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At least 343 records · Page 19

Virtual Machine Language Controls Remote Devices

Kennedy Space Center worked with Blue Sun Enterprises, based in Boulder, Colorado, to enhance the company's virtual machine language (VML) to control the instruments on the Regolith and Environment Science and Oxygen and Lunar Volatiles Extraction mission. Now the NASA-improved VML is available for crewed and uncrewed spacecraft, and has potential applications on remote systems such as weather balloons, unmanned aerial vehicles, and submarines.

Source record↗

An Application of UAV Attitude Estimation Using a Low-Cost Inertial Navigation System

Unmanned Aerial Vehicles (UAV) are playing an increasing role in aviation. Various methods exist for the computation of UAV attitude based on low cost microelectromechanical systems (MEMS) and Global Positioning System (GPS) receivers. There has been a recent increase in UAV autonomy as sensors are becoming more compact and onboard processing power has increased significantly. Correct UAV attitude estimation will play a critical role in navigation and separation assurance as UAVs share airspace with civil air traffic. This paper describes attitude estimation derived by post-processing data from a small low cost Inertial Navigation System (INS) recorded during the flight of a subscale commercial off the shelf (COTS) UAV. Two discrete time attitude estimation schemes are presented here in detail. The first is an adaptation of the Kalman Filter to accommodate nonlinear systems, the Extended Kalman Filter (EKF). The EKF returns quaternion estimates of the UAV attitude based on MEMS gyro, magnetometer, accelerometer, and pitot tube inputs. The second scheme is the complementary filter which is a simpler algorithm that splits the sensor frequency spectrum based on noise characteristics. The necessity to correct both filters for gravity measurement errors during turning maneuvers is demonstrated. It is shown that the proposed algorithms may be used to estimate UAV attitude. The effects of vibration on sensor measurements are discussed. Heuristic tuning comments pertaining to sensor filtering and gain selection to achieve acceptable performance during flight are given. Comparisons of attitude estimation performance are made between the EKF and the complementary filter.

Eure, Kenneth W.↗

Thermal Modeling and Analysis of the Hurricane Imaging Radiometer (HIRad)

The Hurricane Imaging Radiometer (HIRad) is a payload carried by an unmanned aerial vehicle (UAV) at altitudes up to 60,000 ft with the purpose of measuring ocean surface wind speeds and near ocean surface rain rates in hurricanes. The payload includes several components that must maintain steady temperatures throughout the flight. Minimizing the temperature drift of these components allows for accurate data collection and conclusions to be drawn concerning the behavior of hurricanes. HIRad has flown on several different UAVs over the past two years during the fall hurricane season. Based on the data from the 2011 flight, a Thermal Desktop model was created to simulate the payload and reproduce the temperatures. Using this model, recommendations were made to reduce the temperature drift through the use of heaters controlled by resistance temperature detector (RTD) sensors. The suggestions made were implemented for the 2012 hurricane season and further data was collected. The implementation of the heaters reduced the temperature drift for a portion of the flight, but after a period of time, the temperatures rose. With this new flight data, the thermal model was updated and correlated. Detailed analysis was conducted to determine a more effective way to reduce the temperature drift. The final recommendations made were to adjust the set temperatures of the heaters for 2013 flights and implement hardware changes for flights beyond 2013.

Mauro, Stephanie↗

Modeling and Analysis of the Hurricane Imaging Radiometer (HIRAD)

The Hurricane Imaging Radiometer (HIRad) is a payload carried by an unmanned aerial vehicle (UAV) at altitudes up to 60,000 ft with the purpose of measuring ocean surface wind speeds and near ocean surface rain rates in hurricanes. The payload includes several components that must maintain steady temperatures throughout the flight. Minimizing the temperature drift of these components allows for accurate data collection and conclusions to be drawn concerning the behavior of hurricanes. HIRad has flown on several different UAVs over the past two years during the fall hurricane season. Based on the data from the 2011 flight, a Thermal Desktop model was created to simulate the payload and reproduce the temperatures. Using this model, recommendations were made to reduce the temperature drift through the use of heaters controlled by resistance temperature detector (RTD) sensors. The suggestions made were implemented for the 2012 hurricane season and further data was collected. The implementation of the heaters reduced the temperature drift for a portion of the flight, but after a period of time, the temperatures rose. With this new flight data, the thermal model was updated and correlated. Detailed analysis was conducted to determine a more effective way to reduce the temperature drift. The final recommendations made were to adjust the set temperatures of the heaters for 2013 flights and implement hardware changes for flights beyond 2013.

