Systematic comparison of automated geological feature detection methods for impact craters
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The ability to characterize the global cloud cover from space has been greatly enhanced by the availability of MODIS, CloudSat, and CALIOP data. The three sensors provide good complementary information about clouds. In this study, we investigated unexpected observations of certain types of clouds apparent in the MODIS data but not detected by CloudSat and CALIOP. Several examples are presented and generally these undetected clouds are geometrically thin, low-level clouds. In particular, they are located in the Arctic region and have optical thicknesses of less than 14, top height altitudes of below 2.5 km, and layer thickness of less than 1 km. CloudSat may miss such low-level clouds because of its coarse vertical resolution of about 500 m and it has limited sensitivity near the surface. Unexpectedly, CALIOP with a much higher vertical resolution of 30 m also misses these clouds and this is due to the cloud s geometrically thin nature and surface proximity.
A CMOS imager integrated circuit using compressive sensing and bio-inspired detection is presented which integrates novel functions and algorithms within a novel hardware architecture enabling efficient on-chip implementation.
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Walsh functions form an orthonormal basis set consisting of square waves. Square waves make the system well suited for detecting and representing functions with discontinuities. Given a uniform distribution of 2p cells on a one-dimensional element, it has been proven that the inner product of the Walsh Root function for group p with every polynomial of degree < or = (p - 1) across the element is identically zero. It has also been proven that the magnitude and location of a discontinuous jump, as represented by a Heaviside function, are explicitly identified by its Fast Walsh Transform (FWT) coefficients. These two proofs enable an algorithm that quickly provides a Weighted Least Squares fit to distributions across the element that include a discontinuity. The detection of a discontinuity enables analytic relations to locally describe its evolution and provide increased accuracy. Time accurate examples are provided for advection, Burgers equation, and Riemann problems (diaphragm burst) in closed tubes and de Laval nozzles. New algorithms to detect up to two C0 and/or C1 discontinuities within a single element are developed for application to the Riemann problem, in which a contact discontinuity and shock wave form after the diaphragm bursts.
Using GEOS-5, we are developing a 1D ENS approach for assimilating CATS near real time observations of total attenuated backscatter at 1064 nm: a) After performing a 1-ENS assimilation of a cloud-free profile, the GEOS-5 analysis closely followed observed total attenuated backscatter. b) Vertical localization length scales were varied for the well-mixed PBL and the free troposphere After assimilating a cloud free segment of a CATS granule, the fine detail of a dust event was obtained in the GEOS-5 analysis for both total attenuated backscatter and extinction. Future Work: a) Explore horizontal localization and test within a cloudy aerosol layer. b) Address noisy analysis increments in the free troposphere where both CATS and GEOS-5 aerosol loadings are low. c) Develop a technique to screen CATS ground return from profiles. d) "Dynamic" lidar ratio that will evolve in conjunction with simulated aerosol mixtures.
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Radar look direction effects on geological features detectability, considering topographic relief and incidence angles roles in feature enhancement and suppression
Hydrogen fire detection system discovers fires by detecting the flickering ultraviolet radiation emitted by the OH molecule, a short-lived intermediate combustion product found in hydrogen-air flames. In a space application, the system discriminates against false signals from sunlight and rocket engine exhaust plume radiation.
Pin-point landing is required to enable missions to land close, typically within 10 meters, to scientifically important targets in generally hazardous terrain. In Pin Point Landing both high accuracy and high speed estimation of position and orientation is needed to provide input to the control system to safely choose and navigate to a safe landing site. A proposed algorithm called VISion aided Inertial NAVigation (VISINAV) has shown that the accuracy requirements can be met. [2][3] VISINAV was shown in software only, and was expected to use FPGA enhancements in the future to improve the computational speed needed for pin point landing during Entry Descent and Landing (EDL). Homography, feature detection and spatial correlation are computationally intensive parts of VISINAV. Homography aligns the map image with the descent image so that small correlation windows can be used, and feature detection provides regions that spatial correlation can track from frame to frame in order to estimate vehicle motion. On MER the image Homography, Feature Detection and Correlation would take approximately 650ms tracking 75 features between frames. We implemented Homography, Feature detection and Correlation on a Virtex 4 LX160 FPGA to run in under 25ms while tracking 500 features to improve algorithm reliability and throughput.
