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At least 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
NASA NTRS2007

NASA CEV Reference GN&C Architecture

The Orion Crew Exploration Vehicle (CEV) will be the first human spacecraft built by NASA in almost 3 decades and will be the first vehicle to perform both Low Earth Orbit (LEO) missions and lunar missions since Apollo. The awesome challenge of designing a Guidance, Navigation, and Control (GN&C) system for this vehicle that satisfies all of its various mission requirements is countered by the opportunity to take advantage of the improvements in algorithms, software, sensors, and other related GN&C technology over this period. This paper describes the CEV GN&C reference architecture developed to support the overall NASA reference configuration and validate the driving requirements of the Constellation (Cx) Architecture Requirements Document (CARD, Reference 1) and the CEV System Requirements Document (SRD, Reference 2). The Orion GN&C team designed the reference architecture based on the functional allocation of GN&C roles and responsibilities of CEV with respect to the other Cx vehicles, such as the Crew Launch Vehicle (CLV), Earth Departure Stage (EDS), and Lunar Surface Area Module (LSAM), across all flight phases. The specific challenges and responsibilities of the CEV GN&C system from launch pad to touchdown will be introduced along with an overview of the navigation sensor suite, its redundancy management, and flight software (FSW) architecture. Sensors will be discussed in terms of range of operation, data utility within the navigation system, and rationale for selection. The software architecture is illustrated via block diagrams, commensurate with the design aspects.

Tamblyn, Scott↗
NASA NTRS1989

Precision Segmented Reflector figure control system architecture

A control system architecture for an actively controlled segmented reflector is described along with a design realization for achieving precision alignment of reflector panels. Performance requirements are derived in part from the Large Deployable Reflector, which is a representative mission, and error allocations are made which consider mirror panel surface errors, position measurement and figure estimation, and position control of both quasi-static and dynamic disturbances. The design uses multiple wavelength interferometric edge sensors and voice coil actuators in conjunction with a hybrid control strategy to correct panel position errors. A unit cell shown to be central to the concept is analyzed. The cell integrates the sensing, actuation, and mechanical functions of a control module together with a reflector panel to form a unitized assembly.

Mettler, E.↗
NASA NTRS2009

Expert system for controlling plant growth in a contained environment

In a system for optimizing crop growth, vegetation is cultivated in a contained environment, such as a greenhouse, an underground cavern or other enclosed space. Imaging equipment is positioned within or about the contained environment, to acquire spatially distributed crop growth information, and environmental sensors are provided to acquire data regarding multiple environmental conditions that can affect crop development. Illumination within the contained environment, and the addition of essential nutrients and chemicals are in turn controlled in response to data acquired by the imaging apparatus and environmental sensors, by an ''expert system'' which is trained to analyze and evaluate crop conditions. The expert system controls the spatial and temporal lighting pattern within the contained area, and the timing and allocation of nutrients and chemicals to achieve optimized crop development. A user can access the ''expert system'' remotely, to assess activity within the growth chamber, and can override the ''expert system''.

May, George A.↗
NASA NTRS2011

Expert system for controlling plant growth in a contained environment

In a system for optimizing crop growth, vegetation is cultivated in a contained environment, such as a greenhouse, an underground cavern or other enclosed space. Imaging equipment is positioned within or about the contained environment, to acquire spatially distributed crop growth information, and environmental sensors are provided to acquire data regarding multiple environmental conditions that can affect crop development. Illumination within the contained environment, and the addition of essential nutrients and chemicals are in turn controlled in response to data acquired by the imaging apparatus and environmental sensors, by an "expert system" which is trained to analyze and evaluate crop conditions. The expert system controls the spatial and temporal lighting pattern within the contained area, and the timing and allocation of nutrients and chemicals to achieve optimized crop development. A user can access the "expert system" remotely, to assess activity within the growth chamber, and can override the "expert system".

