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All sourcesNASA NTRSDOE OSTI
NASA NTRS2017

Validation and Scaling of Soil Moisture in a Semi-Arid Environment: SMAP Validation Experiment 2015 (SMAPVEX15)

The NASA SMAP (Soil Moisture Active Passive) mission conducted the SMAP Validation Experiment 2015 (SMAPVEX15) in order to support the calibration and validation activities of SMAP soil moisture data products. The main goals of the experiment were to address issues regarding the spatial disaggregation methodologies for improvement of soil moisture products and validation of the in situ measurement upscaling techniques. To support these objectives high-resolution soil moisture maps were acquired with the airborne PALS (Passive Active L-band Sensor) instrument over an area in southeast Arizona that includes the Walnut Gulch Experimental Watershed (WGEW), and intensive ground sampling was carried out to augment the permanent in situ instrumentation. The objective of the paper was to establish the correspondence and relationship between the highly heterogeneous spatial distribution of soil moisture on the ground and the coarse resolution radiometer-based soil moisture retrievals of SMAP. The high-resolution mapping conducted with PALS provided the required connection between the in situ measurements and SMAP retrievals. The in situ measurements were used to validate the PALS soil moisture acquired at 1-km resolution. Based on the information from a dense network of rain gauges in the study area, the in situ soil moisture measurements did not capture all the precipitation events accurately. That is, the PALS and SMAP soil moisture estimates responded to precipitation events detected by rain gauges, which were in some cases not detected by the in situ soil moisture sensors. It was also concluded that the spatial distribution of the soil moisture resulted from the relatively small spatial extents of the typical convective storms in this region was not completely captured with the in situ stations. After removing those cases (approximately10 of the observations) the following metrics were obtained: RMSD (root mean square difference) of0.016m3m3 and correlation of 0.83. The PALS soil moisture was also compared to SMAP and in situ soil moisture at the 36-km scale, which is the SMAP grid size for the standard product. PALS and SMAP soil moistures were found to be very similar owing to the close match of the brightness temperature measurements and the use of a common soil moisture retrieval algorithm. Spatial heterogeneity, which was identified using the high-resolution PALS soil moisture and the intensive ground sampling, also contributed to differences between the soil moisture estimates. In general, discrepancies found between the L-band soil moisture estimates and the 5-cm depth in situ measurements require methodologies to mitigate the impact on their interpretations in soil moisture validation and algorithm development. Specifically, the metrics computed for the SMAP radiometer-based soil moisture product over WGEW will include errors resulting from rainfall, particularly during the monsoon season when the spatial distribution of soil moisture is especially heterogeneous.

SMAPVEX15↗
NASA NTRS2017

NeMO-Net The Neural Multi-Modal Observation Training Network for Global Coral Reef Assessment

In the past decade, coral reefs worldwide have experienced unprecedented stresses due to climate change, ocean acidification, and anthropomorphic pressures, instigating massive bleaching and die-off of these fragile and diverse ecosystems. Furthermore, remote sensing of these shallow marine habitats is hindered by ocean wave distortion, refraction and optical attenuation, leading invariably to data products that are often of low resolution and signal-to-noise (SNR) ratio. However, recent advances in UAV and Fluid Lensing technology have allowed us to capture multispectral 3D imagery of these systems at sub-cm scales from above the water surface, giving us an unprecedented view of their growth and decay. Exploiting the fine-scaled features of these datasets, machine learning methods such as MAP, PCA, and SVM can not only accurately classify the living cover and morphology of these reef systems (below 8 error), but are also able to map the spectral space between airborne and satellite imagery, augmenting and improving the classification accuracy of previously low-resolution datasets.We are currently implementing NeMO-Net, the first open-source deep convolutional neural network (CNN) and interactive active learning and training software to accurately assess the present and past dynamics of coral reef ecosystems through determination of percent living cover and morphology. NeMO-Net will be built upon the QGIS platform to ingest UAV, airborne and satellite datasets from various sources and sensor capabilities, and through data-fusion determine the coral reef ecosystem makeup globally at unprecedented spatial and temporal scales. To achieve this, we will exploit virtual data augmentation, the use of semi-supervised learning, and active learning through a tablet platform allowing for users to manually train uncertain or difficult to classify datasets. The project will make use of Pythons extensive libraries for machine learning, as well as extending integration to GPU and High-End Computing Capability (HECC) on the Pleiades supercomputing cluster, located at NASA Ames. The project is being supported by NASAs Earth Science Technology Office (ESTO) Advanced Information Systems Technology (AIST-16) Program.

