The ASTER Imaging Sensor on NASA's Terra Platform
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It has been demonstrated that current-generation global ocean general circulation models (OGCM) are able to simulate large-scale sea level variations fairly well. In this study, a GFDL/MOM-based OGCM was used to investigate its sensitivity to different wind forcing. Simulations of global sea level using wind forcing from the ERS-1 Scatterometer and the NMC operational analysis were compared to the observations made by the TOPEX/Poseidon (T/P) radar altimeter for a two-year period. The result of the study has demonstrated the sensitivity of the OGCM to the quality of wind forcing, as well as the synergistic use of two spaceborne sensors in advancing the study of wind-driven ocean dynamics.
Advanced satellite sensors are tasked with improving global measurements of the Earth's atmosphere, clouds, and surface to enable enhancements in weather prediction, climate monitoring capability, and environmental change detection. Measurement system validation is crucial to achieving this goal and maximizing research and operational utility of resultant data. Field campaigns including satellite under-flights with well calibrated FTS sensors aboard high-altitude aircraft are an essential part of the validation task. This presentation focuses on an overview of validation methodology developed for assessment of high spectral resolution infrared systems, and includes results of preliminary studies performed to investigate the performance of the Infrared Atmospheric Sounding Interferometer (IASI) instrument aboard the MetOp-A satellite.
A need exists for miniaturized, rugged, low-cost high-vacuum systems. Recent advances in sensor technology have led to the development of very small mass spectrometer detectors as well as other analytical instruments such as scanning electron microscopes. However, the vacuum systems to support these sensors remain large, heavy, and power-hungry. To meet this need, a miniaturized vacuum system was developed based on a very small, rugged, and inexpensive-to-manufacture molecular drag pump (MDP). The MDP is enabled by a miniature, very-high-speed (200,000 rpm), rugged, low-power, brushless DC motor optimized for wide temperature operation and long life. The key advantages of the pump are reduced cost and improved ruggedness compared to other mechanical hig-hvacuum pumps. The machining of the rotor and stators is very simple compared to that necessary to fabricate rotor and stator blades for other pump designs. Also, the symmetry of the rotor is such that dynamic balancing of the rotor will likely not be necessary. Finally, the number of parts in the unit is cut by nearly a factor of three over competing designs. The new pump forms the heart of a complete vacuum system optimized to support analytical instruments in terrestrial applications and on spacecraft and planetary landers. The MDP achieves high vacuum coupled to a ruggedized diaphragm rough pump. Instead of the relatively complicated rotor and stator blades used in turbomolecular pumps, the rotor in the MDP consists of a simple, smooth cylinder of aluminum. This will turn at approximately 200,000 rpm inside an outer stator housing. The pump stator comprises a cylindrical aluminum housing with one or more specially designed grooves that serve as flow channels. To minimize the length of the pump, the gas is forced down the flow channels of the outer stator to the base of the pump. The gas is then turned and pulled toward the top through a second set of channels cut into an inner stator housing that surrounds the motor. The compressed gas then flows down channels in the motor housing to the exhaust port of the pump. The exhaust port of the pump is connected to a commercially available diaphragm or scroll pump.
As the need grows for increased autonomy and position knowledge accuracy to support missions beyond Earth orbit, engineers must push and develop more advanced navigation sensors and systems that operate independent of Earth-based analysis and processing. Several spacecraft are approaching this problem using inter-spacecraft radiometric tracking and onboard autonomous optical navigation methods. This paper proposes an alternative implementation to aid in spacecraft position fixing. The proposed method Network-Based Navigation technique takes advantage of the communication data being sent between spacecraft and between spacecraft and ground control to embed navigation information. The navigation system uses these packets to provide navigation estimates to an onboard navigation filter to augment traditional ground-based radiometric tracking techniques. As opposed to using digital signal measurements to capture inherent information of the transmitted signal itself, this method relies on the embedded navigation packet headers to calculate a navigation estimate. This method is heavily dependent on clock accuracy and the initial results show the promising performance of a notional system.