Mauro, Stephanie↗

Requirements Flowdown for Prognostics and Health Management

Prognostics and Health Management (PHM) principles have considerable promise to change the game of lifecycle cost of engineering systems at high safety levels by providing a reliable estimate of future system states. This estimate is a key for planning and decision making in an operational setting. While technology solutions have made considerable advances, the tie-in into the systems engineering process is lagging behind, which delays fielding of PHM-enabled systems. The derivation of specifications from high level requirements for algorithm performance to ensure quality predictions is not well developed. From an engineering perspective some key parameters driving the requirements for prognostics performance include: (1) maximum allowable Probability of Failure (PoF) of the prognostic system to bound the risk of losing an asset, (2) tolerable limits on proactive maintenance to minimize missed opportunity of asset usage, (3) lead time to specify the amount of advanced warning needed for actionable decisions, and (4) required confidence to specify when prognosis is sufficiently good to be used. This paper takes a systems engineering view towards the requirements specification process and presents a method for the flowdown process. A case study based on an electric Unmanned Aerial Vehicle (e-UAV) scenario demonstrates how top level requirements for performance, cost, and safety flow down to the health management level and specify quantitative requirements for prognostic algorithm performance.

video acuity↗

NASA Unmanned Aircraft (UA) Control and Non-Payload Communication (CNPC) System Waveform Trade Studies

Unmanned Aircraft Systems (UAS) represent a new capability that will provide a variety of services in the government (public) and commercial (civil) aviation sectors. The growth of this potential industry has not yet been realized due to the lack of a common understanding of what is required to safely operate UAS in the National Airspace System (NAS). To address this deficiency, NASA has established a project called UAS Integration in the NAS (UAS in the NAS), under the Integrated Systems Research Program (ISRP) of the Aeronautics Research Mission Directorate (ARMD). This project provides an opportunity to transition concepts, technology, algorithms, and knowledge to the Federal Aviation Administration (FAA) and other stakeholders to help them define the requirements, regulations, and issues for routine UAS access to the NAS. The safe, routine, and efficient integration of UAS into the NAS requires new radio frequency (RF) spectrum allocations and a new data communications system which is both secure and scalable with increasing UAS traffic without adversely impacting the Air Traffic Control (ATC) communication system. These data communications, referred to as Control and Non-Payload Communications (CNPC), whose purpose is to exchange information between the unmanned aircraft and the ground control station to ensure safe, reliable, and effective unmanned aircraft flight operation. A Communications Subproject within the UAS in the NAS Project has been established to address issues related to CNPC development, certification and fielding. The focus of the Communications Subproject is on validating and allocating new RF spectrum and data link communications to enable civil UAS integration into the NAS. The goal is to validate secure, robust data links within the allocated frequency spectrum for UAS. A vision, architectural concepts, and seed requirements for the future commercial UAS CNPC system have been developed by RTCA Special Committee 203 (SC-203) in the process of determining formal recommendations to the FAA in its role provided for under the Federal Advisory Committee Act. NASA intends to conduct its research and development in keeping with this vision and associated architectural concepts. The prototype communication systems developed and tested by NASA will be used to validate and update the initial SC-203 requirements in order to provide a foundation for SC-203's Minimum Aviation System Performance Standards (MASPS).

