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NASA NTRS2016

Exploring Cognition Using Software Defined Radios for NASA Missions

NASA missions typically operate using a communication infrastructure that requires significant schedule planning with limited flexibility when the needs of the mission change. Parameters such as modulation, coding scheme, frequency, and data rate are fixed for the life of the mission. This is due to antiquated hardware and software for both the space and ground assets and a very complex set of mission profiles. Automated techniques in place by commercial telecommunication companies are being explored by NASA to determine their usability by NASA to reduce cost and increase science return. Adding cognition the ability to learn from past decisions and adjust behavior is also being investigated. Software Defined Radios are an ideal way to implement cognitive concepts. Cognition can be considered in many different aspects of the communication system. Radio functions, such as frequency, modulation, data rate, coding and filters can be adjusted based on measurements of signal degradation. Data delivery mechanisms and route changes based on past successes and failures can be made to more efficiently deliver the data to the end user. Automated antenna pointing can be added to improve gain, coverage, or adjust the target. Scheduling improvements and automation to reduce the dependence on humans provide more flexible capabilities. The Cognitive Communications project, funded by the Space Communication and Navigation Program, is exploring these concepts and using the SCaN Testbed on board the International Space Station to implement them as they evolve. The SCaN Testbed contains three Software Defined Radios and a flight computer. These four computing platforms, along with a tracking antenna system and the supporting ground infrastructure, will be used to implement various concepts in a system similar to those used by missions. Multiple universities and SBIR companies are supporting this investigation. This paper will describe the cognitive system ideas under consideration and the plan for implementing them on platforms, including the SCaN Testbed. Discussions in the paper will include how these concepts might be used to reduce cost and improve the science return for NASA missions.

transmitters receivers↗

NASA NTRS2014

Simulation Technology at NASA

NASA Ames Research Center is home to several high-fidelity research flight and air-traffic control simulation facilities which, together with an experienced workforce, produce high-quality research data and findings that have proven to be applicable in the real world. These assets include the Vertical Motion Simulator (VMS), Crew Vehicle Systems Research Facility (CVSRF), Future Flight Central (FFC) air traffic control tower simulator, and several air-traffic control (ATC) simulators. The VMS combines a high-fidelity simulation capability with an adaptable simulation environment, enabling customization for numerous human-in-the-loop research applications. The distinctive feature of the VMS is its unparalleled large amplitude, high-fidelity motion capability. In over 30 years of continuous operation, the VMS has contributed significantly to the body of knowledge in a range of disciplines directly benefiting several aerospace programs and flight safety, including the design and development of flight control systems for the Joint Strike Fighter, Space Shuttle Orbiter, and rotorcraft. It continues to be used for researching new vehicle configurations, vehicle control and safety, transfer-of-training, etc., by NASA, other government agencies, and Industry.The CVSRF includes two motion-based flight simulators: a Boeing 747-400 full flight simulator and the reconfigurable Advanced Concepts Flight Simulator (ACFS). These simulators are primarily used to research air-traffic management concepts and procedures, advanced navigation and avionics concepts, and cockpit human factors. FFC is a full-sized control tower simulator with a 360-degree external field-of-view display system and reconfigurable system architecture. FFC and the ATC simulators are used for testing air-traffic management automation and decision support tools and demonstrate their feasibility in a realistic environment prior to technology transfer for implementation in the National Airspace System (NAS).To support integrated simulations and flight-tests for NASA's Unmanned Aircraft Systems (UAS) in the National Airspace System (NAS) Project, NASA developed a distributed test environment incorporating Live, Virtual, Constructive, (LVC) concepts. Development of the software enabling the LVC is conducted primarily at the Distributed Simulation Research Lab (DSRL) at NASA Ames. The LVC components provide the core infrastructure supporting simulation of UAS operations by integrating live and virtual aircraft in a realistic air traffic environment. This provides the ability to conduct tests more efficiently by promoting the use of existing distributed assets. The LVC infrastructure was used in several human-in-the-loop simulations to evaluate acceptance of Detect and Avoid (DAA) advisories used by UAS pilots to maintain well clear of other virtual traffic and to negotiate maneuvers with air traffic control. It is currently being used to support testing of self-separation algorithms between unmanned and manned aircraft in live flight. Further simulations with more comprehensive air traffic scenarios mixing live and virtual aircraft is planned.In the current fiscal environment, maintaining and upgrading these high-fidelity simulation assets and retaining the skilled workforce necessary to meet future research needs is the primary non-technical challenge.