May, George A.↗
NASA NTRS2002

Microwave-Driven Multifunctional Capability of Membrane Structures

A large, ultra lightweight space structure, such as solar sails and Gossamer spacecrafts, requires a distributed power source to alleviate wire networks, unlike the localized on-board power infrastructures typically found in most small spacecrafts. The concept of microwave-driven multifunctional capability for membrane structures is envisioned as the best option to alleviate the complexity associated with hard-wired control circuitry and on-board power infrastructures. A rectenna array based on a patch configuration for high voltage output was developed to drive membrane actuators, sensors, probes, or other devices. Networked patch rectenna array receives and converts microwave power into a DC power for an array of smart actuators. To use microwave power effectively, the concept of a power allocation and distribution (PAD) circuit is adopted for networking a rectenna/actuator patch array. The use of patch rectennas adds a significant amount of rigidity to membrane flexibility and they are relatively heavy. A dipole rectenna array (DRA) appears to be ideal for thin-film membrane structures, since DRA is flexible and light. Preliminary design and fabrication of PAD circuitry that consists of a few nodal elements were made for laboratory testing. The networked actuators were tested to correlate the network coupling effect, power allocation and distribution, and response time.

Choi, Sang H.↗
NASA NTRS2014

The MAVEN Magnetic Field Investigation

The MAVEN magnetic field investigation is part of a comprehensive particles and fields subsystem that will measure the magnetic and electric fields and plasma environment of Mars and its interaction with the solar wind. The magnetic field instrumentation consists of two independent tri-axial fluxgate magnetometer sensors, remotely mounted at the outer extremity of the two solar arrays on small extensions ("boomlets"). The sensors are controlled by independent and functionally identical electronics assemblies that are integrated within the particles and fields subsystem and draw their power from redundant power supplies within that system. Each magnetometer measures the ambient vector magnetic field over a wide dynamic range (to 65,536 nT per axis) with a quantization uncertainty of 0.008 nT in the most sensitive dynamic range and an accuracy of better than 0.05%. Both magnetometers sample the ambient magnetic field at an intrinsic sample rate of 32 vector samples per second. Telemetry is transferred from each magnetometer to the particles and fields package once per second and subsequently passed to the spacecraft after some reformatting. The magnetic field data volume may be reduced by averaging and decimation, when necessary to meet telemetry allocations, and application of data compression, utilizing a lossless 8-bit differencing scheme. The MAVEN magnetic field experiment may be reconfigured in flight to meet unanticipated needs and is fully hardware redundant. A spacecraft magnetic control program was implemented to provide a magnetically clean environment for the magnetic sensors and the MAVEN mission plan provides for occasional spacecraft maneuvers - multiple rotations about the spacecraft x and z axes - to characterize spacecraft fields and/or instrument offsets in flight.

Magnetic↗
NASA NTRS1992

Geostationary Operational Environmental Satellite (GOES-N report). Volume 2: Technical appendix

The contents include: operation with inclinations up to 3.5 deg to extend life; earth sensor improvements to reduce noise; sensor configurations studied; momentum management system design; reaction wheel induced dynamic interaction; controller design; spacecraft motion compensation; analog filtering; GFRP servo design - modern control approach; feedforward compensation as applied to GOES-1 sounder; discussion of allocation of navigation, inframe registration and image-to-image error budget overview; and spatial response and cloud smearing study.

Source record↗
NASA NTRS1988

Expert system for on-board satellite scheduling and control

An Expert System is described which Rockwell Satellite and Space Electronics Division (S&SED) is developing to dynamically schedule the allocation of on-board satellite resources and activities. This expert system is the Satellite Controller. The resources to be scheduled include power, propellant and recording tape. The activities controlled include scheduling satellite functions such as sensor checkout and operation. The scheduling of these resources and activities is presently a labor intensive and time consuming ground operations task. Developing a schedule requires extensive knowledge of the system and subsystems operations, operational constraints, and satellite design and configuration. This scheduling process requires highly trained experts anywhere from several hours to several weeks to accomplish. The process is done through brute force, that is examining cryptic mnemonic data off line to interpret the health and status of the satellite. Then schedules are formulated either as the result of practical operator experience or heuristics - that is rules of thumb. Orbital operations must become more productive in the future to reduce life cycle costs and decrease dependence on ground control. This reduction is required to increase autonomy and survivability of future systems. The design of future satellites require that the scheduling function be transferred from ground to on board systems.

