Results for “situation awareness” — Page 48

NASA NTRS2018

New, Multi-Spectral (RGB) Imagery Products from GOES-16 Usher in a New Era of Satellite Meteorology

Otherwise known as "R-G-B" imagery, these new products provide a paradigm shift in short-term nowcasting and situational awareness via remote sensing. SPoRT used NASA instruments like MODIS and S-NPP VIIRS to demonstrate RGB capabilities prior to GOES-16. Now, with geostationary RGBs in operations, SPoRT has collaborated with select forecasters to assess the impact of this new GOES-16 capability.

Fuell, Kevin K.↗

NASA NTRS2018

Collision Avoidance "Short Course" Part III: CA in Changing Space Flight Environment

Satellite conjunction assessment is perhaps the fastest-growing area in space situational awareness and protection, with military, civil, and commercial satellite owner/operators embracing more and more sophisticated processes to "avoid the avoidable" namely collisions between high-value space assets and orbital debris. NASA and CNES have collaborated to offer an introductory short course on all the major aspects of the conjunction assessment problem. This half-day course will cover satellite conjunction dynamics and theory, JSpOC conjunction data products, major risk assessment parameters and plots, conjunction remediation decision support, and present and future challenges. This briefing represents the NASA portion of the course.

Newman, Lauri↗

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 NTRS2016

Predicting Real-Time Safety of the National Airspace System

To gain the situational awareness necessary for informed decision making regarding avoidance of airspace hazards, each operator must consolidate operations-relevant information from disparate sources and apply extensive domain knowledge to correctly interpret not just the current state of the NAS but forecast its (combined) evolution over the duration of the operation. This time- and workload-intensive process is periodically repeated throughout the operation so that changes can be managed in a timely manner.The imprecision, inaccuracies, inconsistency, and incompleteness of the incoming data further challenges the process. To facilitate informed decision making, this paper presents a model-based framework for the textitautomated real-time monitoring and prediction of possible effects of airspace hazards on the safety of the National Airspace System (NAS). First, hazards to flight are identified and transformed into sms, that is, quantities of interest that could be evaluated based on available data and are predictive of an unsafe event. The sms and associated thresholds that specify when an event transitions from emphsafe to emphunsafe are combined with models of airspace operations and aircraft dynamics. The framework can include any hazard to flight that can be modeled quantitatively. Models can be detailed and complex, or they can be considerably simplifed, as appropriate to the application. Real-time NAS safety monitoring and prediction begins with an estimate of the state of the NAS using the dynamic models. Given the state estimate and a probability distribution of future inputs to the NAS, we can then predict the evolution of the NAS - the future state - and the occurrence of hazards and unsafe events. The entire probability distribution of airspace sms is computed, not just point estimates, without significant assumptions regarding the distribution type andor parameters. We demonstrate our overall approach through a simulated scenario in which we predict the occurrence of some unsafe events and show how these predictions evolve in time as flight operations progress. Predictions accounting for common sources of uncertainty are included and it is shown how the predictions improve in time, become more confident, and change dynamically as new information is made available to the prediction algorithm.

safety↗

NASA NTRS2018

Tactile Display for EVA

As human spaceflight crews engage in more complex missions beyond low Earth orbit, their need for autonomy increases. ISS-like operations in which Earth-based mission control monitors life-critical systems and provides real time support for crew tasks will be limited by communication bandwidth and delays, forcing the crew to take on a subset of these responsibilities. This presents the biggest challenge during Extravehicular Activity (EVA)s, where the crew is already overloaded and their ability to interact with information systems is severely limited. Tactile displays, which present information using the sense of touch, expand the users' communication bandwidth. This untapped interface modality can be used for a wide range of interactions during EVA, including emergency alerts, non-emergency situational awareness, and simple instruction.

Aceves, Ricco↗

NASA NTRS2018

Deepti: Deep Learning-Based Tropical Cyclone Intensity Estimation

We present the development of a deep learning model for objective estimation of tropical cyclone intensity at a higher temporal frequency, deployment of the model in production, design and implementation of the tropical cyclone monitoring and intensity estimation system and development of an interactive portal for situational awareness and evaluation of intensity estimation.