Remote Sensin↗
NASA NTRS2017

NeMO-Net: The Neural Multi-Modal Observation and Training Network for Global Coral Reef Assessment

In the past decade, coral reefs worldwide have experienced unprecedented stresses due to climate change, ocean acidification, and anthropomorphic pressures, instigating massive bleaching and die-off of these fragile and diverse ecosystems. Furthermore, remote sensing of these shallow marine habitats is hindered by ocean wave distortion, refraction and optical attenuation, leading invariably to data products that are often of low resolution and signal-to-noise (SNR) ratio. However, recent advances in UAV and Fluid Lensing technology have allowed us to capture multispectral 3D imagery of these systems at sub-cm scales from above the water surface, giving us an unprecedented view of their growth and decay. Exploiting the fine-scaled features of these datasets, machine learning methods such as MAP, PCA, and SVM can not only accurately classify the living cover and morphology of these reef systems (below 8 percent error), but are also able to map the spectral space between airborne and satellite imagery, augmenting and improving the classification accuracy of previously low-resolution datasets. We are currently implementing NeMO-Net, the first open-source deep convolutional neural network (CNN) and interactive active learning and training software to accurately assess the present and past dynamics of coral reef ecosystems through determination of percent living cover and morphology. NeMO-Net will be built upon the QGIS platform to ingest UAV, airborne and satellite datasets from various sources and sensor capabilities, and through data-fusion determine the coral reef ecosystem makeup globally at unprecedented spatial and temporal scales. To achieve this, we will exploit virtual data augmentation, the use of semi-supervised learning, and active learning through a tablet platform allowing for users to manually train uncertain or difficult to classify datasets. The project will make use of Pythons extensive libraries for machine learning, as well as extending integration to GPU and High-End Computing Capability (HECC) on the Pleiades supercomputing cluster, located at NASA Ames. The project is being supported by NASAs Earth Science Technology Office (ESTO) Advanced Information Systems Technology (AIST-16) Program.

NeMO-Net↗
NASA NTRS1975

Auxiliary DCP data acquisition system

An airborne DCP Data Aquisition System has been designed to augment the ERTS satellite data recovery system. The DCP's are data collection platforms located at pertinent sites. With the appropriate sensors they are able to collect, digitally encode and transmit environmental parameters to the ERTS satellite. The satellite in turn relays these transmissions to a ground station for processing. The satellite is available for such relay duty a minimum of two times in a 24-hour period. The equipment is to obtain continuous DCP data during periods of unusual environmental activity--storms, floods, etc. Two circumstances contributed to the decision to design such a system; (1) Wallops Station utilizes surveillance aircraft in support of rocket launches and also in support of earth resources activities; (2) the area in which Wallops is located, the Delaware and Chesapeake Bay areas, are fertile areas for DCP usage. Therefore, by developing an airborne DCP receiving station and installing it on aircraft more continuous DCP data can be provided from sites in the surrounding areas at relatively low cost.

Snyder, R. V.↗
NASA NTRS1983

NASA/RAE collaboration on nonlinear control using the F-8C digital fly-by-wire aircraft

Design procedures are reviewed for variable integral control to optimize response (VICTOR) algorithms and results of preliminary flight tests are presented. The F-8C aircraft is operated in the remotely augmented vehicle (RAV) mode, with the control laws implemented as FORTRAN programs on a ground-based computer. Pilot commands and sensor information are telemetered to the ground, where the data are processed to form surface commands which are then telemetered back to the aircraft. The RAV mode represents a singlestring (simplex) system and is therefore vulnerable to a hardover since comparison monitoring is not possible. Hence, extensive error checking is conducted on both the ground and airborne computers to prevent the development of potentially hazardous situations. Experience with the RAV monitoring and validation procedures is described.

