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We used comparisons of gravity and geoid with topography in the spatial and spectral domains, together with additional information from the geologic record, to constrain support mechanisms for loads on the surface of Mars and their implications for the planet's crustal and lithospheric properties and evolution.
We are developing onboard planning and scheduling technology to enable in situ robotic explorers, such as rovers and aerobots, to more effectively assist scientists in planetary exploration. In our current work, we are focusing on situations in which the robot is exploring large geographical features such as craters, channels or regional boundaries. In to develop valid and high quality plans, the robot must take into account a range of scientific and engineering constraints and preferences. We have developed a system that incorporates multiobjective optimization and planning allowing the robot to generate high quality mission operations plans that respect resource limitations and mission constraints while attempting to maximize science and engineering objectives. An important scientific objective for the exploration of geological features is selecting observations that spatially cover an area of interest. We have developed a metric to enable an in situ explorer to reason about and track the spatial coverage quality of a plan. We describe this technique and show how it is combined in the overall multiobjective optimization and planning algorithm.
A model of how humans sense the velocity of moving images is proposed. The model exploits constraints provided by human psychophysics, notably that motion-sensing elements appear tuned for two-dimensional spatial frequency, and by the frequency spectrum of a moving image, namely, that its support lies in the plane in which the temporal frequency equals the dot product of the spatial frequency and the image velocity. The first stage of the model is a set of spatial-frequency-tuned, direction-selective linear sensors. The temporal frequency of the response of each sensor is shown to encode the component of the image velocity in the sensor direction. At the second stage, these components are resolved in order to measure the velocity of image motion at each of a number of spatial locations and spatial frequencies. The model has been applied to several illustrative examples, including apparent motion, coherent gratings, and natural image sequences. The model agrees qualitatively with human perception.
Solution of the steady 2-D Euler equations using mesh embedding, or local grid refinement, with a cell-centered finite volume scheme is investigated. Embedded regions which are topologically similar to the global grid are considered. An isoenergetic model for the governing equations is used in Jameson's finite volume multistage scheme with modifications to the boundary conditions and smoothing. A detailed study of the embedding interface flux and smoothing formulations is conducted. Taylor expansion analysis reveals that local second order spatial accuracy is not possible if a conservative interface flux formulation is used. The analysis also gives constraints for local first order accuracy. An energy stability analysis indicates that downwind weighting of interface fluxes causes local instabilities. Analysis shows that conservative interface smoothing formulations must have a locally convective component, but that correct interface formulations allow globally dissipative smoothing. Embedded mesh solutions obtained with this scheme are presented for a transonic airfoil. They show that if embedding interfaces are close to the shocks, then small modifications in the interface location can have large effects on converge and solution accuracy.
(50000) Quaoar, one of the largest Trans-neptunian objects, is comparable in size to Pluto's moon Charon. However, while Charon's surface is rich almost exclusively in H2O ice, Quaoar's surface characterized by ices of CH4, N2, as well as C2H6, a product of irradiation of CH4 (Dalle Ore et al. 2009). Because of its distance from the Sun, Quaoar is expected to have preserved, to a degree, its original composition, however, its relatively small size did not make it a prime candidate for presence of volatile ices in the study by Schaller and Brown (2007). Furthermore, based on the Brown et al. (2011) study (Brown, Schaller, & Fraser, 2011. A Hypothesis for the Color Diversity of the Kuiper Belt. ApJL, 739, L60) its red coloration points to CH3OH as the ice which, when irradiated, might have produced the red material. We present new visible to near-infrared (0.3-2.48 micrometers) spectro-photometric data obtained with the XSHOOTER (Vernet et al. 2011, A&A, 536A, 105 ) instrument at the VLT-ESO facility at four different longitudes on the surface of Quaoar. The data are complemented by previously published photometric observations obtained in the near-infrared (3.6, 4.5 micrometers) with the Spitzer Space Telescope, which provide an extra set of constraints in the model calculation process in spite of the different observing times that preclude establishing the spatial consistency between the two sets. For each of the four spectra we perform spectral modeling of the entire wavelength range -from 0.3 to 4.5 micrometers- by means of a code based on the Shkuratov radiative transfer formulation of the slab model. We obtain spatially resolved compositional information for the surface of Quaoar supporting the presence of CH4 and C2H6, as previously reported, along with evidence for N2 and NH3OH. The albedo at the two Spitzer bands indicates the likely presence of CO and CO2. CH3OH, predicted on the basis of Quaoar's coloration (Brown et al. 2011), is not found at any of the four longitudes, implying that the presence of this ice is a sufficient, but not necessary condition for reddening of TNO surfaces. Other ices, in particular CH4 (Brunetto et al. 2006), have been shown to be plausible precursors for reddening of TNO surfaces.