Maskey, Manil↗

NASA NTRS2019

Simultaneous Localization and Mapping for Satellite Rendezvous and Proximity Operations Using Random Finite Sets

Future space missions require that spacecraft have the capability to autonomously navigate non-cooperative environments for rendezvous and proximity operations (RPO). Current relative navigation filters can have difficulty in these situations, diverging due to complications with data association, high measurement uncertainty, and clutter, particularly when detailed a priori maps of the target object or spacecraft do not exist. The goal of this work is to demonstrate the feasibility of random finite set (RFS) filters for spacecraft relative navigation and pose estimation. The approach is to formulate satellite relative navigation and pose estimation as a simultaneous localization and mapping (SLAM) problem, in which an observer spacecraft seeks to simultaneously estimate the location of features on a target object or spacecraft as well as its relative position, velocity and attitude. This work utilizes a filter developed using the framework of RFS which are well suited to multi-target SLAM operations, avoiding data association entirely. Relevant RPO scenarios with simulated flash LIDAR measurements are tested with a Probability Hypothesis Density (PHD) RFS filter embedded in a particle filter to obtain a feature map of a target and a relative pose estimate between the target and observer. Preliminary results show that an RFS-based filter can successfully perform SLAM in a spacecraft relative navigation scenario with no a priori map of the target. These results demonstrate the feasibility of RFS filtering for spacecraft relative navigation and motivate future studies which may expand to tracking space objects for space situational awareness, as well as relative navigation around small bodies.

Schlenker, Lauren↗

NASA NTRS2019

Simultaneous Localization and Mapping for Satellite Rendezvous and Proximity Operations using Random Finite Sets

Future space missions require that spacecraft have the capability to autonomously navigate non-cooperative environments for rendezvous and proximity operations (RPO). Current relative navigation filters can have difficulty in these situations, diverging due to complications with data association, high measurement uncertainty, and clutter, particularly when detailed a priori maps of the target object or spacecraft do not exist. The goal of this work is to demonstrate the feasibility of random finite set (RFS) filters for spacecraft relative navigation and pose estimation. The approach is to formulate satellite relative navigation and pose estimation as a simultaneous localization and mapping (SLAM) problem, in which an observer spacecraft seeks to simultaneously estimate the location of features on a target object or spacecraft as well as its relative position, velocity and attitude. This work utilizes a filter developed using the framework of RFS which are well suited to multi-target SLAM operations, avoiding data association entirely. Relevant RPO scenarios with simulated flash LIDAR measurements are tested with a Probability Hypothesis Density (PHD) RFS filter embedded in a particle filter to obtain a feature map of a target and a relative pose estimate between the target and observer. Preliminary results show that an RFS-based filter can successfully perform SLAM in a spacecraft relative navigation scenario with no a priori map of the target. These results demonstrate the feasibility of RFS filtering for spacecraft relative navigation and motivate future studies which may expand to tracking space objects for space situational awareness, as well as relative navigation around small bodies.

