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NASA NTRS2017

Protecting the Health of Astronauts: Enhancing Occupational Health Monitoring and Surveillance for Former NASA Astronauts to Understand Long-Term Outcomes of Spaceflight-Related Exposures

The astronaut community is unique, and may be disproportionately exposed to occupational hazards not commonly seen in other communities. The extent to which the demands of the astronaut occupation and exposure to spaceflight-related hazards affect the health of the astronaut population over the life course is not completely known. A better understanding of the individual, population, and mission impacts of astronaut occupational exposures is critical to providing clinical care, targeting occupational surveillance efforts, and planning for future space exploration. The ability to characterize the risk of latent health conditions is a significant component of this understanding. Provision of health screening services to active and former astronauts ensures individual, mission, and community health and safety. Currently, the NASA-Johnson Space Center (JSC) Flight Medicine Clinic (FMC) provides extensive medical monitoring to active astronauts throughout their careers. Upon retirement, astronauts may voluntarily return to the JSC FMC for an annual preventive exam. However, current retiree monitoring includes only selected screening tests, representing an opportunity for augmentation. The potential long-term health effects of spaceflight demand an expanded framework of testing for former astronauts. The need is two-fold: screening tests widely recommended for other aging populations are necessary to rule out conditions resulting from the natural aging process (e.g., colonoscopy, mammography); and expanded monitoring will increase NASA's ability to better characterize conditions resulting from astronaut occupational exposures. To meet this need, NASA has begun an extensive exploration of the overall approach, cost, and policy implications of e an Astronaut Occupational Health program to include expanded medical monitoring of former NASA astronauts. Increasing the breadth of monitoring services will ultimately enrich the existing evidence base of occupational health risks to astronauts. Such an expansion would therefore improve the understanding of the health of the astronaut population as a whole, and the ability to identify, mitigate, and manage such risks in preparation for deep space exploration missions.

Rossi, Meredith↗
NASA NTRS2017

Tracking Historical NASA EVA Training: Lifetime Surveillance of Astronaut Health (LSAH) Development of the EVA Suit Exposure Tracker (EVA SET)

During a spacewalk, designated as extravehicular activity (EVA), an astronaut ventures from the protective environment of the spacecraft into the vacuum of space. EVAs are among the most challenging tasks during a mission, as they are complex and place the astronaut in a highly stressful environment dependent on the spacesuit for survival. Due to the complexity of EVA, NASA has conducted various training programs on Earth to mimic the environment of space and to practice maneuvers in a more controlled and forgiving environment. However, rewards offset the risks of EVA, as some of the greatest accomplishments in the space program were accomplished during EVA, such as the Apollo moonwalks and the Hubble Space Telescope repair missions. Water has become the environment of choice for EVA training on Earth, using neutral buoyancy as a substitute for microgravity. During EVA training, an astronaut wears a modified version of the spacesuit adapted for working in water. This high fidelity suit allows the astronaut to move in the water while performing tasks on full-sized mockups of space vehicles, telescopes, and satellites. During the early Gemini missions, several EVA objectives were much more difficult than planned and required additional time. Later missions demonstrated that "complex (EVA) tasks were feasible when restraints maintained body position and underwater simulation training ensured a high success probability".1,2 EVA training has evolved from controlling body positioning to perform basic tasks to complex maintenance of the Hubble Space Telescope and construction of the International Space Station (ISS). Today, preparation is centered at special facilities built specifically for EVA training, such as the Neutral Buoyancy Laboratory (NBL) at NASA's Johnson Space Center ([JSC], Houston) and the Hydrolab at the Gagarin Cosmonaut Training Centre ([GCTC], Star City, outside Moscow). Underwater training for an EVA is also considered hazardous duty for NASA astronauts. This activity places astronauts at risk for decompression sickness and barotrauma as well as various musculoskeletal disorders from working in the spacesuit. The medical, operational and research communities over the years have requested access to EVA training data to better understand the risks. As a result of these requests, epidemiologists within the Lifetime Surveillance of Astronaut Health (LSAH) team have compiled records from numerous EVA training venues to quantify the exposure to EVA training. The EVA Suit Exposure Tracker (EVA SET) dataset is a compilation of ground-based training activities using the extravehicular mobility unit (EMU) in neutrally buoyant pools to enhance EVA performance on orbit. These data can be used by the current ISS program and future exploration missions by informing physicians, researchers, and operational personnel on the risks of EVA training in order that future suit and mission designs incorporate greater safety. The purpose of this technical report is to document briefly the various facilities where NASA astronauts have performed EVA training while describing in detail the EVA training records used to generate the EVA SET dataset.