Advances in sensors and avionics computation power suggest real-time structural load measurements could be used in flight control systems for improved safety and performance. A conventional transport flight control system determines the moments necessary to meet the pilot's command, while rejecting disturbances and maintaining stability of the aircraft. Control allocation is the problem of converting these desired moments into control effector commands. In this paper, a framework is proposed to incorporate real-time structural load feedback and structural load constraints in the control allocator. Constrained optimal control allocation can be used to achieve desired moments without exceeding specified limits on monitored load points. Minimization of structural loads by the control allocator is used to alleviate gust loads. The framework to incorporate structural loads in the flight control system and an optimal control allocation algorithm will be described and then demonstrated on a nonlinear simulation of a generic transport aircraft with flight dynamics and static structural loads.
NASA, DoD, DHS, and commercial industry have a need for miniaturized, rugged, low-cost vacuum systems. Recent advances in sensor technology have led to the development of very small mass spectrometer detectors as well as other miniature analytical instruments. However, the vacuum systems to support these sensors remain large, heavy, and power-hungry. To meet this need, a miniaturized vacuum system was created based on a very small, rugged, and inexpensive- to-manufacture molecular drag pump (MDP). The MDP is enabled by the development of a miniature, veryhigh- speed, rugged, low-power, brushless DC motor optimized for wide temperature operation and long life. Such a pump represents an order-of-magnitude reduction in mass, volume, and cost over current, commercially available, state-ofthe- art vacuum pumps. The vacuum system consists of the MDP coupled to a ruggedized rough pump (for terrestrial applications or for planets with substantial atmospheres). The rotor in the MDP consists of a simple smooth cylinder of aluminum spinning at approximately 200,000 RPM inside an outer stator housing. The pump stator comprises a cylindrical aluminum housing with one or more specially designed grooves that serve as flow channels. To minimize the length of the pump, the gas is forced down the flow channels of the outer stator to the base of the pump. The gas is then turned and pulled toward the top through a second set of channels cut into an inner stator housing that surrounds the motor. The compressed gas then flows down channels in the motor housing to the exhaust port of the pump. The exhaust port of the pump is connected to a diaphragm or scroll pump. This pump delivers very high performance in a very small envelope. The design was simplified so that a smaller compression ratio, easier manufacturing process, and enhanced ruggedness can be achieved at the lowest possible cost. The machining of the rotor and stators is very simple compared to that necessary to fabricate TMP (turbo molecular pump) rotor and stator blades. Also, the symmetry of the rotor is such that dynamic balancing of the rotor is greatly simplified. Finally, because of the simplified design, the number of parts in the unit is cut by nearly a factor of three. In fact, there are only five parts, not counting the motor and off-the-shelf screws and O-rings. This reduces the amount of machining and also makes fit-up much simpler while allowing the maintenance of close tolerances.
Remote sensing is one of a suite of geospatial technologies that are having a growing impact in a wide variety of areas from commerce to science to public policy. The field of remote sensing evolved from the interpretation of aerial photographs to the analysis of satellite imagery, and from local area studies to global analyses, with advances in sensor system technologies and digital computing. Today remote sensor systems can provide data from energy emitted, reflected, and/or transmitted from all parts of the electromagnetic spectrum. Examples of applications of these data include population and demography studies, study of archaeological sites, energy studies using hydrological models, urban planning, environmental monitoring, environments, treaty enforcement, land use/land cover planning, weather forecasting, and agricultural production estimation, just to name a few. The material that follows provides a brief overview of the historical development of remote sensing, emphasizing the increasing complexity of platforms, systems, and tasks.