Barry, John M.↗
NASA NTRS2014

Multi-Source Autonomous Response for Targeting and Monitoring of Volcanic Activity

The study of volcanoes is important for both purely scientific and human survival reasons. From a scientific standpoint, volcanic gas and ash emissions contribute significantly to the terrestrial atmosphere. Ash depositions and lava flows can also greatly affect local environments. From a human survival standpoint, many people live within the reach of active volcanoes, and therefore can be endangered by both atmospheric (ash, debris) toxicity and lava flow. There are many potential information sources that can be used to determine how to best monitor volcanic activity worldwide. These are of varying temporal frequency, spatial regard, method of access, and reliability. The problem is how to incorporate all of these inputs in a general framework to assign/task/reconfigure assets to monitor events in a timely fashion. In situ sensing can provide a valuable range of complementary information such as seismographic, discharge, acoustic, and other data. However, many volcanoes are not instrumented with in situ sensors, and those that have sensor networks are restricted to a relatively small numbers of point sensors. Consequently, ideal volcanic study synergistically combines space and in situ measurements. This work demonstrates an effort to integrate spaceborne sensing from MODIS (Terra and Aqua), ALI (EO-1), Worldview-2, and in situ sensing in an automated scheme to improve global volcano monitoring. Specifically, it is a "sensor web" concept in which a number of volcano monitoring systems are linked together to monitor volcanic activity more accurately, and this activity measurement automatically tasks space assets to acquire further satellite imagery of ongoing volcanic activity. A general framework was developed for evidence combination that accounts for multiple information sources in a scientist-directed fashion to weigh inputs and allocate observations based on the confidence of an events occurrence, rarity of the event at that location, and other scientists' inputs. The software framework uses multiple source languages and is a general framework for combining inputs and incrementally submitting observation requests/reconfigurations, accounting for prior requests. The autonomous aspect of operations is unique, especially in the context of the wide range of inputs that includes manually inputted electronic reports (such as the Air Force Weather Advisories), automated satellite-based detection methods (such as MODVOLC and GOESVOLC), and in situ sensor networks.

Davies, Ashley G.↗
NASA NTRS1988

A methodology for mapping forest latent heat flux densities using remote sensing

Surface temperatures and reflectances of an upper elevation Sierran mixed conifer forest were monitored using the Thematic Mapper Simulator sensor during the summer of 1985 in order to explore the possibility of using remote sensing to determine the distribution of solar energy on forested watersheds. The results show that the method is capable of quantifying the relative energy allocation relationships between the two cover types defined in the study. It is noted that the method also has the potential to map forest latent heat flux densities.

Pierce, Lars L.↗
NASA NTRS2013

Adaptive Sensing of Time Series with Application to Remote Exploration

We address the problem of adaptive informationoptimal data collection in time series. Here a remote sensor or explorer agent throttles its sampling rate in order to track anomalous events while obeying constraints on time and power. This problem is challenging because the agent has limited visibility -- all collected datapoints lie in the past, but its resource allocation decisions require predicting far into the future. Our solution is to continually fit a Gaussian process model to the latest data and optimize the sampling plan on line to maximize information gain. We compare the performance characteristics of stationary and nonstationary Gaussian process models. We also describe an application based on geologic analysis during planetary rover exploration. Here adaptive sampling can improve coverage of localized anomalies and potentially benefit mission science yield of long autonomous traverses.