CVSRF↗

NASA NTRS2022

Air Traffic Management TestBed: Weather Visualization using Map Tiles

Running realistic simulations and developing algorithms for decision support tools usually require weather data access. This document describes the weather data service capability implemented in the Air Traffic Management (ATM) TestBed. The capability provides ways for querying weather data from the weather products provided by the National Aeronautics and Space Administration’s (NASA) Sherlock ATM Data Warehouse. Depending on use cases, weather data can be queried using a Java application programming interface, web data access, and map tile image access. Map tile images are generated using triangular meshes obtained using the Matching Squares contour algorithm. An analysis determines a grid size that will produce both high image quality and fast image rendering. In addition, the visualization of weather data as map tiles on a TestBed visualization tool called Traffic Viewer is presented.

Chok Fung Lai↗

NASA NTRS2023

NASA’s Digital Information Platform to Accelerate the Transformation of the National Airspace System

In order to accelerate the digital transformation of airspace operations, a foundational framework and infrastructure for providing sustainable, data-driven, and cohesive decision-making digital services for both traditional and emergent air vehicles is being developed. The reference implementation of Digital Information Platform builds an ecosystem for the aviation community by providing access to a secure and trusted source of aviation data and services. Several key features and services have been implemented to enable secure data sharing, communication, and service registration on the Platform. The technical approach used to implement these features is presented here. NASA-developed integrated aviation data and machine learning based prediction services to optimize airspace operations are available on the Platform. These services are being evaluated in an operational environment by flight operators and the real-world benefits are being captured. The Platform fosters collaboration among industry and researchers to develop complex aviation services and the aim is to make it publicly accessible for consumption by the aviation community.

Digital Transformation↗

NASA NTRSDate not supplied

NASA’s Digital Information Platform to Accelerate the Transformation of the National Airspace System

Digital Transformation↗

NASA NTRS2003

Organizational Culture and Safety

'..only a fool perseveres in error.' Cicero. Humans will break the most advanced technological devices and override safety and security systems if they are given the latitude. Within the workplace, the operator may be just one of several factors in causing accidents or making risky decisions. Other variables considered for their involvement in the negative and often catastrophic outcomes include the organizational context and culture. Many organizations have constructed and implemented safety programs to be assimilated into their culture to assure employee commitment and understanding of the importance of everyday safety. The purpose of this paper is to examine literature on organizational safety cultures and programs that attempt to combat vulnerability, risk taking behavior and decisions and identify the role of training in attempting to mitigate unsafe acts.

Adams, Catherine A.↗

NASA NTRSDate not supplied

NASA’s Unsteady Pressure-Sensitive Paint Phase I Development Overview

Since 2019, a group out of NASA Ames Research Center(ARC)has been focused on implementing systematic updates to make unsteady pressure-sensitive paint (uPSP) a more viable capability for production wind tunnel testing. Focusing on the general categories of data acquisition, data transfer, data processing, and data visualization, the uPSP Development Team has made several improvements to increase data quality and innovate a more workable system that would provide valuable surface pressure data to customers. As a result of the COVID-19 pandemic and several initial demonstration tests prior to the formal start of the development effort, the decision was made to focus on launch vehicles as the test article. To-date this development has focused on implementation in the ARC Unitary Plan Wind Tunnel 11-by11-footTransonic Wind Tunnel due to the large optical access of the test section and that the NASA Advanced Supercomputer is located at ARC. This paper summarizes the project origins and the results of four years of development effort, which will all culminate in a final demonstration test in the first half of2024.

unsteady pressure-sensitive paint↗

NASA NTRS1981

Optical recognition of statistical patterns

Optical implementation of the Fukunaga-Koontz transform (FKT) and the Least-Squares Linear Mapping Technique (LSLMT) is described. The FKT is a linear transformation which performs image feature extraction for a two-class image classification problem. The LSLMT performs a transform from large dimensional feature space to small dimensional decision space for separating multiple image classes by maximizing the interclass differences while minimizing the intraclass variations. The FKT and the LSLMT were optically implemented by utilizing a coded phase optical processor. The transform was used for classifying birds and fish. After the F-K basis functions were calculated, those most useful for classification were incorporated into a computer generated hologram. The output of the optical processor, consisting of the squared magnitude of the F-K coefficients, was detected by a T.V. camera, digitized, and fed into a micro-computer for classification. A simple linear classifier based on only two F-K coefficients was able to separate the images into two classes, indicating that the F-K transform had chosen good features. Two advantages of optically implementing the FKT and LSLMT are parallel and real time processing.