Uncertainty in top-of-atmosphere (TOA) radiation fluxes observations are larger in the Arctic than in other regions. These uncertainties are due to the low sun angles and the highly reflective, anisotropic, and heterogeneous surface conditions. Quantifying, attributing, and reducing Arctic TOA radiative flux uncertainty enables a better understanding of the rapidly changing Arctic. To advance this goal, we compare the Cloud and Earth’s Radiant Energy System (CERES) TOA radiative fluxes with Arctic Radiation-IceBridge Sea and Ice Experiment (ARISE) campaign measurements collected in September 2014. We compare CERES TOA and aircraft radiative flux measurements using two complementary approaches: grid box average fluxes and instantaneously matched footprints. The grid box mean flux comparison indicates an agreement between CERES and aircraft measurements within 2σ uncertainty (calibration and inversion) in the longwave for all five grid boxes and for four-of-five grid boxes in the shortwave; shortwave and longwave mean differences are -7.9 and +2.3 Wm 2, respectively. The comparison of 36 40 instantaneously matched footprints with aircraft measurements reveals mean differences of -120.25 and -1.00.4 Wm 2 in the shortwave and longwave, respectively. To further explore the persistent negative difference in the shortwave, Wwe further quantify the effects of temporal and spatial sampling differences, angular distribution models, and scene identification to CERES-aircraft differences. Our analysis indicates that sampling differences (including scene evolution) account for an additional 1.8 and 1.7% uncertainty in the shortwave and longwave, respectively and , but indicates no bias. After accounting for this sampling uncertainty, all CERES-aircraft grid box mean fluxes agree within 2σ uncertainty. Scene identification errors due to sea ice concentration data set differences exhibit no bias in the shortwave flux difference and indicate the possibility of substantial differences in the CERES fluxes in specific cases with large spatial heterogeneity. Considering the instantaneously matched footprints, we find that the angular distribution models account may account for up to 7.3 Wm-2 of the persistent CERES-aircraft shortwave flux difference due to systematic differences in the anisotropy for sea ice partly cloudy scenes. Additional analysis using a special programmable scan model with the CERES FM2 instrument suggests a significant view zenith angle dependence of the CERES fluxes for sea ice partly cloudy scenes where shortwave fluxes systematically decrease with increasing view zenith angle; no dependence is found for other scene types. We conclude that (1) spatial heterogeneity and scene temporal evolution substantially limit our ability to use aircraft measurements to place strong constraints on CERES TOA fluxes and (2) that the representation of anisotropy in sea ice partly cloudy scenes is likely a significant factor contributing to the persistent negative CERES-aircraft shortwave flux difference in this comparison and require additional data to analysis fully quantify the potential bias.