Butler, G. F.↗
NASA NTRS1991

The role of the remotely augmented vehicle (RAV) laboratory in flight research

This paper presents on overview of the unique capabilities and historical significance of the Remotely Augmented Vehicle (RAV) Laboratory at the NASA Dryden Flight Research Facility. The report reviews the role of the RAV Laboratory in enhancing flight test programs and efficient testing of new aircraft control laws. The history of the RAV Laboratory is discussed with a sample of its application using the X-29 aircraft. The RAV Laboratory allows for closed- or open-loop augmentation of the research aircraft while in flight using ground-based, high performance real-time computers. Telemetry systems transfer sensor and control data between the ground and the aircraft. The RAV capability provides for enhanced computational power, improved flight data quality, and alternate methods for the testing of control system concepts. The Laboratory is easily reconfigured to reflect changes within a flight program and can be adapted to new flight programs.

Cohen, Dorothea↗
NASA NTRS1998

Autonomous Attitude Sensor Calibration (ASCAL)

In this paper, an approach to increase the degree of autonomy of flight software is proposed. We describe an enhancement of the Attitude Determination and Control System by augmenting it with self-calibration capability. Conventional attitude estimation and control algorithms are combined with higher level decision making and machine learning algorithms in order to deal with the uncertainty and complexity of the problem.

Peterson, Chariya↗
NASA NTRS1999

ASCAL: Autonomous Attitude Sensor Calibration

Abstract In this paper, an approach to increase the degree of autonomy of flight software is proposed. We describe an enhancement of the Attitude Determination and Control System by augmenting it with self-calibration capability. Conventional attitude estimation and control algorithms are combined with higher level decision making and machine learning algorithms in order to deal with the uncertainty and complexity of the problem.

Peterson, Chariya↗
NASA NTRS1976

Preliminary design-lift/cruise fan research and technology airplane flight control system

This report presents the preliminary design of a stability augmentation system for a NASA V/STOL research and technology airplane. This stability augmentation system is postulated as the simplest system that meets handling qualities levels for research and technology missions flown by NASA test pilots. The airplane studied in this report is a T-39 fitted with tilting lift/cruise fan nacelles and a nose fan. The propulsion system features a shaft interconnecting the three variable pitch fans and three power plants. The mathematical modeling is based on pre-wind tunnel test estimated data. The selected stability augmentation system uses variable gains scheduled with airspeed. Failure analysis of the system illustrates the benign effect of engine failure. Airplane rate sensor failure must be solved with redundancy.

Gotlieb, P.↗
NASA NTRS1977

The preliminary design of a lift-cruise fan airplane flight control system

This paper presents the preliminary design of a stability augmentation system for a NASA V/STOL research and technology airplane. This stability augmentation system is postulated as the simplest system that meets handling-quality levels for research and technology missions flown by NASA test pilots. The airplane studied in this report is a modified T-39 fitted with tilting lift/cruise fan nacelles and a nose fan. The propulsion system features a shaft that interconnects three variable-pitch fans and three powerplants. The mathematical modeling is based on pre-wind tunnel test estimated data. The selected stability augmentation system uses variable gains scheduled with airspeed. Failure analysis of the system illustrates the benign effect of engine failure. Airplane rate sensor failure must be solved with redundancy.

Gotlieb, P.↗
NASA NTRS1991

Status of Sundstrand research

Wind shear detection status is presented in the form of view-graphs. The following subject areas are covered: second generation detection (Q-bias, gamma bias, temperature biases, maneuvering flight modulation, and altitude modulation); third generation wind shear detection (use wind shear computation to augment flight path and terrain alerts, modulation of alert thresholds based on wind/terrain data base, incorporate wind shear/terrain alert enhancements from predictive sensor data); and future research and development.