Schlenker, Lauren↗

NASA NTRS2018

San Francisco Bar Pilot Fatigue Study

The purpose of this study was to evaluate the extent of fatigue among San Francisco Bar Pilots (Maritime Pilots) and its potential impact on safety, and to make recommendations concerning how the risk of fatigue could be managed. Information was gathered via a literature review, observations of Bar Pilots at work, surveys, a task analysis, and an analysis of dispatch records.The work of San Francisco Bar Pilots involves an unusual mix of activities and job demands. Their work calls for situational awareness, reasoning, communication, and perceptual abilities comparable to those required by airline pilots and air traffic controllers. Errors can have severe consequences for public safety and the environment, as well as significant financial costs. Fatigue is increasingly recognized as a hazard that must be managed by the transportation industry. The reduced sleep quality and quantity experienced by personnel who work at night, in conjunction with human circadian rhythms can lead to an operationally significant level of cognitive impairment. The cognitive impact of fatigue includes functions that are critical to safe maritime piloting, such as vigilance, judgment, reaction time and communication. The surveys distributed to Bar Pilots did not uncover evidence of widespread fatigue. The survey results also suggested that fatigue was not a major concern of Bar Pilots. Bar Pilots had overall low scores on the subjective fatigue measures used in the survey, and generally assessed the safety risk due to fatigue as low. Compared to air traffic controllers, Bar Pilots gave significantly lower ratings on questions concerning the prevalence and impact of fatigue. The application of fatigue modeling software to Bar Pilot dispatch records identified that in most cases, pilot's cognitive effectiveness was predicted to be acceptable during their duty periods. However, these results could not be verified with objective data.The study identified a number of fatigue issues that deserve attention. These include Bar Pilot work periods that frequently infringe on the circadian low, consecutive work periods without a significant break, consecutive periods of night work, unpredictable work schedules, start time variability, the potential for sleep inertia, and the number of pilots on the board at any given time.

fatigue↗

NASA NTRS2019

ISEP: A Joint SRAG/CCMC Collaboration to Improve Mitigation of Space Weather Effects on Crew Health in the Exo-LEO Era

The Space Radiation Analysis Group (SRAG) at Johnson Space Center (JSC) is tasked with monitoring changes to space weather and mitigating any resultant impacts to crew health and safety. As human spaceflight goals extend from Low-Earth Orbit (LEO) missions like the International Space Station (ISS) to the moon, Mars and beyond, SRAG will need to update their current approach for crew monitoring of and protection from radiation exposure due to energetic Solar Particle Events (ESPEs). Challenges faced in planning exo-LEO missions include the lack of protection from the Earth’s geomagnetic field employed by the ISS in addition to limited communication capability between the crew and the ground. In the event of an ESPE, the current ISS trajectory ensures that the vehicle is only traveling through fields of higher radiation exposure for a brief period of time; the Earth’s geomagnetic field prevents the penetration of the high-energy particles of concern throughout the majority of the orbit. Exo-LEO missions, on the other hand, require that the vehicle travel through free space, exposing vehicle and crew to the full impact of the ESPE. NASA has combined multiple approaches to resolve this radiation exposure issue. New vehicles are designed to take advantage of advances in particle transport modeling capabilities and shielding technology, allowing redistribution of mass throughout the vehicle to areas of thinner shielding when the energetic particle flux has increased to levels of concern. Although vehicle shielding is an important aspect of radiation exposure protection, there is a continued requirement to monitor and predict the space weather environment. To this end, SRAG maintains a console position in Mission Control with 24/7 mission support capability. In the event of increased solar activity, SRAG collaborates with the Flight Control Team (FCT) to determine if crew action (i.e., shelter) is required. During any increase in solar activity, the FCT needs three pieces of information to effectively decide the crew response in light of other required mission tasks: if an event (ESPE) will occur, how ‘intense’ an observed event will be, and how long will an observed event will last. An ideal alert system limits false alarms, therefore causing the crew to take action unnecessarily, without ignoring events that pose a hazard to the crew. SRAG’s current operational concept for ISS missions focuses on short-term forecasts, best described as ‘now-casting’. Console operators are in daily communication with the Space Weather Prediction Center (SWPC) for situational awareness purposes. When conditions exist that may lead to increased solar activity, operators receive notifications from SWPC. In the case of a well-connected ESPE, the console operator may only have on the order of minutes to several hours to notify the FCT of the event and provide a recommendation for crew action. As NASA shifts to exo-LEO missions, the increased time in free space as well as the reduced ability to communicate with the crew will force a transition in crew protection strategy that emphasizes improvments to both the accuracy and the lead time in forecasting capabilities.