Lee, S. H.↗

NASA NTRS2014

A Sounding-based Severe Weather Tool to Support Daily Operations at Kennedy Space Center and Cape Canaveral Air Force Station

People and property at Kennedy Space Center (KSC) and Cape Canaveral Air Force Station (CCAFS) are at risk when severe weather occurs. Strong winds, hail and tornadoes can injure individuals and cause costly damage to structures if not properly protected. NASA's Launch Services Program and Ground Systems Development and Operations Program and other KSC programs use the daily and weekly severe weather forecasts issued by the 45th Weather Squadron (45 WS) to determine if they need to limit an activity such as working on gantries, or protect property such as a vehicle on a pad. The 45 WS requested the Applied Meteorology Unit (AMU) develop a warm season (May-September) severe weather tool for use in the Meteorological Interactive Data Display System (MIDDS) based on the late morning, 1500 UTC (1100 local time), CCAFS (XMR) sounding. The 45 WS frequently makes decisions to issue a severe weather watch and other severe weather warning support products to NASA and the 45th Space Wing in the late morning, after the 1500 UTC sounding. The results of this work indicate that certain stability indices based on the late morning XMR soundings can depict differences between days with reported severe weather and days with no reported severe weather. The AMU determined a frequency of reported severe weather for the stability indices and implemented an operational tool in MIDDS.

Hail↗

NASA NTRS2024

Smallsat 2024 - Starling Cubesat Swarm Technology Demonstration Flight Results

The Starling swarm of four 6U CubeSats launched in July 2023 to test four key technologies to enable future swarm missions: 1) Mobile Ad-Hoc Networking (MANET) over a crosslink radio network 2) Autonomous onboard decision-making for operations 3) Optical-based absolute and relative navigation 4) Autonomous maneuver planning and execution The Starling team implemented the Better Approach to Mobile Ad-hoc Networking (B.A.T.M.A.N.) protocol to automatically manage the crosslink network of four satellites. The B.A.T.M.A.N. protocol uses a decentralized approach to managing a multi-hop mesh network of devices, in this case, a satellite swarm. The four satellites were able to successfully establish a network at multiple data rates and demonstrate file transfer and command issuance between spacecraft over the network. Starling incorporated Distributed Spacecraft Autonomy's (DSA) software to demonstrate onboard decision-making. The DSA software takes L1/L2 band GPS measurements and uses them to estimate the relative Total Electron Count (TEC) in the ionosphere. The onboard software then determines if there are any features of interest and provides that information to the other satellites over the crosslink network. The swarm of satellites then reaches a consensus on the optimal TEC observation strategy and adjusts its measurement collection tactics autonomously. The Starling Formation-Flying Optical Experiment (StarFOX), produced by Stanford's Space Rendezvous Laboratory, uses the onboard star trackers to collect images of the other swarm spacecraft and produce angles-only navigation estimates. This system is envisioned to be valuable in applications in which Global Navigation Satellite Systems (GNSS) are not available, such as in cis-lunar or deep space. StarFOX successfully applied its algorithms to multiple simultaneous spacecraft targets using the star tracker imagery. Finally, Starling used Emergent Space's Cluster Flight Application (CFA) software suite for the Reconfiguration and Orbit Maintenance Experiments Onboard (ROMEO) demonstration of autonomously planning and executing propulsive maneuvers. Large swarms will need to be able to maintain formation requirements with minimal operator involvement, especially as the size of the swarm scales up. Results from the ROMEO experiment are presented. Starling is funded by the Small Spacecraft Technology (SST) program out of NASA's Space Technology Mission Directorate (STMD).