Bateman, Don↗
NASA NTRS1985

An analysis of Landsat Thematic Mapper P-Product internal geometry and conformity to earth surface geometry

Performance requirements regarding geometric accuracy have been defined in terms of end product goals, but until recently no precise details have been given concerning the conditions under which that accuracy is to be achieved. In order to achieve higher spatial and spectral resolutions, the Thematic Mapper (TM) sensor was designed to image in both forward and reverse mirror sweeps in two separate focal planes. Both hardware and software have been augmented and changed during the course of the Landsat TM developments to achieve improved geometric accuracy. An investigation has been conducted to determine if the TM meets the National Map Accuracy Standards for geometric accuracy at larger scales. It was found that TM imagery, in terms of geometry, has come close to, and in some cases exceeded, its stringent specifications.

Bryant, N. A.↗
NASA NTRS1994

Using generic tool kits to build intelligent systems

The Intelligent Systems and Robots Center at Sandia National Laboratories is developing technologies for the automation of processes associated with environmental remediation and information-driven manufacturing. These technologies, which focus on automated planning and programming and sensor-based and model-based control, are used to build intelligent systems which are able to generate plans of action, program the necessary devices, and use sensors to react to changes in the environment. By automating tasks through the use of programmable devices tied to computer models which are augmented by sensing, requirements for faster, safer, and cheaper systems are being satisfied. However, because of the need for rapid cost-effect prototyping and multi-laboratory teaming, it is also necessary to define a consistent approach to the construction of controllers for such systems. As a result, the Generic Intelligent System Controller (GISC) concept has been developed. This concept promotes the philosophy of producing generic tool kits which can be used and reused to build intelligent control systems.

Miller, David J.↗
NASA NTRS2020

Free-Space Optical Communication for CubeSats in Low Lunar Orbit (LLO)

The NASA ARTEMIS Program will include LunaNet, a highly extensible, open architecture, lunar communications and navigation network. A constellation of CubeSats in Low Lunar Orbit (LLO), 100 km, could form an optical communications and navigation network as part of LunaNet, with terminals on the lunar surface, including mobile ones such as with astronauts and rovers. The proposed CubeSat nodes should provide data relay and navigational aid services. The proposed effort herein is to develop a fine pointing capability for laser beam pointing to augment body pointing by CubeSats. Body pointing was used by Aerospace Corporation for the CubeSats in LEO in NASA’s Optical Communications and Sensors Demonstration (OCSD) program [1]. Previously, this fine pointing capability was computer simulated for the OCSD program [2,3]. With fine pointing, the spot size on the Earth was reduced by a factor of eight with a reduction in laser output power by a factor of sixty-four, thereby mitigating the thermal load challenge on the CubeSats. The same reductions in spot size and laser output power can be achieved for CubeSats in LLO. A new method is described for optical data transmissions from satellites, which uses laser arrays for laser beam pointing. It combines a lens system and an array of vertical-cavity, surface-emitting lasers and photodetectors, an VCSEL/Photodetector Array, (both mature technologies), in a novel way. This system is applied to CubeSats in low lunar orbit, (LLO), which use body pointing. Also, It may be able to replace current architectures which use dynamical systems, (i.e., moving parts) to point the laser, and which may also use vibration isolation platforms. The computer simulations used the optics code, OpticStudio, from Zemax, LLC, which has the capabilities to model the laser source and diffraction effects from wave optics. These capabilities make it possible to model laser beam propagation over long space communication distances.

Goorjian, P. M.↗
NASA NTRS1976

B-52 stability augmentation system reliability

The B-52 SAS (Stability Augmentation System) was developed and retrofitted to nearly 300 aircraft. It actively controls B-52 structural bending, provides improved yaw and pitch damping through sensors and electronic control channels, and puts complete reliance on hydraulic control power for rudder and elevators. The system has experienced over 300,000 flight hours and has exhibited service reliability comparable to the results of the reliability test program. Development experience points out numerous lessons with potential application in the mechanization and development of advanced technology control systems of high reliability.