artificial intelligence↗
NASA NTRS2020

Leveraging Space and Ground Assets in a Sensorweb for Scientific Monitoring: Early Results and Opportunities for the Future

Increased space and ground sensing is enabling dramaticnew measurements of a wide range of Earth Science andApplied Earth Science phenomena. New space sensors tomonitor volcanism, flooding, wildfires, weather, and manyother phenomena abound.New challenges exist to rapidly assimilate available dataand to optimize measurements (e.g. direct assets) to bestobserve these complex and dynamic spatiotemporalphenomena. Artificial Intelligence offers the potential toassist in data interpretation and resource allocation to bestallocate sensing assets. We describe some efforts to buildand experiment with such “sensorweb” systems as well asoffer some direction for the future sensorweb observationsystems.

Chien, Steve↗
NASA NTRSDate not supplied

Optimal Communication Topology Determination and Sensor Selection for Independent Airspace Surveillance

The paper presents an approach to sensors selection and network topology determination for independent airspace surveillance with maximum outcome and minimum cost using ground based distributed sensing, computing and communication network infrastructure. The selection criteria includes minimum estimation error, maximum airspace coverage, minimum communication time and power consumption while guaranteeing the system observability and providing in-time quality information to a monitoring observer. The developed algorithm uses multi-objective optimization strategy taking into account trade-offs between conflicting objectives and relaxations for in time implementation. It is implemented utilizing graph theoretic tools. The approach is validated in a desktop simulation environment using synthetic sensors data generated for a simulated multi-vehicle flight scenario in the selected regional airspace.

Distributed sensing↗
NASA NTRS2015

The Role of the NASA Global Hawk Link Module as an Information Nexus For Atmospheric Mapping Missions

The Link Module described in this paper was developed for the NASA Uninhabited Aerial System (UAS) Global Hawk Pacific Mission (GloPAC) Airborne Science Campaign; four flights of 30 hour duration, supporting the Aura Validation Experiment (AVE). It was used again during the Genesis and Rapid Intensification Processes (GRIP) experiment, a NASA Earth Science field experiment to better understand how tropical storms form and develop into major hurricanes. In these missions, the Link Module negotiated all communication over the high bandwidth Ku satellite link, archived all the science data from onboard experiments in a spatially enabled database, routed command and control of the instruments from the Global Hawk Operations Center, and re-transmitted select data sets directly to experimenters control and analysis systems. The availability of aggregated information from collections of sensors, and remote control capabilities, in real-time, is revolutionizing the way Airborne Science is being conducted. The Link Module NG now being flown in support of the NASA Earth Venture missions, the Hurricane and Severe Storm Sentinel (HS3) mission, and Airborne Tropical Tropopause Experiment (A TTREX) mission, has advanced data fusion technologies that are further advancing the Scientific productivity, flexibility and robustness of these systems. On-the-fly traffic shaping has been developed to allow the high definition video, used for critical flight control segments, to dynamically allocate variable bandwidth on demand. Historically, the Link Module evolved from the instrument and communication interface controller used by NASA's Pathfinder and Pathfinder plus solar powered UAS's in the late 1990' s. It later was expanded for use in the AIRDAS four channel scanner flown on the NASA Altus UAS, and then again to a module in the AMS twelve channel multispectral scanner flying on the NASA (Predator-b) Ikhana UAS. The current system is the answer to the challenges imposed by extremely long duration UASs, with on-board multi-instrument (>= 12) Sensor Webs.

