM phantom. Methods: The cadaver of an 88-year old male and the ATOM phantom were scanned by a GE LightSpeed Pro 16 MDCT. For the cadaver study, the Thimble chambers (Model 10×5−0.6CT and 10×6−0.6CT) were used to measure the absorbed dose in different deep and superficial organs. Whole-body scans were first performed to construct a complete image database for MC simulations. Abdomen/pelvis helical scans were then conducted using 120/100 kVps, 300 mAs and a pitch factor of 1.375:1. For the ATOM phantom study, the OSL dosimeters were used and helical scans were performed using 120 kVp and x, y, z tube current modulation (TCM). For the MC simulations, sufficient particles were run in both cases such that the statistical errors of the results by ARCHER-CT were limited to 1%. Results: For the human cadaver scan, the doses to the stomach, liver, colon, left kidney, pancreas and urinary bladder were compared. The difference between experiments and simulations was within 19% for the 120 kVp and 25% for the 100 kVp. For the ATOM phantom scan, the doses to the lung, thyroid, esophagus, heart, stomach, liver, spleen, kidneys and thymus were compared. The difference was 39.2% for the esophagus, and within 16% for all other organs. Conclusion: In this study the experimental and simulated CT doses were compared. Their difference is primarily attributed to the systematic errors of the MC simulations, including the accuracy of the bowtie filter modeling, and the algorithm to generate voxelized phantom from DICOM images. The experimental error is considered small and may arise from the dosimeters. R01 grant (R01EB015478) from National Institute of Biomedical Imaging and Bioengineering.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2019

The neutron electric dipole moment experiment at the Spallation Neutron Source

Novel experimental techniques are required to make the next big leap in neutron electric dipole moment experimental sensitivity, both in terms of statistics and systematic error control. The nEDM experiment at the Spallation Neutron Source (nEDM@SNS) will implement the scheme of Golub & Lamoreaux [Phys. Rep., 237, 1 (1994)]. The unique properties of combining polarized ultracold neutrons, polarized 3 He, and superfluid 4He will be exploited to provide a sensitivity to ~ 10-28 e · cm. Our cryogenic apparatus will deploy two small (3 L) measurement cells with a high density of ultracold neutrons produced and spin analyzed in situ. The electric field strength, precession time, magnetic shielding, and detected UCN number will all be enhanced compared to previous room temperature Ramsey measurements. Our 3 He co-magnetometer offers unique control of systematic effects, in particular the Bloch-Siegert induced false EDM. Furthermore, there will be two distinct measurement modes: free precession and dressed spin. This will provide an important self-check of our results. Following five years of “critical component demonstration,” our collaboration transitioned to a “large scale integration” phase in 2018. An overview of our measurement techniques, experimental design, and brief updates are described in these proceedings.

Leung, Kent↗
NASA NTRS1991

Estimation of geopotential differences over intercontinental locations using satellite and terrestrial measurements

An error analysis study was conducted in order to assess the current accuracies and the future anticipated improvements in the estimation of geopotential differences over intercontinental locations. An observation/estimation scheme was proposed and studied, whereby gravity disturbance measurements on the Earth's surface, in caps surrounding the estimation points, are combined with corresponding data in caps directly over these points at the altitude of a low orbiting satellite, for the estimation of the geopotential difference between the terrestrial stations. The mathematical modeling required to relate the primary observables to the parameters to be estimated, was studied for the terrestrial data and the data at altitude. Emphasis was placed on the examination of systematic effects and on the corresponding reductions that need to be applied to the measurements to avoid systematic errors. The error estimation for the geopotential differences was performed using both truncation theory and least squares collocation with ring averages, in case observations on the Earth's surface only are used. The error analysis indicated that with the currently available global geopotential model OSU89B and with gravity disturbance data in 2 deg caps surrounding the estimation points, the error of the geopotential difference arising from errors in the reference model and the cap data is about 23 kgal cm, for 30 deg station separation.