Bowling, T. C.↗
NASA NTRS1989

Vibration suppression for precision segmented reflector backup structure

An ongoing effort at the JPL on vibration suppression for the Precision Segmented Reflector backup structure is centered on the vibration damping augmentation through a system consisting of active and passive damping members. An active member is a structural member with built-in piezoelectric actuator and sensors. An efficient method was developed for optimal placement of active and passive damping members in the truss-type backup structure. A simple synergistic model between the active and passive damping was proposed based on a weighted energy dissipation criterion. A baseline passive member design with constrained viscoelastic material treatment was used as the source of passive damping.

Chen, G.-S.↗
NASA NTRS1992

On-board attitude determination for the Explorer Platform satellite

This paper describes the attitude determination algorithm for the Explorer Platform satellite. The algorithm, which is baselined on the Landsat code, is a six-element linear quadratic state estimation processor, in the form of a Kalman filter augmented by an adaptive filter process. Improvements to the original Landsat algorithm were required to meet mission pointing requirements. These consisted of a more efficient sensor processing algorithm and the addition of an adaptive filter which acts as a check on the Kalman filter during satellite slew maneuvers. A 1750A processor will be flown on board the satellite for the first time as a coprocessor (COP) in addition to the NASA Standard Spacecraft Computer. The attitude determination algorithm, which will be resident in the COP's memory, will make full use of its improved processing capabilities to meet mission requirements. Additional benefits were gained by writing the attitude determination code in Ada.

Jayaraman, C.↗
NASA NTRSDate not supplied

The Gandalf Staff: A Mobile Tool for Lunar Exploration (2nd year of development)

The Gandalf Staff is a mobile tool designed to be a flexible device supporting crewed and uncrewed operations on the lunar surface. The core of the device is a 24v battery with communications and data storage systems. Initial optional components supporting crewed Extra-Vehicular Activity (EVA) include a LiDAR and 360˚ camera. These provide 3D mapping of the traverse for documentation, and to aid future planning. The mapping also creates outreach opportunities for the public to “stand beside” the astronaut in Virtual Reality (VR). The staff provides external lighting for field site illumination in the south polar region low sun angle environment. Navigation instruments for crew position determination with Lunar Search and Rescue (LunaSAR) are also included. The staff itself can be used as a walking aid or as a splint for Incapacitated Crew Rescue (ICR). As a stand-alone device, the staff operates as a long duration untended science platform collecting environmental data and sending it to a lunar base station. The stand-alone mode requires connection to an auxiliary power source (e.g. solar array) and energy storage system (e.g. battery), so it could become an electrical recharging station. To make rapid progress in the 1st year, and also to demonstrate innovative project management techniques, NASA guided a private industry partner, T STAR, in leading Capstone Engineering student teams at Texas A&M University (TAMU) for proof-of-concept development and testing. These teams developed the power system and demonstrated successful integration of LiDAR, WiFi communications, and external lighting subsystems. Another industry team at Jacobs Technology prototyped a tripod to hold the staff upright. For the 2nd year (FY’22), NASA will again collaborate with partners to prototype enhanced power and lighting concepts. Year 2 will also add new capability for LunaSAR and geophysical science instrumentation using a heat probe. The heat probe is based upon Apollo heritage but modified to measure subsurface volatile ice regimes at the Artemis landing site. Components of the Gandalf Staff can be developed, tested, and deployed independently, or on the integrated staff, rovers, or utility trailers. The project supports crew safety, lunar sample curation, mission science, and public outreach goals of NASA. PLAIN TEST SUMMARY: Gandalf Staff is a 24v battery powered mobile tool for the lunar surface supporting crewed geologic field site exploration, or as a stand-alone science platform. As a tool assisting astronauts conducting field geology, the Gandalf Staff provides external lighting to illuminate shadowed regions on the surface. It also documents the process of collecting rocks and dust samples using a LiDAR (laser range instrument) and cameras. The staff provides a beacon for emergency location of astronauts and augments communications when the astronauts are blocked by large boulders. As a standalone science platform, the Gandalf Staff provides a power system for instruments and sensors to measure the lunar environment over long periods of time. The staff gathers data and sends the results to a lunar base station for analysis.

External Lighting↗