Aircraft Communications↗

Communications Technology Assessment for the Unmanned Aircraft System (UAS) Control and Non-Payload Communications (CNPC) Link

The National Aeronautics and Space Administration (NASA) Glenn Research Center (GRC) is performing communications systems research for the Unmanned Aircraft System (UAS) in the National Airspace System (NAS) Project. One of the goals of the communications element is to select and test a communications technology for the UAS Control and Non-Payload Communications (CNPC) link. The GRC UAS Modeling and Simulation (M/S) Sub Team will evaluate the performance of several potential technologies for the CNPC link through detailed software simulations. In parallel, an industry partner will implement a technology in hardware to be used for flight testing. The task necessitated a technical assessment of existing Radio Frequency (RF) communications technologies to identify the best candidate systems for use as the UAS CNPC link. The assessment provides a basis for selecting the technologies for the M/S effort and the hardware radio design. The process developed for the technical assessments for the Future Communications Study1 (FCS) was used as an initial starting point for this assessment. The FCS is a joint Federal Aviation Administration (FAA) and Eurocontrol study on technologies for use as a future aeronautical communications link. The FCS technology assessment process methodology can be applied to the UAS CNPC link; however the findings of the FCS are not directly applicable because of different requirements between a CNPC link and a general aeronautical data link. Additional technologies were added to the potential technologies list from the State of the Art Unmanned Aircraft System Communication Assessment developed by NASA GRC2. This document investigates the state of the art of communications as related to UAS. A portion of the document examines potential communications systems for a UAS communication architecture. Like the FCS, the state of the art assessment surveyed existing communications technologies. It did not, however, perform a detailed assessment of the technology necessary to recommend a technology for the UAS CNPC link. The technical assessment process, as shown in Figure 1, consists of the following steps. First, candidate RF communications technologies are identified. An initial review of each of these technologies is then performed to determine if the technology appears to be a good candidate and requires further review. Any technology that can be shown to be inadequate at that point is removed from consideration to allow for more detailed analysis of the remaining technologies. Criteria for the detailed assessments are defined and a scoring methodology is devised. This is followed by the detailed review and scoring of each technology. The least favorable technologies are removed during the process until only the few best candidates remain.

Aircraft Command and Control↗

SILHIL Replication of Electric Aircraft Powertrain Dynamics and Inner-Loop Control for V&V of System Health Management Routines

Software-in-the-loop and Hardware-in-the-loop testing of failure prognostics and decision making tools for aircraft systems will facilitate more comprehensive and cost-effective testing than what is practical to conduct with flight tests. A framework is described for the offline recreation of dynamic loads on simulated or physical aircraft powertrain components based on a real-time simulation of airframe dynamics running on a flight simulator, an inner-loop flight control policy executed by either an autopilot routine or a human pilot, and a supervisory fault management control policy. The creation of an offline framework for verifying and validating supervisory failure prognostics and decision making routines is described for the example of battery charge depletion failure scenarios onboard a prototype electric unmanned aerial vehicle.

Verification and Validation↗

A Physics-Based Modeling Framework for Prognostic Studies

Prognostics and Health Management (PHM) methodologies have emerged as one of the key enablers for achieving efficient system level maintenance as part of a busy operations schedule, and lowering overall life cycle costs. PHM is also emerging as a high-priority issue in critical applications, where the focus is on conducting fundamental research in the field of integrated systems health management. The term diagnostics relates to the ability to detect and isolate faults or failures in a system. Prognostics on the other hand is the process of predicting health condition and remaining useful life based on current state, previous conditions and future operating conditions. PHM methods combine sensing, data collection, interpretation of environmental, operational, and performance related parameters to indicate systems health under its actual application conditions. The development of prognostics methodologies for the electronics field has become more important as more electrical systems are being used to replace traditional systems in several applications in the aeronautics, maritime, and automotive fields. The development of prognostics methods for electronics presents several challenges due to the great variety of components used in a system, a continuous development of new electronics technologies, and a general lack of understanding of how electronics fail. Similarly with electric unmanned aerial vehicles, electrichybrid cars, and commercial passenger aircraft, we are witnessing a drastic increase in the usage of batteries to power vehicles. However, for battery-powered vehicles to operate at maximum efficiency and reliability, it becomes crucial to both monitor battery health and performance and to predict end of discharge (EOD) and end of useful life (EOL) events. We develop an electrochemistry-based model of Li-ion batteries that capture the significant electrochemical processes, are computationally efficient, capture the effects of aging, and are of suitable accuracy for reliable EOD prediction in a variety of usage profiles.