Hurricanes↗
NASA NTRS1980

Asynchronous interactive control systems

A class of interactive control systems is derived by generalizing interactive manipulator control systems. The general structural properties of such systems are discussed and an appropriate general software implementation is proposed. This is based on the fact that tasks of interactive control systems can be represented as a network of a finite set of actions which have specific operational characteristics and specific resource requirements, and which are of limited duration. This has enabled the decomposition of the overall control algorithm into a set of subalgorithms, called subcontrollers, which can operate simultaneously and asynchronously. Coordinate transformations of sensor feedback data and actuator set-points have enabled the further simplification of the subcontrollers and have reduced their conflicting resource requirements. The modules of the decomposed control system are implemented as parallel processes with disjoint memory space communicating only by I/O. The synchronization mechanisms for dynamic resource allocation among subcontrollers and other synchronization mechanisms are also discussed in this paper. Such a software organization is suitable for the general form of multiprocessing using computer networks with distributed storage.

Vuskovic, M. I.↗
NASA NTRS2018

Playbook for UAS: UX of Goal-Oriented Planning & Execution

We are evaluating the tool Playbook, a mission planning and scheduling tool used for analog missions and research experiments at NASA. We are adapting Playbook to support an unmanned aerial vehicle (UAV) demonstration that will simulate a "search and recover" mission. To support this demonstration, we need to test this software and its usability with human subjects. Playbook will be used to plan, edit, and monitor simulated UAV swarms, and we are interested in evaluating these capabilities. Allocation of roles and responsibilities between human-automation systems is key to promoting productive cooperation between these two agents. When guiding swarms the user should not be concerned with moving waypoints, adjusting heading and altitude or any other small actions that traditional pilots control. Providing situational awareness through sensor data including radar, heat, live camera feed, and topographic information are key when managing multiple UAVs together. First responders need a good picture of disaster areas in order to make informed decisions. These sensors can initiate movements in the mission that indicate when the human should take control of single aircraft.

UAV swarms↗
NASA NTRS2011

Airborne Remote Observations of L-Band Radio Frequency Interference and Implications for Satellite Missions

Passive remote sensing of the Earth s surface and atmosphere from space has significant importance in operational and research environmental studies, in particular for the scientific understanding, monitoring and prediction of climate change and its impacts. Passive remote sensing requires the measurement of naturally occurring radiations, usually of very low power levels, which contain essential information on the physical process under investigation. As such, these sensed radio frequency bands are a unique natural resource enabling space borne passive sensing of the atmosphere and the Earth s surface that deserves adequate allocation to the Earth Exploration Satellite Service and absolute protection from interference. Unfortunately, radio frequency interference (RFI) is an increasing problem for Earth remote sensing, particularly for passive observations of natural emissions. Because these natural signals tend to be very weak, even low levels of interference received by a passive sensor may degrade the fidelity of scientific data. The characteristics of RFI (low-level interference and radar-pulse noise) are not well known because there has been no systematic surveillance, spectrum inventory or mapping of RFI. While conducting a flight experiment over central Tennessee in May 2010, RFI, a concern for any instrument operating in the passive L band frequency, was observed across 16 subbands between 1402-1427 MHz. Such a survey provides rare characterization data from which to further develop mitigation technologies as well as to identify bandwidths to avoid in future sensor formulation.

Laymon, Charles↗
NASA NTRS1975

A comparative interregional analysis of selected data from LANDSAT-1 and EREP for the inventory and monitoring of natural ecosystems

Comparative statistics were presented on the capability of LANDSAT-1 and three of the Skylab remote sensing systems (S-190A, S-190B, S-192) for the recognition and inventory of analogous natural vegetations and landscape features important in resource allocation and management. Two analogous regions presenting vegetational zonation from salt desert to alpine conditions above the timberline were observed, emphasizing the visual interpretation mode in the investigation. An hierarchical legend system was used as the basic classification of all land surface features. Comparative tests were run on image identifiability with the different sensor systems, and mapping and interpretation tests were made both in monocular and stereo interpretation with all systems except the S-192. Significant advantage was found in the use of stereo from space when image analysis is by visual or visual-machine-aided interactive systems. Some cost factors in mapping from space are identified. The various image types are compared and an operational system is postulated.

Poulton, C. E.↗