Laughlin, Mitzi S.↗
NASA NTRS2017

Considerations for RTCA Phase 2 Low Size, Weight, and Power (SWAP) Surveillance Requirements

RTCA (Radio Technical Commission for Aeronautics) Special Committee 228 has initiated a second phase for the development of minimum operational performance standards (MOPS) for UAS (Unmanned Aircraft Systems) detect and avoid (DAA) systems. Technologies to enable UAS with less available Size, Weight, and Power (SWaP) will be considered. A white paper is in development for what topics and issues need to be addressed to develop DAA requirements for low SWAP surveillance systems. This briefing will document the issues to be investigated in SC-228. It will also serve as a review with the committee to get feedback so the white paper can be written and finalized. These topics and issues are not necessarily all the things that NASA will contribute to SC-228 during Phase 2, but what the overall committee needs to accomplish. A portion of the work will be in NASA's UAS in the NAS (National Airspace System) project plan.

Santiago, Confesor↗
NASA NTRS2018

Preliminary Error Characterization and Parametric Error Model for the Automatic Dependent Surveillance - Contract Extended Projected Profile Message

A critical component of Trajectory-Based Operations (TBO) is the ability for a consistent and accurate 4-dimensional trajectory (4DT) to be shared and synchronized between airborne and ground systems as well as amongst various ground automation systems. The Aeronautical Telecommunication Network—Baseline 2 (ATN-B2) standard defines the Extended Projected Profile (EPP) trajectory that can be sent via Automatic Dependent Surveillance-Contract (ADS-C) from an aircraft to ground automation. The EPP trajectory message contains a representation of the reference trajectory from an aircraft’s Flight Management System (FMS). In this work, a set of scenarios were run in a high-fidelity aircraft and FMS simulation to perform an initial characterization of EPP trajectory errors under a given set of conditions. The parameters investigated were the route length, route type, wind magnitude error, wind direction error, and with and without a required time-of-arrival (RTA) constraint. In addition, linear regression was used to identify a set of EPP error models for the cross-track, vertical, and time errors.

Guerreiro, Nelson M.↗
NASA NTRS2018

A Component-Level Model of Automatic Dependent Surveillance - Broadcast (ADS-B)

Automatic Dependent Surveillance – Broadcast (ADS-B) is being employed in numerous peer-to-peer initiatives attempting to expand the capacity of the National Airspace System (NAS) or enable mixed operations of manned and unmanned vehicles. Safety assessments of these initiatives rely, in part, on modeling the accuracy of ADS-B in reporting the position and direction of an ownship and surrounding traffic. Frequently, these initiatives utilize a position uncertainty model that applies a reported ADS-B estimation position uncertainty (EPU) value to a Rayleigh distribution and uses a Gauss-Markov random walk to add error to the ADS-B output of a vehicle. This model of ADS-B state error is easy to implement and apply to numerous problems. However, it has a couple of draw-backs. First, the ADS-B state errors are equally probable in all directions. This is a good assumption in situations where aircraft maneuvering is not constrained. However, in situations where the aircraft maneuvering is constrained such as landing, the error distribution is likely to exhibit directionality and the non-directional model may skew results especially when assessing very low probabilities (e.g., 10(exp -9)) of catastrophic encounters. Second, the model does not account for processing latency in the receiving aircraft. NASA Langley Research Center (LaRC) recently examined the feasibility of decreasing the spacing of aircraft on parallel approaches to runways separated by as little as 700 feet. For Monte-Carlo analysis using a high-fidelity simulation of a large transport, LaRC started with a Gauss-Markov model of ADS-B error but then developed a component level model of ADS-B error to increase the fidelity of results.

Madden, Michael M.↗
NASA NTRS2019

Alternative Surveillance Fast Time Simulation with Sensor Uncertainties and Mitigation

This presentation describes a simulation plan for the fast time simulation 3 for the modeling and simulation team in the UAS (Unmanned Aircraft Systems) in the NAS (National Airspace System)project. Objectives: Investigate the effect of limited surveillance volume and realistic radar noise on DAA (Detect and Avoid) performance; Evaluate the ability of the sensor uncertainty mitigation (SUM) feature of the DAIDALUS [Dectect and Avoid...] algorithm to improve DAA alerting and guidance [Includes content on SWaP-C (size, weight, power, and cost) of unmanned aircraft; and Near-mid-air-collision (NMAC).]