National Security Space (NSS) presents multi-faceted S and T challenges. We must continually innovate enterprise and information management; provide decision support; develop advanced materials; enhance sensor technology; transform communication technology; develop advanced propulsion and resilient space architectures and capabilities; and enhance multiple additional S and T domains. These challenges are best met by leveraging advanced S and T research and technology development from a number of DoD agencies and civil agencies such as NASA. The authors of this paper have engaged in these activities since 2006 and over the past decade developed multiple strategic S and T relationships. This paper highlights the Office of the Space Missile Systems Center (SMC) Chief Scientist (SMC/ST) collaboration with the NASA Office of Chief Technologist (NASA OCT), which has multiple S and T activities that are relevant to NSS. In particular we discuss the development of the Technology Roadmaps that benefit both Civil Space and NSS. Our collaboration with NASA OCT has been of mutual benefit to multiple participants. Some of the other DoD components include the Defense Advanced Research Projects agency (DARPA), Air Force Research Laboratory (AFRL), Naval Research Laboratory (NRL), The USAF Office of Chief Scientist, the USAF Science Advisory Board (SAB), Space and Naval Warfare Systems Command (SPAWAR), and a number of other services and agencies. In addition, the human talent is a key enabler of advanced S and T activities; it is absolutely critical to have a strong supply of talent in the fields of Science Technology, Engineering, and Mathematics (STEM). Consequently, we continually collaborate with the USAF Institute of Technology (AFIT), other service academies and graduate schools, and other universities and colleges. This paper highlights the benefits that result from such strategic S and T partnerships and recommends a way forward that will continually build upon these achievements into the future.
NASA field center Marshall Space Flight Center (Huntsville, AL), has invested in advanced wireless sensor technology development. Developments for a wireless microcontroller back-end were primarily focused on the commercial Synapse Wireless family of devices. These devices have many useful features for NASA applications, good characteristics and the ability to be programmed Over-The-Air (OTA). The effort has focused on two widely used sensor types, mechanical strain gauges and thermal sensors. Mechanical strain gauges are used extensively in NASA structural testing and even on vehicle instrumentation systems. Additionally, thermal monitoring with many types of sensors is extensively used. These thermal sensors include thermocouples of all types, resistive temperature devices (RTDs), diodes and other thermal sensor types. The wireless thermal board will accommodate all of these types of sensor inputs to an analog front end. The analog front end on each of the sensors interfaces to the Synapse wireless microcontroller, based on the Atmel Atmega128 device. Once the analog sensor output data is digitized by the onboard analog to digital converter (A/D), the data is available for analysis, computation or transmission. Various hardware features allow custom embedded software to manage battery power to enhance battery life. This technology development fits nicely into using numerous additional sensor front ends, including some of the low-cost printed circuit board capacitive moisture content sensors currently being developed at Auburn University.
NASA airborne missions in 2011 and 2013 over Monterey Bay, CA, demonstrated novel above- and in-water calibration and validation measurements supporting a combined airborne sensor approach (imaging spectrometer, microradiometers, and a sun photometer). The resultant airborne data characterize contemporaneous coastal atmospheric and aquatic properties plus sea-truth observations from state-of-the-art instrument systems spanning a next-generation spectral domain (320-875 nm). This airborne instrument suite for calibration, validation, and research flew at the lowest safe altitude (ca. 100 ft or 30 m) as well as higher altitudes (e.g., 6,000 ft or 1,800 m) above the sea surface covering a larger area in a single synoptic sortie than ship-based measurements at a few stations during the same sampling period. Data collection of coincident atmospheric and aquatic properties near the sea surface and at altitude allows the input of relevant variables into atmospheric correction schemes to improve the output of corrected imaging spectrometer data. Specific channels support legacy and next-generation satellite capabilities, and flights are planned to within 30 min of satellite overpass. This concept supports calibration and validation activities of ocean color phenomena (e.g., river plumes, algal blooms) and studies of water quality and coastal ecosystems. The 2011 COAST mission flew at 100 and 6,000 ft on a Twin Otter platform with flight plans accommodating the competing requirements of the sensor suite, which included the Coastal-Airborne In-situ Radiometers (C-AIR) for the first time. C-AIR (Biospherical Instruments Inc.) also flew in the 2013 OCEANIA mission at 100 and 1,000 ft on the Twin Otter below the California airborne simulation of the proposed NASA HyspIRI satellite system comprised of an imaging spectrometer and thermal infrared multispectral imager on the ER-2 at 65,000 ft (20,000 m). For both missions, the Compact-Optical Profiling System (Biospherical Instruments, Inc.), an in-water system with microradiometers matching C-AIR, was deployed to compare sea-truth measurements and low-altitude Twin Otter flights within Monterey Bay red tide events. This novel airborne and in-water sensor capability advances the science of coastal measurements and enables rapid response for coastal events.