Barzilla, Janet E.↗

NASA NTRS2019

Modular Damage Detection for Expandable and Inflatable Structures

NASA has identified potential damage from micrometeoroid and orbital debris (MMOD) impacts as a primary threat to Commercial Crew Program vehicles. The International Space Station (ISS) and extraterrestrial habitats also exhibit the risk of damage caused by MMODs. Currently no integrated in-situ or real-time health monitoring damage detection system is being used for expandable and inflatable structures. A novel, modular damage detection system design that incorporates interchangeable and replaceable sensory panels in a foldable architecture is described. The design implements technologies that provide for situational awareness, self-configuration, and damage detection and localization. The system is applicable for the new Gateway and surface and ground support infrastructure

Lewis, Mark E.↗

NASA NTRS2014

First Results from the Mojave Volatiles Prospector (MVP) Field Campaign, a Lunar Polar Rover Mission Analog

The Mojave Volatiles Prospector (MVP) project is a science-driven field program with the goal to produce critical knowledge for conducting robotic exploration of the Moon. MVP will feed science, payload, and operational lessons learned to the development of a real-time, short-duration lunar polar volatiles prospecting mission. MVP achieves these goals through a simulated lunar rover mission to investigate the composition and distribution of surface and subsurface volatiles in a natural and a priori unknown environment within the Mojave Desert, improving our understanding of how to find, characterize, and access volatiles on the Moon. The MVP field site is the Mojave Desert, selected for its low, naturally occurring water abundance. The Mojave typically has on the order of 2-6% water, making it a suitable lunar analog for this field test. MVP uses the Near Infrared and Visible Spectrometer Subsystem (NIRVSS), Neutron Spectrometer Subsystem (NSS), and a downward facing GroundCam camera on the KREX-2 rover to investigate the relationship between the distribution of volatiles and soil crust variation. Through this investigation, we mature robotic in situ instruments and concepts of instrument operations, improve ground software tools for real time science, and carry out publishable research on the water cycle and its connection to geomorphology and mineralogy in desert environments. A lunar polar rover mission is unlike prior space missions and requires a new concept of operations. The rover must navigate 3-5 km of terrain and examine multiple sites in in just ~6 days. Operational decisions must be made in real time, requiring constant situational awareness, data analysis and rapid turnaround decision support tools. This presentation will focus on the first science results and operational architecture findings from the MVP field deployment relevant to a lunar polar rover mission.

Heldmann, Jennifer L.↗

NASA NTRS2019

Alternatives for Scheduling Departures for Efficient Surface Metering in ATD-2: Exploration in a Human-in-the-Loop Simulation

A Human-in-the-Loop (HITL) simulation was conducted to explore whether Ramp Controllers at Charlotte Douglas International Airport (CLT) could both release departing aircraft at an advised time at the gate and also meet an advised time at the spot, where Air Traffic Control (ATC) takes control. Three conditions were compared: (1) Baseline, with no scheduling advisories, (2) instructions to meet advisory times at the gate only, and (3) instructions to meet advisory times at both the gate and the spot. Surprisingly, results showed increased compliance with advisories at the spot in the second condition. This was likely due to increased ramp congestion in the third condition as well as higher Ramp Controller workload and lower situation awareness. Instructing Ramp Controllers to meet scheduling times at the spots, in addition to the gates, is therefore not likely to improve surface scheduling predictability at CLT and may indeed worsen it.

airport surface scheduling↗

NASA NTRS2019

Predicting Satellite Close Approaches Using Statistical Parameters in the Context of Artificial Intelligence

In order to ensure a sustainable use of low earth orbit in particular and near Earth space in general, reliable and effective close approach prediction be-tween space objects is key. Only this allows for efficient and timely colli-sion avoidance. Space Situational Awareness (SSA) for commercial and government missions will be facing the rapidly growing amount of small and potentially less agile satellites as well as debris in the near earth realm, such as the increase in CubeSat launches and upcoming large constellations. At the same time, space object detection capabilities are expected to increase significantly, allowing for the reliable detection of smaller objects, e.g. when the Air Force Space Fence radar becomes operational. In combination, the space object catalog is expected to increase tremendously in size. In this paper, we introduce an investigative approach based on the latest capabili-ties in artificial intelligence in fostering the potential for fast and accurate close approach predictions. We consider the study of statistical and infor-mation theory parameters in contrast and complementary to the classical probability of collision computation alone, in order to determine the feasi-bility of reliably predicting close approaches.