Li-ion Batteries↗

Advances in Parallelization for Large Scale Oct-Tree Mesh Generation

Despite great advancements in the parallelization of numerical simulation codes over the last 20 years, it is still common to perform grid generation in serial. Generating large scale grids in serial often requires using special "grid generation" compute machines that can have more than ten times the memory of average machines. While some parallel mesh generation techniques have been proposed, generating very large meshes for LES or aeroacoustic simulations is still a challenging problem. An automated method for the parallel generation of very large scale off-body hierarchical meshes is presented here. This work enables large scale parallel generation of off-body meshes by using a novel combination of parallel grid generation techniques and a hybrid "top down" and "bottom up" oct-tree method. Meshes are generated using hardware commonly found in parallel compute clusters. The capability to generate very large meshes is demonstrated by the generation of off-body meshes surrounding complex aerospace geometries. Results are shown including a one billion cell mesh generated around a Predator Unmanned Aerial Vehicle geometry, which was generated on 64 processors in under 45 minutes.

O'Connell, Matthew↗

Low Noise Amplifiers and Receivers for Remote Sensing

The study of atmospheric dynamics and climatology depend on accurate and frequent measurements of temperature and humidity profiles of the atmosphere. These measurements furthermore enable highly accurate measurements of ocean topography by providing total column water vapour data for radar path delay correction. The atmospheric temperature profile is characterized at the oxygen molecule absorption frequencies (60 and 118 GHz) and the humidity profile at the water molecule absorption frequencies (23 and 183 GHz). Total column measurements can be achieved by comparing measured radiometric temperatures at atmospheric window channels, such as 90, 130, and 166 GHz. The standard receiver technology for these frequencies was diode mixers with MMIC LNAs being applied at the lower frequencies. The sensitivity of millimeter wave receivers improved significantly with the introduction of the low noise 35 nm gate length InP MMIC amplifiers. We currently achieve 3 dB noise figure at 180 GHz and 2 dB noise figure at 90 GHz with our MMIC low noise amplifiers (LNAs) in room temperature. These amplifiers and the receivers we have built using them made it possible to conduct highly accurate airborne measurements campaigns from the Global Hawk unmanned aerial vehicle, develop millimeter wave internally calibrated radiometers for altimeter radar path delay correction, and build prototypes of large arrays of millimeter receivers for a geostationary interferometric sounder. We use the developed millimeter wave receivers to measure temperature and humidity profiles in the atmosphere and in hurricanes as well as to characterize the path delay error in ocean topography alitmetery.

low noise temperature↗

Low Noise Amplifiers and Receivers for Remote Sensing

The study of atmospheric dynamics and climatology depend on accurate and frequent measurements of temperature and humidity profiles of the atmosphere. These measurements furthermore enable highly accurate measurements of ocean topography by providing total column water vapour data for radar path delay correction. The atmospheric temperature profile is characterised at the oxygen molecule absorption frequencies (60 and 118 GHz) and the humidity profile at the water molecule absorption frequencies (23 and 183 GHz). Total column measurements can be achieved by comparing measured radiometric temperatures at atmospheric window channels, such as 90, 130 and 166 GHz. The standard receiver technology for these frequencies was diode mixers with MMIC LNAs being applied at the lower frequencies. The sensitivity of millimetre wave receivers improved significantly with the introduction of the low noise 35 nm gate length InP MMIC amplifiers. We currently achieve 3 dB noise figure at 180 GHz and 2 dB noise figure at 90 GHz with our MMIC low noise amplifiers (LNAs) in room temperature. These amplifiers and the receivers we have built using them made it possible to conduct highly accurate airborne measurement campaigns from the Global Hawk unmanned aerial vehicle, develop millimeter wave internally calibrated radiometers for altimeter radar path delay correction, and build prototypes of large arrays of millimeter receivers for a geostationary interferometric sounder. We use the developed millimeter wave receivers to measure temperature and humidity profiles in the atmosphere and in hurricanes as well as to characterize the path delay error in ocean topography altimetry.