Pavlis, Nikolaos K.↗
NASA NTRS1999

Improving Assimilated Global Climate Data Using TRMM and SSM/I Rainfall and Moisture Data

Current global analyses contain significant errors in primary hydrological fields such as precipitation, evaporation, and related cloud and moisture in the tropics. Work has been underway at NASA's Data Assimilation Office to explore the use of TRMM and SSM/I-derived rainfall and total precipitable water (TPW) data in global data assimilation to directly constrain these hydrological parameters. We found that assimilating these data types improves not only the precipitation and moisture estimates but also key climate parameters directly linked to convection such as the outgoing longwave radiation, clouds, and the large-scale circulation in the tropics. We will present results showing that assimilating TRMM and SSM/I 6-hour averaged rain rates and TPW estimates significantly reduces the state-dependent systematic errors in assimilated products. Specifically, rainfall assimilation improves cloud and latent heating distributions, which, in turn, improves the cloudy-sky radiation and the large-scale circulation, while TPW assimilation reduces moisture biases to improve radiation in clear-sky regions. Rainfall and TPW assimilation also improves tropical forecasts beyond 1 day.

Hou, Arthur Y.↗
DOE OSTI2023

Improving Dark Energy Constraints Using Low-Redshift Large-Scale Structures

The primary goal of this project was to improve constraints on dark energy measurements by improving our ability to extract cosmological information from low redshift large-scale structures. PI Clowe's project's primary aim was to reduce the bias in measurements of the masses of clusters of galaxies to a level where the evolution of the cluster mass function can be used in the Vera Rubin Observatory's Legacy Survey of Space and Time Dark Energy Science Collaboration survey to improve the accuracy of the measurement of dark energy and other cosmological parameters. Co-PI Seo's project studied observational systematics affecting large-scale clustering of galaxies, which will be used to improve dark energy constraints from the Dark Energy Spectroscopic Instrument (DESI). The cluster lensing project employed a series of simulations and observations of clusters of galaxies to test numerous potential systematic errors in cluster mass measurements using weak gravitational lensing as the accuracy of current weak lensing measurements are more than order of magnitude worse than what is required to use clusters of galaxies for accurate determination of dark energy parameters. PI Clowe and group developed and analyzed simulations to test for, and correct biases introduced in, the weak lensing measurement process. Finally, PI Clowe and group developed a method of detecting clusters using galaxy overdensities and applied the method to the BLISS and DES surveys. The success of spectroscopic dark energy mission such as the extended Baryon Oscillation Spectroscopic Survey (eBOSS) and the Dark Energy Spectroscopic Instrument (DESI) will depend on a thorough understanding of various observational systematics in the target density fluctuations that would give rise to spurious, non-cosmological signals. PI Seo and group developed a deep learning, artificial neural network (ANN) technique that modeled and mitigated such effects, aimed at deriving more robust galaxy clustering signals not only for the baryon acoustic oscillation feature and redshift-space distortions but also for primordial non-Gaussianity constraint.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Binary pseudo-random array standards for calibration of 3D optical surface profilers used for metrology with significantly curved x-ray optics

High-accuracy metrology is vitally important in manufacturing ultra-high-quality free-form mirrors designed to manipulate X-ray light with nanometer-scale wavelengths. The current capabilities and possibility for improvements in X-ray mirror manufacturing are limited by inherent imperfections of the integrated metrology tools. In the case of Fizeau interferometry, metrology tools are currently calibrated with super-polished flat test-standard/reference mirrors. This is acceptable for measuring slightly curved X-ray optics. However, for even moderately curved aspherical X-ray mirrors the flat-reference calibration is not sufficiently accurate and stitching Fizeau interferometer-based surface metrology is used to mitigate the problem. But still, the retrace and aberration errors, as well as the limited spatial resolution, described with the instrument transfer function (ITF), can be transferred into the optical surface topography of X-ray mirrors obtained in stitching metrology. For ITF calibration, we have developed an original technique, based on test standards structured as two-dimensional (2D) highly-randomized (HR) binary pseudo-random arrays (BPRAs). The technique employs the unique properties of the HR BPRA patterns in the spatial frequency domain., i.e. the inherent 2D power spectral density of the HR BPRA pattern has a deterministic white-noise-like character that allows direct determination of the ITF with uniform sensitivity over the entire spatial frequency range and field-of-view of an instrument. Here, we explore technological, metrological, and analytical aspects essential for calibration of the retrace and aberration errors of Fizeau interferometers using different types of tilted test samples, including a super-polished reference mirror for the re-trace calibration and the uniformly redundant array (URA) BPRA standards for the geometrical distortion (aberration) calibration. While the first method was previously demonstrated by researchers at DIAMOND Light Source, a method based on the URA BPRA is described and demonstrated here for the first time. We outline the design and fabrication process used in fabrication of URA BPRA test standards, and present the results of application of the URA BPRA standards demonstrating the high efficacy of our approach to geometrical distortion calibration of Fizeau interferometers. We also discuss the possible sources of unexpected peculiarities of the systematic errors, including an astigmatic character of the retrace error, observed with Fizeau interferometers at the Advanced Light Source X-Ray Optics Laboratory.