An expandable and reconfigurable instrument node includes a feature detection means and a data processing portion in communication with the feature detection means, the data processing portion configured and disposed to process feature information. The instrument node further includes a phase locked loop (PLL) oscillator in communication with the data processing portion, the PLL oscillator configured and disposed to provide PLL information to the processing portion. The instrument node further includes a single tone transceiver and a pulse transceiver in communication with the PLL oscillator, the single tone transceiver configured and disposed to transmit or receive a single tone for phase correction of the PLL oscillator and the pulse transceiver configured and disposed to transmit and receive signals for phase correction of the PLL oscillator. The instrument node further includes a global positioning (GPA) receiver in communication with the processing portion, the GPS receiver configured and disposed to establish a global position of the instrument node.
Optical spectra were taken of comets Halley, West, and Brorsen-Metcalf in the wavelength region 3200 to 6400 A. These spectra were offset approximately 10(exp -5) to 10(exp -6) km tailward from the nucleus so that the features detected were all ions with the exception of a very small residual C2 emission at 5165 A. The full labeled tail spectrum of comet Halley is given. While most of the features detected are attributable to CO(+), H2O(+), CO2(+), CH(+), and OH(+), there are three moderately strong bands in the spectra of comets Halley and Brorsen-Metcalf which remain unidentified. These features were not detected in comet West. All three spectra in the 4800 to 5400 A region are presented, Brorsen-Metcalf is the gassiest of the three. The central wavelengths of the unidentified features are 4930, 5300, and 6000 A. In an effort to identify the ions responsible for these features as well as to confirm previous identifications, laboratory spectra of ions were compared with the comet spectra. H2O(+) and CO(+) are known to have extensive emission in the 4800 to 6200 A region. Therefore, the possibility that these unidentified features are due to H2O(+) and CO(+) was investigated. A search for the following bands was conducted: H2O(+) (11-0), H2O(+) (12-0), H2O(+) (13-1), CO(+) (1-1), and CO(+) (0-0). CO(+) (1-1) and CO(+) (0-0) were previously identified and are present in all the spectra examined. The H2O(+) (11-0) band was identified. Comparison of the H2O(+) (11-0) synthetic spectrum with comet Brorsen-Metcalf data is presented. The relative fluxes of the blended H2O(+) lines in the synthetic spectrum match those of the cometary data. After eliminating H2O(+) and CO(+) as significant contributors to the stronger unidentified features, spectra of ions which are not yet identified in the optical region of comets were compared to the data. These ions are NH(+), CS(+), and C2(+). None of these ions appears to be a significant contributor to the optical spectra of these three comets. In conclusion, H2O(+) (11-0) was unabiguously identified in cometary optical spectra. No other molecular ion for which there are laboratory spectra can explain the unidentified features found in the ion tails of comets Halley and Brorsen-Metcalf.
Integrated System Health Management (ISHM) is a capability that focuses on determining the condition (health) of every element in a complex System (detect anomalies, diagnose causes, prognosis of future anomalies), and provide data, information, and knowledge (DIaK)-not just data-to control systems for safe and effective operation. This capability is currently done by large teams of people, primarily from ground, but needs to be embedded on-board systems to a higher degree to enable NASA's new Exploration Mission (long term travel and stay in space), while increasing safety and decreasing life cycle costs of spacecraft (vehicles; platforms; bases or outposts; and ground test, launch, and processing operations). The topics related to this capability include: 1) ISHM Related News Articles; 2) ISHM Vision For Exploration; 3) Layers Representing How ISHM is Currently Performed; 4) ISHM Testbeds & Prototypes at NASA SSC; 5) ISHM Functional Capability Level (FCL); 6) ISHM Functional Capability Level (FCL) and Technology Readiness Level (TRL); 7) Core Elements: Capabilities Needed; 8) Core Elements; 9) Open Systems Architecture for Condition-Based Maintenance (OSA-CBM); 10) Core Elements: Architecture, taxonomy, and ontology (ATO) for DIaK management; 11) Core Elements: ATO for DIaK Management; 12) ISHM Architecture Physical Implementation; 13) Core Elements: Standards; 14) Systematic Implementation; 15) Sketch of Work Phasing; 16) Interrelationship Between Traditional Avionics Systems, Time Critical ISHM and Advanced ISHM; 17) Testbeds and On-Board ISHM; 18) Testbed Requirements: RETS AND ISS; 19) Sustainable Development and Validation Process; 20) Development of on-board ISHM; 21) Taxonomy/Ontology of Object Oriented Implementation; 22) ISHM Capability on the E1 Test Stand Hydraulic System; 23) Define Relationships to Embed Intelligence; 24) Intelligent Elements Physical and Virtual; 25) ISHM Testbeds and Prototypes at SSC Current Implementations; 26) Trailer-Mounted RETS; 27) Modeling and Simulation; 28) Summary ISHM Testbed Environments; 29) Data Mining - ARC; 30) Transitioning ISHM to Support NASA Missions; 31) Feature Detection Routines; 32) Sample Features Detected in SSC Test Stand Data; and 33) Health Assessment Database (DIaK Repository).