The Space Servicing Capabilities Project (SSCP) at NASA's Goddard Space Flight Center (GSFC) has been tasked with developing systems for servicing space assets. Starting in 2009, the SSCP completed a study documenting potential customers and the business case for servicing, as well as defining several notional missions and required technologies. In 2010, SSCP moved to the implementation stage by completing several ground demonstrations and commencing development of two International Space Station (ISS) payloads-the Robotic Refueling Mission (RRM) and the Dextre Pointing Package (DPP)--to mitigate new technology risks for a robotic mission to service existing assets in geosynchronous orbit. This paper introduces the DPP, scheduled to fly in July of 2012 on the third operational SpaceX Dragon mission, and its Autonomous Rendezvous and Docking (AR&D) instruments. The combination of sensors and advanced avionics provide valuable on-orbit demonstrations of essential technologies for servicing existing vehicles, both cooperative and non-cooperative.
Many numerical weather prediction (NWP) centers assimilate radiances affected by clouds and precipitation from microwave sensors, with the expectation that these data can provide critical constraints on meteorological parameters in dynamically sensitive regions to make significant impacts on forecast accuracy for precipitation. The Global Modeling and Assimilation Office (GMAO) at NASA Goddard Space Flight Center assimilates all-sky microwave radiance data from various microwave sensors such as all-sky GPM Microwave Imager (GMI) radiance in the Goddard Earth Observing System (GEOS) atmospheric data assimilation system (ADAS), which includes the GEOS atmospheric model, the Gridpoint Statistical Interpolation (GSI) atmospheric analysis system, and the Goddard Aerosol Assimilation System (GAAS). So far, most of NWP centers apply same large data thinning distances, that are used in clear-sky radiance data to avoid correlated observation errors, to all-sky microwave radiance data. For example, NASA GMAO is applying 145 km thinning distances for most of satellite radiance data including microwave radiance data in which all-sky approach is implemented. Even with these coarse observation data usage in all-sky assimilation approach, noticeable positive impacts from all-sky microwave data on hurricane track forecasts were identified in GEOS-5 system. The motivation of this study is based on the dynamic thinning distance method developed in our all-sky framework to use of denser data in cloudy and precipitating regions due to relatively small spatial correlations of observation errors. To investigate the benefits of all-sky microwave radiance on hurricane forecasts, several hurricane cases selected between 2016-2017 are examined. The dynamic thinning distance method is utilized in our all-sky approach to understand the sources and mechanisms to explain the benefits of all-sky microwave radiance data from various microwave radiance sensors like Advanced Microwave Sounder Unit (AMSU-A), Microwave Humidity Sounder (MHS), and GMI on GEOS-5 analyses and forecasts of various hurricanes.
The state of the art of Big Earth Data Analytics can be expected to evolve rapidly in the coming years. The forces driving evolution come from both growth in the data and advancement in the field of data analytics. In the data area, advances in sensor instrumentation and platform miniaturization are increasing both data resolution and coverage, resulting in enormous growth in data Volume. Increases in temporal resolution in particular also generate demands for higher data Velocity. At the same time, the proliferation of instruments and the platforms on which they reside is increasing the Variety of datasets. The Variety increase in turn leads to questions about the Veracity of the data. In the algorithm area, powerful machine learning methods are coming to the fore, particularly Deep Neural Networks. These are powerful at detecting interesting features in the data, integrating many different measurements (i.e., data fusion), and classification problems. However, they are still challenging when seeking explanations of how natural or socio-economic phenomena work using Earth Observations. Thus, classical analysis techniques will remain relevant when the emphasis is on forming or testing explanations, as well as to support interactive data exploration.