Uncertainty in top-of-atmosphere (TOA) radiation fluxes observations are larger in the Arctic than in other regions. These uncertainties are due to the low sun angles and the highly reflective, anisotropic, and heterogeneous surface conditions. Quantifying, attributing, and reducing Arctic TOA radiative flux uncertainty enables a better understanding of the rapidly changing Arctic. To advance this goal, we compare the Cloud and Earth’s Radiant Energy System (CERES) TOA radiative fluxes with Arctic Radiation-IceBridge Sea and Ice Experiment (ARISE) campaign measurements collected in September 2014. We compare CERES TOA and aircraft radiative flux measurements using two complementary approaches: grid box average fluxes and instantaneously matched footprints. The grid box mean flux comparison indicates an agreement between CERES and aircraft measurements within 2 uncertainty (calibration and inversion) in the longwave for all five grid boxes and for four-of-five grid boxes in the shortwave; shortwave and longwave mean differences are -7.9 and +2.3 Wm‑2, respectively. The comparison of 36 instantaneously matched footprints with aircraft measurements reveals mean differences of -10.5 and 0.4 Wm‑2 in the shortwave and longwave, respectively. To further explore the persistent negative difference in the shortwave, we further quantify the effects of temporal and spatial sampling differences, angular distribution models, and scene identification to CERES-aircraft differences. Our analysis indicates that sampling differences (including scene evolution) account for an additional 1.8 and 1.7% uncertainty in the shortwave and longwave, respectively and indicates no bias. After accounting for this sampling uncertainty, all CERES-aircraft grid box mean fluxes agree within 2 uncertainty. Scene identification errors due to sea ice concentration data set differences exhibit no bias in the shortwave flux difference and indicate the possibility of substantial differences in the CERES fluxes in specific cases with large spatial heterogeneity. Considering the instantaneously matched footprints, we find that the angular distribution models account may account for up to ‑7.3 Wm-2 of the persistent CERES-aircraft shortwave flux difference due to systematic differences in the anisotropy for sea ice partly cloudy scenes. Additional analysis using a special scan model with the CERES FM2 instrument suggests a significant view zenith angle dependence of the CERES fluxes for sea ice partly cloudy scenes where shortwave fluxes systematically decrease with increasing view zenith angle; no dependence is found for other scene types. We conclude that (1) spatial heterogeneity and scene temporal evolution substantially limit our ability to use aircraft measurements to place strong constraints on CERES TOA fluxes and (2) that the representation of anisotropy in sea ice partly cloudy scenes is a significant factor contributing to the persistent negative CERES-aircraft shortwave flux difference in this comparison and require additional data to analysis fully quantify the potential bias.
The assumed-modes method in multibody dynamics allows the elastic deformation of each component in the system to be approximated by a sum of products of spatial and temporal functions commonly known as modes and modal coordinates respectively. The choice of component modes used to model articulating and non-articulating flexible multibody systems is examined. Attention is directed toward three classical Component Mode Synthesis (CMS) methods whereby component normal modes are generated by treating the component interface (I/F) as either fixed, free, or loaded with mass and stiffness contributions from the remaining components. The fixed and free I/F normal modes are augmented by static shape functions termed constraint and residual modes respectively. A mode selection procedure is outlined whereby component modes are selected from the Craig-Bampton (fixed I/F plus constraint), MacNeal-Rubin (free I/F plus residual), or Benfield-Hruda (loaded I/F) mode sets in accordance with a modal ordering scheme derived from balance realization theory. The success of the approach is judged by comparing the actuator-to-sensor frequency response of the reduced order system with that of the full order system over the frequency range of interest. A finite element model of the Galileo spacecraft serves as an example in demonstrating the effectiveness of the proposed mode selection method.
We will formulate the problem of resolving spatial (space occupancy and support-stability) interactions in terms of tools developed in Operating Systems for the problems of deadlocks and synchronization. We show how to construct state graphs and to detect resource contentions and deadlocks from these state graphs. We describe an algorithm, called CONTAC, to deal with deadlocks where 'processes' represent the ordered motions of parts. The algorithm is a monitor-like process using preventative preemptive protocol to resolve higher-degree deadlocks. We develop the representation for knowledge about current allocations, pending requests, and synchronization constraints, to generate a contention-free sequence of actions. In this paper we focus on modeling deadlocks which are manifestations of spatial interactions.