Mashiku, A.↗

NASA NTRS2019

Predicting Satellite Close Approaches Using Statistical Parameters in the Context of Artificial Intelligence

In order to ensure a sustainable use of low earth orbit in particular and near Earth space in general, reliable and effective close approach prediction be-tween space objects is key. Only this allows for efficient and timely colli-sion avoidance. Space Situational Awareness (SSA) for commercial and government missions will be facing the rapidly growing amount of small and potentially less agile satellites as well as debris in the near earth realm, such as the increase in CubeSat launches and upcoming large constellations. At the same time, space object detection capabilities are expected to increase significantly, allowing for the reliable detection of smaller objects, e.g. when the Air Force Space Fence radar becomes operational. In combination, the space object catalog is expected to increase tremendously in size. In this paper, we introduce an investigative approach based on the latest capabili-ties in artificial intelligence in fostering the potential for fast and accurate close approach predictions. We consider the study of statistical and infor-mation theory parameters in contrast and complementary to the classical probability of collision computation alone, in order to determine the feasi-bility of reliably predicting close approaches.

Mashiku, Alinda↗

NASA NTRS2019

Nasa Conjunction Assessment Risk Analysis Updated Requirements Architecture

The NASA Conjunction Assessment Risk Analysis (CARA) program has been performing routine on-orbit satellite conjunction risk analysis for unmanned NASA spacecraft since 2005, and has developed a robust operations procedure and set of recommended best practices for operational conjunction assessment. However, a number of recent developments in Space Situational Awareness and commercial space operations conduct, such as the immanent deployment of much more sensitive space sensing systems and the launching of much larger satellite constellations, have begun to challenge these standard collision risk parameters and calculations. In response CARA has pursued a multi-year evaluation initiative to re-examine risk assessment algorithms and techniques, to develop needed improvements, and to assemble analysis-based operational requirements. This paper gives an overview of the principal parts of the Conjunction Assessment (CA) risk assessment process used at CARA, outlines the technical challenges that each part presents, surveys the possible solutions, and then indicates which particular solution is being recommended for NASA.

Newman, Lauri K.↗

NASA NTRS2019

NASA Conjunction Assessment Risk Analysis (CARA) Updated Requirements Architecture

The NASA Conjunction Assessment Risk Analysis (CARA) program has been performing routine on-orbit satellite conjunction risk analysis for unmanned NASA spacecraft since 2005, and has developed a robust operations procedure and set of recommended best practices for operational conjunction assessment. However, a number of recent developments in Space Situational Awareness and commercial space operations conduct, such as the immanent deployment of much more sensitive space sensing systems and the launching of much larger satellite constellations, have begun to challenge these standard collision risk parameters and calculations. In response CARA has pursued a multi-year evaluation initiative to re-examine risk assessment algorithms and techniques, to develop needed improvements, and to assemble analysis-based operational requirements. This paper gives an overview of the principal parts of the Conjunction Assessment (CA) risk assessment process used at CARA, outlines the technical challenges that each part presents, surveys the possible solutions, and then indicates which particular solution is being recommended for NASA.

Newman, L. K.↗

NASA NTRS2019

Collision Avoidance "Short Course" Part III: CA in Changing Space Flight Environment

Satellite conjunction assessment is perhaps the fastest-growing area in space situational awareness and protection, with military, civil, and commercial satellite owner/operators embracing more and more sophisticated processes to "avoid the avoidable"â€”namely collisions between high-value space assets and orbital debris. NASA and CNES have collaborated to offer an introductory short course on all the major aspects of the conjunction assessment problem. This half-day course will cover satellite conjunction dynamics and theory, JSpOC conjunction data products, major risk assessment parameters and plots, conjunction remediation decision support, and present and future challenges. This briefing represents the NASA portion of the course.

avoidance↗