Munechika, Keiko↗
DOE OSTI2014

New evidence for a substellar luminosity problem: Dynamical mass for the brown dwarf binary Gl 417BC

We present new evidence for a problem with cooling rates predicted by substellar evolutionary models that implies that model-derived masses in the literature for brown dwarfs and directly imaged planets may be too high. Based on our dynamical mass for Gl 417BC (L4.5+L6) and a gyrochronology system age from its young, solar-type host star, commonly used models predict luminosities 0.2-0.4 dex lower than we observe. This corroborates a similar luminosity-age discrepancy identified in our previous work on the L4+L4 binary HD 130948BC, which coincidentally has nearly identical component masses (≈50-55 M{sub Jup}) and age (≈800 Myr) as Gl 417BC. Such a luminosity offset would cause systematic errors of 15%-25% in model-derived masses at this age. After comparing different models, including cloudless models that should not be appropriate for mid-L dwarfs like Gl 417BC and HD 130948BC but actually match their luminosities better, we speculate the observed overluminosity could be caused by opacity holes (i.e., patchy clouds) in these objects. Moreover, from hybrid substellar evolutionary models that account for cloud disappearance, we infer the corresponding phase of overluminosity may extend from a few hundred million years up to a few gigayears and cause masses to be overestimated by up to 25%, even well after clouds disappear from view entirely. Thus, the range of ages and spectral types affected by this potential systematic shift in luminosity evolution would encompass most known directly imaged gas-giants and field brown dwarfs.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Determining the bubble nucleation efficiency of low-energy nuclear recoils in superheated C 3 F 8 dark matter detectors

The bubble nucleation efficiency of low-energy nuclear recoils in superheated liquids plays a crucial role in interpreting results from direct searches for weakly interacting massive particle (WIMP) dark matter. Here, the PICO collaboration presents the results of the efficiencies for bubble nucleation from carbon and fluorine recoils in superheated C 3 F 8 from calibration data taken with five distinct neutron spectra at various thermodynamic thresholds ranging from 2.1 to 3.9 keV. Instead of assuming any particular functional forms for the nuclear recoil efficiency, a generalized piecewise linear model is proposed with systematic errors included as nuisance parameters to minimize model-introduced uncertainties. A Markov chain Monte Carlo routine is applied to sample the nuclear recoil efficiency for fluorine and carbon at 2.45 and 3.29 keV thermodynamic thresholds simultaneously. The nucleation efficiency for fluorine was found to be ≥ 50% for nuclear recoils of 3.3 keV (3.7 keV) at a thermodynamic Seitz threshold of 2.45 keV (3.29 keV), and for carbon the efficiency was found to be ≥ 50% for recoils of 10.6 keV (11.1 keV) at a threshold of 2.45 keV (3.29 keV). Simulated datasets are used to calculate a p value for the fit, confirming that the model used is compatible with the data. The fit paradigm is also assessed for potential systematic biases, which although small, are corrected for. Additional steps are performed to calculate the expected interaction rates of WIMPs in the PICO-60 detector, a requirement for calculating WIMP exclusion limits.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRS1999

Improved Earth Sensor Performance Using a Sequentially Correlated Noise Model

Spacecraft attitude estimation by means of an extended Kalman filter requires a reasonably true model of the inherent noise of each sensor. For some sensors, the largest uncorrected noise comes not from the sensor itself, but from errors in the model for the predicted observations. This is certainly the case for Earth horizon sensors. The Earth horizon as seen from low Earth orbit is nearly a circle whose radius depends primarily on altitude. A straightforward latitude-dependent correction is added to this to account for the oblateness of the Earth. There also are both seasonal and stochastic variations in the horizon height. The seasonal variations can be predicted to some limited degree based on models derived from historical data. The stochastic component characteristically shows variations that are correlated both in time and space but which are unpredictable over long time spans. This work investigates whether Earth horizon sensor performance can be improved by solving for its systematic error as an augmentation of an attitude Kalman filter. It is found that using only Earth and Sun sensors, the augmented state is not fully observable. Even when magnetometer data is included, only the pitch axis component of the error can be improved; the roll component is unobservable.