In order to overcome spatial resolution limitations associated with physical sensor limitations when using smallsats and cubesats, we utilize an image processing technology referred to as Super-Resolution (SR). In general, software approaches are increasingly considered in connection with smaller satellites for which size, mass and power constraints limit the sensor capabilities. Being able to perform hardware vs. software trades might enable more capabilities for a lower cost. This paper describes recent experiments conducted to optimize the spatial enhancement of acquired observations using multiple sub-pixel shifted low resolution image.
In order to overcome spatial resolution limitations associated with physical sensor limitations when using smallsats and cubesats, we utilize an image processing technology referred to as Super-Resolution (SR). In general, software approaches are increasingly considered in connection with smaller satellites for which size, mass and power constraints limit the sensor capabilities. Being able to perform hardware vs. software trades might enable more capabilities for a lower cost. This paper describes recent experiments conducted to optimize the spatial enhancement of acquired observations using multiple sub-pixel shifted low resolution image.
The author has identified the following significant results. Geometric correspondance between a sensed image and a symbolic map is established in an initial stage of processing by adjusting parameters of a sensed model so that the image features predicted from the map optimally match corresponding features extracted from the sensed image. Information in the map is then used to constrain where to look in an image, what to look for, and how to interpret what is seen. For simple monitoring tasks involving multispectral classification, these constraints significantly reduce computation, simplify interpretation, and improve the utility of the resulting information. Previously intractable tasks requiring spatial and textural analysis may become straightforward in the context established by the map knowledge. The use of map-guided image analysis in monitoring the volume of water in a reservoir, the number of boxcars in a railyard, and the number of ships in a harbor is demonstrated.
The ultimate goal of virtual acoustics is to simulate the complex acoustic field experienced by a listener freely moving around within an environment. This paper discusses some of the engineering constraints that may be faced during implementation and the perceptual consequences of these constraints. In particular, the perceptual impact of parameters like the update rate and overall system latency of interactive spatial audio systems is addressed.
While most of the intergalactic medium (IGM) today is permeated by ionized hydrogen, it was largely filled with neutral hydrogen for the first 700 million years after the big bang. The process that ionized the IGM (cosmic reionization) is expected to be spatially inhomogeneous, with fainter galaxies likely playing a significant role. However, we still have only a few direct constraints on the reionization process. Here we report spectroscopic confirmation of two galaxies and very likely a third galaxy in a group (hereafter EGS77) at redshift z = 7.7, merely 680 Myr after the big bang. The physical separation among the three members is <0.7 Mpc. We estimate the radius of ionized bubble of the brightest galaxy to be about 1.02 Mpc, and show that the individual ionized bubbles formed by all three galaxies likely overlap significantly, forming a large yet localized ionized region, indicative of inhomogeneity in the reionization process. It is striking that two of three galaxies in EGS77 are quite faint in the continuum, thanks to our selection using their Lyα line emission in the narrowband filter. Indeed, one is the faintest spectroscopically confirmed galaxy yet discovered at such high redshifts. Our observations provide direct constraints on the process of cosmic reionization, and allow us to investigate the properties of sources responsible for reionizing the universe.
Light detection and ranging (LiDAR) data can provide direct measurements of vegetation structures but are limited by the sparse spatial coverage. Polarimetric synthetic aperture radar (SAR) can perform large-scale high-resolution mapping without weather constraints but the information about vegetation and ground subsurface are mixed in the backscatter data. In this paper, we adopted the Random Forests algorithm to train an upscaling function using tree canopy cover (TCC) and canopy height model (CHM) derived from Goddard’s LiDAR, Hyperspectral and Thermal Imager (G-LiHT) data. The regression model is then applied to the L-band Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR) data acquired during the 2017 Arctic-Boreal Vulnerability Experiment (ABoVE) airborne campaign to map the TCC and CHM over the Delta Junction area in interior Alaska.