Scientists are currently designing instruments, telescopes, and spacecraft to search for evidence of life beyond Earth. This search for life beyond Earth comes with an expectation to detect life that is different than the life found on modern-day Earth. But scientists will also be expected to provide compelling proof behind any claims that we are not alone. These two expectations are seemingly at odds with each other, because it will be easiest to provide compelling evidence for life when we have a deep understanding of the life we are looking at.The study of Earth history provides a means to reconcile this tension. Different periods of Earth history present us with biospheres that are dramatically different from modern-day Earth, but for which we have abundant data. This informs our understanding of habitability, because of the variety of global chemical and climatic conditions in Earth history for which we know life has thrived. The study of Earth history also informs our understanding of how to detect life; as the global influences of life have completely changed, so have the detectable features of Earth's biosphere.The appreciation of our home planet as a tightly coupled system also provides us top-level lessons for how to search for an even broader set of biospheres with a wider variety of detectable features. The study of Earth history has taught us that life is a both a function of and critical forcing on the planetary environment. Numerical models of these interactions can by driven by our understanding of Earth history, and be validated against the geological and geochemical data. These models can then be applied to a wider variety of planetary conditions. This will help scientists determine what kinds of life are possible, and eventually help them recognize and confirm the presence of life on rocky planets around other stars.
Condition queries on distributed data ask where particular conditions are satisfied. It is possible to represent condition queries as geometric objects by plotting field data in various spaces derived from the data, and by selecting loci within these derived spaces which signify the desired conditions. Rather simple geometric partitions of derived spaces can represent complex condition queries because much complexity can be encapsulated in the derived space mapping itself A geometric view of condition queries provides a useful conceptual unification, allowing one to intuitively understand many existing vector field feature detection algorithms -- and to design new ones -- as variations on a common theme. A geometric representation of condition queries also provides a simple and coherent basis for computer implementation, reducing a wide variety of existing and potential vector field feature detection techniques to a few simple geometric operations.
The objective of this work was to enhance the predictive capability of widely used computational fluid dynamic (CFD) codes through the use of solution adaptive gridding. Most problems of engineering interest involve multi-block grids and widely disparate length scales. Hence, it is desirable that the adaptive grid feature detection algorithm be developed to recognize flow structures of different type as well as differing intensity, and adequately address scaling and normalization across blocks. In order to study the accuracy and efficiency improvements due to the grid adaptation, it is necessary to quantify grid size and distribution requirements as well as computational times of non-adapted solutions. Flow fields about launch vehicles of practical interest often involve supersonic freestream conditions at angle of attack exhibiting large scale separate vortical flow, vortex-vortex and vortex-surface interactions, separated shear layers and multiple shocks of different intensity. In this work, a weight function and an associated mesh redistribution procedure is presented which detects and resolves these features without user intervention. Particular emphasis has been placed upon accurate resolution of expansion regions and boundary layers. Flow past a wedge at Mach=2.0 is used to illustrate the enhanced detection capabilities of this newly developed weight function.