Sedlak, J.↗
DOE OSTI2022

TDCOSMO VIII. A key test of systematics in the hierarchical method of time-delay cosmography

The largest source of systematic errors in the time-delay cosmography method likely arises from the lens model mass distribution, where an inaccurate choice of model could in principle bias the value of $H$ 0 . A Bayesian hierarchical framework has been proposed which combines lens systems with kinematic data, constraining the mass profile shape at a population level. The framework has been previously validated using a small sample of lensing galaxies drawn from hydro-simulations. The goal of this work is to expand the validation to a more general set of lenses consistent with observed systems, as well as confirm the capacity of the method to combine two lens populations: one which has time delay information and one which lacks time delays and has systematically different image radii. For this purpose, we generated samples of analytic lens mass distributions made of baryons+dark matter and fit the subsequent mock images with standard power-law models. Corresponding kinematics data were also emulated. The hierarchical framework applied to an ensemble of time-delay lenses allowed us to correct the $H$ 0 bias associated with model choice to find $H$ 0 within 1.5σ of the fiducial value. We then combined this set with a sample of corresponding lens systems which have no time delays and have a source at lower $z$, resulting in a systematically smaller image radius relative to their effective radius. The hierarchical framework has successfully accounted for this effect, recovering a value of $H$ 0 which is both more precise (σ ~ 2%) and more accurate (0.7% median offset) than the time-delay set alone. This result confirms that non-time-delay lenses can nonetheless contribute valuable constraining power to the determination of $H$ 0 via their kinematic constraints, assuming they come from the same global population as the time-delay set.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1999

Improved Earth Sensor Performance Using a Sequentially Correlated Noise Model

Spacecraft attitude estimation by means of an extended Kalman filter requires a reasonably true model of the inherent noise of each sensor. For some sensors, the largest uncorrected noise comes not from the sensor itself, but from errors in the model for the predicted observations. This is certainly the case for Earth horizon sensors. The Earth horizon as seen from low Earth orbit is nearly a circle whose radius depends primarily on altitude. A straightforward latitude-dependent correction is added to this to account for the oblateness of the Earth. There also are both seasonal and stochastic variations in the horizon height. The seasonal variations can be predicted to some limited degree based on models de(ived from historical data. The stochastic component characteristically shows variations that are correlated both in time and space but which are unpredictable over long time spans. This work investigates whether Earth horizon sensor performance can be improved by solving for its systematic error as an augmentation of an attitude Kalman filter. It is found that using only Earth and Sun sensors, the augmented state is not fully observable. Even when magnetometer data is included, only the pitch axis component of the error can be improved; the roll component is unobservable.

Sedlak, Joseph↗
DOE OSTI2018

Understanding and quantifying the systematic effects of clutter within a radiation detection scene

Because of low signal-to-noise ratios, the main difficultly in real-world detection scenarios is distinguishing between benign sources and potentially-threatening radioactive materials. The variability in observed signal during a radiation detection search operation can be contributed to the stochastic nature of the underlying physics and the systematic errors inherent to the detection systems employed. This variability is compounded for dynamic detection scenarios, where objects, referred to as clutter, traverse through the primary detection scene, introducing potential suppressions in the observed signal due to the attenuation of background radiation. This study examines the impact that clutter, namely automobiles such as small utility vehicles, sedans, and trucks, produces on the observed signal in a 2 in. × 4 in. × 16 in. NaI(Tl) detector. The clutter is identified and tracked in the detection scene using a time-synced video camera and a 2-D light distance and ranging contextual sensors. Two experiments were performed on the Oak Ridge National Laboratory reservation: one using a distributed source within the scene to understand the systematics of detecting and analyzing the clutter, and the second experiment mimicking an urban environment with large buildings positioned on either side of a roadway. The experiments exhibited unique results in the amount of signal suppression and variability of the cluttered signal, both demonstrating an observable suppression from the clutter-free background. These results reveal a new potential category of signal noise intrinsic to real-world detection scenarios that should be considered when establishing detection thresholds based on expected values.

Stewart, Ian R.↗