low noise amplifier↗

EM Modeling of Far-Field Radiation Patterns for Antennas on the GMA-TT UAV

To optimize communication with the Generic Modular Aircraft T-Tail (GMA-TT) unmanned aerial vehicle (UAV), electromagnetic (EM) simulations have been performed to predict the performance of two antenna types on the aircraft. Simulated far-field radiation patterns tell the amount of power radiated by the antennas and the aircraft together, taking into account blockage by the aircraft as well as radiation by conducting and dielectric portions of the aircraft. With a knowledge of the polarization and distance of the two communicating antennas, e.g. one on the UAV and one on the ground, and the transmitted signal strength, a calculation may be performed to find the strength of the signal travelling from one antenna to the other and to check that the transmitted signal meets the receiver system requirements for the designated range. In order to do this, the antenna frequency and polarization must be known for each antenna, in addition to its design and location. The permittivity, permeability, and geometry of the UAV components must also be known. The full-wave method of moments solution produces the appropriate dBi radiation pattern in which the received signal strength is calculated relative to that of an isotropic radiator.

Mackenzie, Anne I.↗

Pioneering a Biobased UAS

With the exponential growth of interest in unmanned aerial vehicles (UAVs) and their vast array of applications in both space exploration and terrestrial uses such as the delivery of medicine and monitoring the environment, the 2014 Stanford-Brown-Spelman iGEM team is pioneering the development of a fully biological UAV for scientific and humanitarian missions. The prospect of a biologically-produced UAV presents numerous advantages over the current manufacturing paradigm. First, a foundational architecture built by cells allows for construction or repair in locations where it would be difficult to bring traditional tools of production. Second, a major limitation of current research with UAVs is the size and high power consumption of analytical instruments, which require bulky electrical components and large fuselages to support their weight. By moving these functions into cells with biosensing capabilities - for example, a series of cells engineered to report GFP, green fluorescent protein, when conditions exceed a certain threshold concentration of a compound of interest, enabling their detection post-flight - these problems of scale can be avoided. To this end, we are working to engineer cells to synthesize cellulose acetate as a novel bioplastic, characterize biological methods of waterproofing the material, and program this material's systemic biodegradation. In addition, we aim to use an "amberless" system to prevent horizontal gene transfer from live cells on the material to microorganisms in the flight environment. So far, we have: successfully transformed Gluconacetobacter hansenii, a cellulose-producing bacterium, with a series of promoters to test transformation efficiency before adding the acetylation genes; isolated protein bands present in the wasp nest material; transformed the cellulose-degrading genes into Escherichia coli; and we have confirmed that the amberless construct prevents protein expression in wild-type cells. In addition, as part of our human outreach project, we have been in touch with leaders in the fields of UAVs, synthetic biology, and earth sciences, and it is clear that biodegradable UAVs could have a significant impact on the industry.

Escherichia↗

Small UAV Automatic Ground Collision Avoidance System Design Considerations and Flight Test Results

The National Aeronautics and Space Administration (NASA) Armstrong Flight Research Center Small Unmanned Aerial Vehicle (SUAV) Automatic Ground Collision Avoidance System (Auto GCAS) project demonstrated several important collision avoidance technologies. First, the SUAV Auto GCAS design included capabilities to take advantage of terrain avoidance maneuvers flying turns to either side as well as straight over terrain. Second, the design also included innovative digital elevation model (DEM) scanning methods. The combination of multi-trajectory options and new scanning methods demonstrated the ability to reduce the nuisance potential of the SUAV while maintaining robust terrain avoidance. Third, the Auto GCAS algorithms were hosted on the processor inside a smartphone, providing a lightweight hardware configuration for use in either the ground control station or on board the test aircraft. Finally, compression of DEM data for the entire Earth and successful hosting of that data on the smartphone was demonstrated. The SUAV Auto GCAS project demonstrated that together these methods and technologies have the potential to dramatically reduce the number of controlled flight into terrain mishaps across a wide range of aviation platforms with similar capabilities including UAVs, general aviation aircraft, helicopters, and model aircraft.