Satellite data from the past several decades provide the most consistent record of land-surface processes that form the basis for scientific assessments of the impacts of climate variations and changes on the environment and human social-economical activities. During this time, scientific research on the characterization and assessment of environmental changes had tended to focus on large-scale land-surface changes with significant social-economic impacts. Increasingly, attention is shifting toward changes that occur more locally and that most directly relate to the everyday life of the majority of the population. In addition, there has been needs to develop management and policy decision support systems that are based on local environmental information. Almost at the same time, the advancement in sensor technology has allowed us to collect an unprecedented volume of environmental data. These data must be curated and analyzed to extract useful information for research and decision support purposes. Established in 2013 and funded by NASA, the Open NASA Earth eXchange (OpenNEX; https://opennex.org/ , Jia et al., 2019 ) project partnered with Amazon Web Services (AWS) to make available a large amount of Earth observing data, modeling results, and analysis tools on the AWS. OpenNEX provides researchers, developers, educators, and ordinary users with easy access to an integrated Earth science computational and data platform, enabling citizen scientists and application developers to realize the full value of NASA data assets and software tools. To encourage the public's engagement in this project, NASA ran virtual workshops and prize competitions. The virtual workshops provided online lectures and tutorials about how prominent scientists used the data in their research and the tutorials gave examples how to use the tools to interrogate the data in the Amazon cloud. Finally, the prize competitions allowed much wider participation in the OpenNEX project and enable testing the non-traditional projects and out-of-box ideas. OpenNEX has continued to evolve and mature. Here, we highlight new features and functionalities available to the community.
The Earth science community is experiencing a high influx of remote sensing data due to recent advancements in sensor technology. This enables the community to extend their research on a larger scale than ever before. Unfortunately, traditional data processing techniques do not scale well to these new, high volume data sources. State-of-the-art machine learning (ML) pipelines have been proven to overcome these burdens in various other fields but are underexploited within the physical sciences community. Moreover, ML is reliant on labeled data, which is currently sparsely available, owing to the fact that ML adoption is still in the early stages within the Earth and atmospheric science communities. To address these issues, we developed the Phenomena Portal, a visual exploration tool that uses ML to detect various atmospheric phenomena on a global scale. This allows the Earth and atmospheric science communities to view trends of occurrences of phenomena, identify potential relationships between them, and analyze spatiotemporal patterns over time. These detections can also serve as initial labeled data for ML research pertaining to the respective phenomena. The tool also incorporates feedback from subject matter experts to further improve the model detection accuracy, thereby facilitating human-in-the-loop. This presentation will provide an overview of the ML model development and cloud deployment. We also discuss the capabilities of the user interface for displaying the detections.
Multi-to hyperspectral evolution of satellite ocean color sensors is advancing space-based coastal ocean science and applications. An approach for optically partitioning phytoplankton (microalgae) communities into component groups is being developed for the Chesapeake Bay.
Small satellites have become an accepted platform for enabling high-quality science measurements and observations. NASA missions have leveraged advances in sensor miniaturization, technology innovations, and new small satellite mission architectures to support high spatial and temporal measurements, continuity measurements, and constellations in response to science objectives described in NASA’s Decadal Surveys. Across six divisions of the Science Mission Directorate (SMD), over 12 years, SMD has funded 88 CubeSat/ SmallSat Missions and 59 Studies to date. Currently, SMD has 53 small spacecraft science missions (87spacecraft) in implementation or formulation. This paper provides the background of efforts to promote the implementation of small satellites within NASA as a balanced portfolio for the agency’s science, technology, and exploration goals. We include analysis of SmallSat awards and trends funded by SMD through Research Opportunities in Space and Earth Sciences (ROSES), Small Innovative Missions for Planetary Exploration (SIMPLEx), and Small Explorer (SMEX) and Medium Explorer (MIDEX) calls over the last 12years. The data source of this assessment is a subset of the NASA SmallSat Coordination Group Database, a collection of all known funded NASA SmallSat and CubeSat missions and studies. This paper also provides an overview of small satellite programs and selected missions from SMD’s divisions: Astrophysics, Heliophysics, Earth Science, and Planetary Science, and describes SMD’s efforts in fostering an incremental and continuous path to achieve high-priority science through transformative science measurements. This paper recognizes the latest observations and trends of the NASA CubeSat / SmallSat Science missions with masses ranging between 1kg to 500kg.