distributed systems↗

NASA NTRS2015

System-Oriented Runway Management Concept of Operations

This document describes a concept for runway management that maximizes the overall efficiency of arrival and departure operations at an airport or group of airports. Specifically, by planning airport runway configurations/usage, it focuses on the efficiency with which arrival flights reach their parking gates from their arrival fixes and departure flights exit the terminal airspace from their parking gates. In the future, the concept could be expanded to include the management of other limited airport resources. While most easily described in the context of a single airport, the concept applies equally well to a group of airports that comprise a metroplex (i.e., airports in close proximity that share resources such that operations at the airports are at least partially dependent) by including the coordination of runway usage decisions between the airports. In fact, the potential benefit of the concept is expected to be larger in future metroplex environments due to the increasing need to coordinate the operations at proximate airports to more efficiently share limited airspace resources. This concept, called System-Oriented Runway Management (SORM), is further broken down into a set of airport traffic management functions that share the principle that operational performance must be measured over the complete surface and airborne trajectories of the airport's arrivals and departures. The "system-oriented" term derives from the belief that the traffic management objective must consider the efficiency of operations over a wide range of aircraft movements and National Airspace System (NAS) dynamics. The SORM concept is comprised of three primary elements: strategic airport capacity planning, airport configuration management, and combined arrival/departure runway planning. Some aspects of the SORM concept, such as using airport configuration management1 as a mechanism for improving aircraft efficiency, are novel. Other elements (e.g., runway scheduling, which is a part of combined arrival/departure runway scheduling) have been well studied, but are included in the concept for completeness and to allow the concept to define the necessary relationship among the elements. The goal of this document is to describe the overall SORM concept and how it would apply both within the NAS and potential future Next Generation Air Traffic System (NextGen) environments, including research conducted to date. Note that the concept is based on the belief that runways are the primary constraint and the decision point for controlling efficiency, but the efficiency of runway management must be measured over a wide range of space and time. Implementation of the SORM concept is envisioned through a collection of complementary, necessary capabilities collectively focused on ensuring efficient arrival and departure traffic management, where that efficiency is measured not only in terms of runway efficiency but in terms of the overall trajectories between parking gates and transition fixes. For the more original elements of the concept-airport configuration management-this document proposes specific air traffic management (ATM) decision-support automation for realizing the concept.

Lohr, Gary W.↗

NASA NTRS2006

Construction and Resource Utilization Explorer (CRUX): Implementing Instrument Suite Data Fusion to Characterize Regolith Hydrogen Resources

CRUX is a modular suite of geophysical and borehole instruments combined with display and decision support system (MapperDSS) tools to characterize regolith resources, surface conditions, and geotechnical properties. CRUX is a NASA-funded Technology Maturation Program effort to provide enabling technology for Lunar and Planetary Surface Operations (LPSO). The MapperDSS uses data fusion methods with CRUX instruments, and other available data and models, to provide regolith properties information needed for LPSO that cannot be determined otherwise. We demonstrate the data fusion method by showing how it might be applied to characterize the distribution and form of hydrogen using a selection of CRUX instruments: Borehole Neutron Probe and Thermal Evolved Gas Analyzer data as a function of depth help interpret Surface Neutron Probe data to generate 3D information. Secondary information from other instruments along with physical models improves the hydrogen distribution characterization, enabling information products for operational decision-making.

in situ resource utilization (ISRU)↗

NASA NTRS2009

Joint Carrier-Phase Synchronization and LDPC Decoding

A method has been proposed to increase the degree of synchronization of a radio receiver with the phase of a suppressed carrier signal modulated with a binary- phase-shift-keying (BPSK) or quaternary- phase-shift-keying (QPSK) signal representing a low-density parity-check (LDPC) code. This method is an extended version of the method described in Using LDPC Code Constraints to Aid Recovery of Symbol Timing (NPO-43112), NASA Tech Briefs, Vol. 32, No. 10 (October 2008), page 54. Both methods and the receiver architectures in which they would be implemented belong to a class of timing- recovery methods and corresponding receiver architectures characterized as pilotless in that they do not require transmission and reception of pilot signals. The proposed method calls for the use of what is known in the art as soft decision feedback to remove the modulation from a replica of the incoming signal prior to feeding this replica to a phase-locked loop (PLL) or other carrier-tracking stage in the receiver. Soft decision feedback refers to suitably processed versions of intermediate results of iterative computations involved in the LDPC decoding process. Unlike a related prior method in which hard decision feedback (the final sequence of decoded symbols) is used to remove the modulation, the proposed method does not require estimation of the decoder error probability. In a basic digital implementation of the proposed method, the incoming signal (having carrier phase theta theta (sub c) plus noise would first be converted to inphase (I) and quadrature (Q) baseband signals by mixing it with I and Q signals at the carrier frequency [wc/(2 pi)] generated by a local oscillator. The resulting demodulated signals would be processed through one-symbol-period integrate and- dump filters, the outputs of which would be sampled and held, then multiplied by a soft-decision version of the baseband modulated signal. The resulting I and Q products consist of terms proportional to the cosine and sine of the carrier phase cc as well as correlated noise components. These products would be fed as inputs to a digital PLL that would include a number-controlled oscillator (NCO), which provides an estimate of the carrier phase, theta(sub c).