A methodology for improving gravity-gradient measurement data exploits the constraints imposed upon the components of the gravity-gradient tensor by the conditions of integrability needed for reconstruction of the gravitational potential. These constraints are derived from the basic equation for the gravitational potential and from mathematical identities that apply to the gravitational potential and its partial derivatives with respect to spatial coordinates. Consider the gravitational potential in a Cartesian coordinate system {x1,x2,x3}. If one measures all the components of the gravity-gradient tensor at all points of interest within a region of space in which one seeks to characterize the gravitational field, one obtains redundant information. One could utilize the constraints to select a minimum (that is, nonredundant) set of measurements from which the gravitational potential could be reconstructed. Alternatively, one could exploit the redundancy to reduce errors from noisy measurements. A convenient example is that of the selection of a minimum set of measurements to characterize the gravitational field at n3 points (where n is an integer) in a cube. Without the benefit of such a selection, it would be necessary to make 9n3 measurements because the gravitygradient tensor has 9 components at each point. The problem of utilizing the redundancy to reduce errors in noisy measurements is an optimization problem: Given a set of noisy values of the components of the gravity-gradient tensor at the measurement points, one seeks a set of corrected values - a set that is optimum in that it minimizes some measure of error (e.g., the sum of squares of the differences between the corrected and noisy measurement values) while taking account of the fact that the constraints must apply to the exact values. The problem as thus posed leads to a vector equation that can be solved to obtain the corrected values.
The X-Ray telescopes (XRT) for the US/Japan collaborative mission Astro-E2 will be of the same basic design as those built for the original Astro-E mission which failed to reach orbit in Feb. 2000. The NASA/GSFC X-ray Astrophysics Branch will again provide the five lightweight, broad-band mirrors for the mission. X-ray calibrations of the mirrors delivered for the original Astro-E instrument showed spatial resolutions characterized by Half-Power Diameters (HPD) in the range of 1.8 - 2.2 minutes of arc, essentially independent of photon energy in the soft X-ray band. For the mission Astro-E2, both funding constraints and management decisions drastically limit any design modifications, so reflector fabrication and assembly procedures have remained largely unchanged. Nevertheless, in view of the importance in scientific return of attaining even a modest improvement in the spatial resolution of these mirrors, we have carefully considered the various sources of spatial error and, whenever possible, incorporated promising modifications. In this paper, we discuss our current understanding of the various error components as well as the small changes we have been able to implement.
The mathematical formulation associated with the problem of stability of motion of a satellite consisting of a main rigid body and three (or less) pairs of flexible rods is presented. The rods are capable of flexure in two orthogonal directions. Whereas the rotational motion of the body is described by generalized coordinates depending on time alone, the elastic displacements of the rods depend both on spatial position and time. Assuming no external torques, there exist motion integrals in the form of momentum integrals. These integrals can be regarded as constraint equations relating the system velocities, and used to reduce the number of variables describing the motion. The stability analysis has been carried out by means of an extension of the Liapunov direct method. Since the elastic vibrations result in energy dissipation, it is shown that the equilibrium position is asymptotically stable if the Hamiltonian is positive definite and unstable if it can take negative values in the neighborhood of the equilibrium. Determining the sign definiteness of the Hamiltonian is complicated by the fact that it contains spatial derivatives of the elastic displacements. Two methods are presented to cope with this problem. The first, the standard modal analysis in conjunction with series truncation, develops criteria in terms of infinite series associated with the natural modes and frequencies of the elastic rods. The second, the method of integral coordinates, yields closed-form stability criteria involving the system parameters, such as the body moments of inertia, the length and mass distribution of the rods, the lowest natural frequencies of the rods, and the satellite spin velocity.