UAS↗
NASA NTRSDate not supplied

Oculometric Surveillance of Neuro-Ocular Function

Future missions to the moon or Mars will require the crew to monitor and assess their health and performance more autonomously, with approaches easily useable and interpretable by non-clinicians. If an autonomous oculometric diagnostic-support system proves to be a reliable predictor of impending impairment of visual function in the case of primary ocular pathology on Earth, then it could also be applied in the future to the surveillance of crew to detect the potential progression of sensorimotor and neuro-ocular compromises during extended spaceflight missions, e.g., SANS, and thus guide earlier and more effective countermeasure intervention. Towards that goal, we intend to determine if a set of largely independent eye-movement metrics, called oculometrics, measured using a simple voluntary eye-tracking task that can be completed in just 5 minutes per eye, could provide clinically valid biomarkers of functional visual deficits due to primary ocular pathology. The premise is that oculometrics could be used to monitor slowly evolving ocular pathologies, potentially detecting them even before structural evidence appears in ocular imaging or other current state-of-the-art clinical measures. This study investigates how NASA’s patented oculometric assessment of visual and visuomotor function, shown to correlate with performance in a manual control task, will correlate with standard ophthalmological tests to confirm clinical and thus operational, validity.

eye movements↗
NASA NTRSDate not supplied

Lightweight Surveillance and Target Acquisition Radar Characterization for High Density Vertiplex Beyond Visual Line of Sight Operations

Abstract- with the growth of the National Aeronautics and Space Administration (NASA) National Campaign, it is becoming increasingly important for government and enforcement agencies to be able to monitor and safely track urban air traffic that will take place in the coming years. The performance of the Lightweight Surveillance and Target Acquisition Radar (LSTAR) is investigated and statistically characterized. The compact LSTAR is mounted on a building at NASA Langley Research Center (LaRC) and operated to track a SR-22 aircraft. Performance data of of the LSTAR tracking is presented by comparing the LSTAR-tracked flight against the on-board flight records and statistical characteristics are presented. Implications of findings to operations within High Density Vertiplex (HDV) at LaRC are discussed. The LSTAR ultimately proves to be a compact method to safely track and monitor small aircraft and other unmanned aerial vehicles.

Nicholas Gaug↗
NASA NTRSDate not supplied

Lightweight Surveillance and Target Acquisition Radar Characterization For High Density Vertiplex Beyond Visual Line of Sight Operations

With the growth of the National Aeronautics and Space Administration (NASA) National Campaign, it is becoming increasingly important for government and enforcement agencies to be able to monitor and safely track urban air traffic that will take place in the coming years. The performance of the Lightweight Surveillance and Target Acquisition Radar (LSTAR) is investigated and statistically characterized. The compact LSTAR is mounted on a building at NASA Langley Research Center (LaRC) and operated to track a SR-22 aircraft. Performance data of the LSTAR tracking is presented by comparing the LSTAR-tracked flight against the onboard flight records and statistical characteristics are presented. Implications of findings to operations within High Density Vertiplex (HDV) at LaRC are discussed. The LSTAR ultimately proves to be a compact method to safely track and monitor small aircraft and other unmanned aerial vehicles.

Nicholas M. Gaug↗
NASA NTRS2023

The Lifetime Surveillance of Astronaut Health Newsletter

Welcome to the April 2023 issue of the Lifetime Surveillance of Astronaut Health (LSAH) Newsletter! Along with the familiar subjects in previous issues, this issue will introduce two new sections: Clinic Corner, where Dr. Tim LaVan shares a brief status of the Flight Medicine Clinic, and Formers Corner, where we share images and captions submitted by you and your fellow crewmates!

Tim Lavan↗
NASA NTRSDate not supplied

Assessing Performance of Radar and Visual Sensing Techniques for Ground-To-Air Surveillance in Advanced Air Mobility

The safe integration of Unmanned Aircraft Vehicles (UAV) within the civil airspace is of great interest to NASA’s Advanced Air Mobility project, which envisions high density of operations in and around urban areas that include both UAV and AAM aircraft. To enable safe autonomous operations of both platforms, reliable airspace surveillance strategies must be designed and experimentally validated in relevant scenarios, where multiple small UAV operate flying in low altitude conditions. An example of such a scenario is described in this paper which provides performance assessment of various sensing strategies experimentally tested during flight campaigns with four UAV completing simultaneous missions from vertiports. Such campaigns are performed by the High Density Vertiplex subproject which assesses a prototype of Urban Air Mobility ecosystem. For the purposes of this work, the flights are observed from multiple sensing nodes each with radar and camera sensors. The visual detection and tracking algorithms achieved 96.1% to 99.9% average tracking coverage of the UAV above the horizon, reaching detection ranges larger than 1 kilometer for octocopter. Radar-based tracking shows a lower coverage mainly due to ground clutter removal challenges but provides comparable detection ranges and meter-level range accuracy.