Sorokowski, Paul↗

Towards a Biosynthetic UAV

We are currently working on a series of projects towards the construction of a fully biological unmanned aerial vehicle (UAV) for use in scientific and humanitarian missions. The prospect of a biologically-produced UAV presents numerous advantages over the current manufacturing paradigm. First, a foundational architecture built by cells allows for construction or repair in locations where it would be difficult to bring traditional tools of production. Second, a major limitation of current research with UAVs is the size and high power consumption of analytical instruments, which require bulky electrical components and large fuselages to support their weight. By moving these functions into cells with biosensing capabilities - for example, a series of cells engineered to report GFP, green fluorescent protein, when conditions exceed a certain threshold concentration of a compound of interest, enabling their detection post-flight - these problems of scale can be avoided. To this end, we are working to engineer cells to synthesize cellulose acetate as a novel bioplastic, characterize biological methods of waterproofing the material, and program this material's systemic biodegradation. In addition, we aim to use an "amberless" system to prevent horizontal gene transfer from live cells on the material to microorganisms in the flight environment.

Biological↗

Automated Segmentation and Classification of Coral using Fluid Lensing from Unmanned Airborne Platforms

In recent years, there has been a growing interest among biologists in monitoring the short and long term health of the world's coral reefs. The environmental impact of climate change poses a growing threat to these biologically diverse and fragile ecosystems, prompting scientists to use remote sensing platforms and computer vision algorithms to analyze shallow marine systems. In this study, we present a novel method for performing coral segmentation and classification from aerial data collected from small unmanned aerial vehicles (sUAV). Our method uses Fluid Lensing algorithms to remove and exploit strong optical distortions created along the air-fluid boundary to produce cm-scale resolution imagery of the ocean floor at depths up to 5 meters. A 3D model of the reef is reconstructed using structure from motion (SFM) algorithms, and the associated depth information is combined with multidimensional maximum a posteriori (MAP) estimation to separate organic from inorganic material and classify coral morphologies in the Fluid-Lensed transects. In this study, MAP estimation is performed using a set of manually classified 100 x 100 pixel training images to determine the most probable coral classification within an interrogated region of interest. Aerial footage of a coral reef was captured off the coast of American Samoa and used to test our proposed method. 90 x 20 meter transects of the Samoan coastline undergo automated classification and are manually segmented by a marine biologist for comparison, leading to success rates as high as 85%. This method has broad applications for coastal remote sensing, and will provide marine biologists access to large swaths of high resolution, segmented coral imagery.

algorithms segments classifications↗

Precision Time Protocol-Based Trilateration for Planetary Navigation

Progeny Systems Corporation has developed a high-fidelity, field-scalable, non-Global Positioning System (GPS) navigation system that offers precision localization over communications channels. The system is bidirectional, providing position information to both base and mobile units. It is the first-ever wireless use of the Institute of Electrical and Electronics Engineers (IEEE) Precision Time Protocol (PTP) in a bidirectional trilateration navigation system. The innovation provides a precise and reliable navigation capability to support traverse-path planning systems and other mapping applications, and it establishes a core infrastructure for long-term lunar and planetary occupation. Mature technologies are integrated to provide navigation capability and to support data and voice communications on the same network. On Earth, the innovation is particularly well suited for use in unmanned aerial vehicles (UAVs), as it offers a non-GPS precision navigation and location service for use in GPS-denied environments. Its bidirectional capability provides real-time location data to the UAV operator and to the UAV. This approach optimizes assisted GPS techniques and can be used to determine the presence of GPS degradation, spoofing, or jamming.

Murdock, Ron↗