Simon, Marvin↗

NASA NTRS2000

Collision in space

On June 25, 1997, the Russian supply spacecraft Progress 234 collided with the Mir space station, rupturing Mir's pressure hull, throwing it into an uncontrolled attitude drift, and nearly forcing evacuation of the station. Like many high-profile accidents, this collision was the consequence of a chain of events leading to the final piloting errors that were its immediate cause. The discussion in this article does not resolve the relative contributions of the actions and decisions in this chain. Neither does it suggest corrective measures, many of which are straightforward and have already been implemented by the National Aeronautics and Space Administration (NASA) and the Russian Space Agency. Rather, its purpose is to identify the human factors that played a pervasive role in the incident. Workplace stress, fatigue, and sleep deprivation were identified by NASA as contributory factors in the Mir-Progress collision (Culbertson, 1997; NASA, forthcoming), but other contributing factors, such as requiring crew to perform difficult tasks for which their training is not current, could potentially become important factors in future situations.

Mir Project↗

NASA NTRS1987

On the synchronizability and detectability of random PPM sequences

The problem of synchronization and detection of random pulse-position-modulation (PPM) sequences is investigated under the assumption of perfect slot synchronization. Maximum-likelihood PPM symbol synchronization and receiver algorithms are derived that make decisions based both on soft as well as hard data; these algorithms are seen to be easily implementable. Bounds derived on the symbol error probability as well as the probability of false synchronization indicate the existence of a rather severe performance floor, which can easily be the limiting factor in the overall system performance. The performance floor is inherent in the PPM format and random data and becomes more serious as the PPM alphabet size Q is increased. A way to eliminate the performance floor is suggested by inserting special PPM symbols in the random data stream.

Georghiades, Costas N.↗

NASA NTRS1987

On the synchronizability and detectability of random PPM sequences

The problem of synchronization and detection of random pulse-position-modulation (PPM) sequences is investigated under the assumption of perfect slot synchronization. Maximum likelihood PPM symbol synchronization and receiver algorithms are derived that make decisions based both on soft as well as hard data; these algorithms are seen to be easily implementable. Bounds were derived on the symbol error probability as well as the probability of false synchronization that indicate the existence of a rather severe performance floor, which can easily be the limiting factor in the overall system performance. The performance floor is inherent in the PPM format and random data and becomes more serious as the PPM alphabet size Q is increased. A way to eliminate the performance floor is suggested by inserting special PPM symbols in the random data stream.

Georghiades, Costas N.↗

NASA NTRS1989

On the synchronizability and detectability of random PPM sequences

The problem of synchronization and detection of random pulse-position modulation (PPM) sequences is investigated under the assumption of perfect slot synchronization. Maximum-likelihood PPM symbol synchronization and receiver algorithms are derived that make decisions based on both soft as well as hard data; these algorithms are seen to be easily implementable. Bounds were derived on the symbol error probability as well as the probability of false synchronization that indicate the existence of a rather severe performance floor, which can easily be the limiting factor in the overall system performance. The performance floor is inherent in the PPM format and random data and becomes more serious as the PPM alphabet size Q is increased. A way to eliminate the performance floor is suggested by inserting special PPM symbols in the random data stream.

Georghiades, Costas N.↗

NASA NTRS1990

Advanced Transport Operating Systems Program

NASA-Langley's Advanced Transport Operating Systems Program employs a heavily instrumented, B 737-100 as its Transport Systems Research Vehicle (TRSV). The TRSV has been used during the demonstration trials of the Time Reference Scanning Beam Microwave Landing System (TRSB MLS), the '4D flight-management' concept, ATC data links, and airborne windshear sensors. The credibility obtainable from successful flight test experiments is often a critical factor in the granting of substantial commitments for commercial implementation by the FAA and industry. In the case of the TRSB MLS, flight test demonstrations were decisive to its selection as the standard landing system by the ICAO.

White, John J.↗