Federica Vitiello↗
NASA NTRS2023

The Lifetime Surveillance of Astronaut Health Newsletter

Welcome to the October 2023 issue of the Lifetime Surveillance of Astronaut Health (LSAH) Newsletter! This issue will showcase our Space Radiation Analysis Group (SRAG), highlighting their contributions towards keeping our astronauts safe during spaceflight.

Ronnie Rafanan↗
NASA NTRS2024

Lifetime Surveillance of Astronaut Health Newsletter

Welcome to the April 2024 issue of the Lifetime Surveillance of Astronaut Health (LSAH) Newsletter. In this issue, we celebrate LSAH lead, Dr. Mary Wear’s retirement, inform you of the Apollo Records Synthesis Project (ARSP), and recap information shared at the 2024 Human Research Program (HRP) Investigators’ Workshop (IWS) by our LSAH Epidemiologists and NASA HRP team.

Anna C. Morgenthaler-Cejka↗
NASA NTRSDate not supplied

Optimal Communication Topology Determination and Sensor Selection for Independent Airspace Surveillance

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

Distributed sensing↗
NASA NTRS2024

The Lifetime Surveillance of Astronaut Health Newsletter

Welcome to the October 2024 issue of the Lifetime Surveillance of Astronaut Health (LSAH) Newsletter. In this issue, we will introduce you to the outgoing LSAH/LSDA lead, Mary Van Baalen, PhD; share with you the history of the NASA Electronic Medical Record (EMR) Project, as well as provide you with additional information on the consent to re-use your Astronaut data and the application of the TREAT Act. Be sure to check out the Clinic Corner, HRP Corner, the Publications Corner, and a special Formers Corner where we share Travel Tips for your LSAH Exam travels!

Ronnie Rafanan↗
NASA NTRSDate not supplied

Sensing Small Uncrewed Aerial Vehicles with Distributed Radars for Advanced Air Mobility Surveillance

In the context of Advanced and Urban Air Mobility major attention is being reserved to the development of sensing strategies for small Uncrewed Aerial Vehicles (sUAVs) to enable their safe operations in and around urban areas. Such strategies should rely on non-cooperative distributed sensors to strengthen the surveillance solution towards the unreliability of Global Navigation Satellite System (GNSS) positioning information, which is typical for low-altitude-flying platforms in urban regions, and increase the monitored airspace volume. To this aim, this paper proposes a fusion solution for a network of distributed ground-based radars, which can be exploited to not only increase the coverage over large airspace volumes but also improve the overall detectability and traceability of sUAVs by leveraging on multiple views over the same area. The solution exploits a centralized fusion scheme in which measurements collected by each radar are shared with a Fusion Center where Kalman Filtering is exploited to build a unique, fused track. Tests conducted on experimental data collected using two sUAVs as flying targets and three distributed radars showed that the proposed solution can produce an increase in coverage from about 20 % (single radar configuration) to about 80 % of the targets’ flight path, as well as a finer accuracy yielding meter and meter-per-second root mean square error values on position and velocity components.

Federica Vitiello↗
NASA NTRSDate not supplied

Optimal Communication Topology Construction and Sensor Selection for Independent Airspace Surveillance

The paper presents an approach with no estimation feedback to sensors selection and communication network topology computation for independent airspace surveillance with maximum outcome and minimum cost using ground based distributed sensing, computing and communication network infrastructure. The selection criteria includes maximum airspace coverage with minimal resources, minimum communication time and power consumption while guaranteeing the system observability and providing in-time high quality information to both stationary and mobile users. The developed algorithms use multi-objective optimization strategy taking into account trade-offs between conflicting objectives and are implemented using off-the-shelf computational tools. The algorithms are validated in a desktop simulation environment using synthetic sensors data generated for a simulated multi-vehicle flight scenario in the selected regional airspace and parameters of a notional wireless communication network.

Distributed sensing↗