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NASA NTRS2019

Remote ID for Rapid Assessment of Flight and Vehicle Information

The ability to rapidly identify UAS in the field has emerged as a critical need for the integration of small UASs into the national airspace and counter-uas operations. This paper proposes an architecture for rapid retrieval of UAS information leveraging NASA's current Unmanned Aircraft System (UAS) Traffic Management (UTM) system. The proposed architecture utilizes UTM components: FIMS (Flight Information Management System), USS (UAS Service Supplier), and vehicle registration and model database in order to provide assessment of the UAS reported in the field including the ability to distinguish between participating and non- participating UTM actors. Detailed system descriptions are provided and preliminary results from field tests conducted during UTM TCL (Technical Capability Level) 3 are discussed. It is found that 94% of the remote ID look-ups were successful. The average time of a look-up is found to be 1.2 seconds. Failure cases are examined and recommendations on next steps to advance UAS remote identification are provided.

Ishihara, Abraham K.↗

NASA NTRS2019

Scenario Complexity for Unmanned Aircraft System Traffic

UTM↗

NASA NTRS2019

Scenario Complexity for Unmanned Aircraft System Traffic

This work introduces an approach to estimate the complexity of a low-altitude air traffic scenario involving multiple UASs using mathematical programming. Given a set of multi-point UAS flight trajectories, vehicle dynamics, and a conflict resolution algorithm, an abstract model is developed such that it can be solved quickly using a mathematical programming optimization software without running high-fidelity simulations that can be computationally expensive and may not suit real-time apA quick and accurate assessment of complexity for a given traffic scenario can help plan and schedule flights to alleviate traffic bottleneck and mitigate operation risks, especially for unmanned aerial system traffic management where high traffic density or complexity is expected. This work introduces a traffic scenario complexity metric that was constructed based on the number of potential conflicts weighted by the conflict resolution cost associated. The cost associated with a conflict is calculated based on the corresponding conflict resolution maneuvers. To obtain the conflict resolution maneuvers, a MILP-based optimization was formulated with the vehicle model and conflict management parameters incorporated. To evaluate the complexity metrics, an approach of using measurements from high-fidelity simulations was proposed. The scenario complexity measurements for 920 random-generated scenarios were obtained through high-fidelity simulations and treated as the ground truth. Two statistics methods: Pearson and Alternative Conditional Expectations were applied for analysis. The results showed that the number of flights has low correlation with the scenario complexity according to the correlation coefficients calculated by both methods. The Alternative Conditional Expectations method shows that the proposed scenario complexity metric has better correlation with the ground truth than the number of potential conflicts.plications. In the abstract model, each vehicle is represented by a time-varied vector associated with position, speed, and heading information. The total extra distance that aircraft need to divert from their original routes to avoid collisions is computed and used to setup a quadratic programming formula. The metrics including the number of conflicts and extra distances travelled by all vehicles are then utilized to estimate the complexity of a given UAS flight scenario. Results and verification against high-fidelity simulations will be provided in the final draft.

traffic complexity↗

NASA NTRS2019

Scalable Traffic Management for Emergency Response Operations (STEReO)

The Scalable Traffic Management for Emergency Response Operations (STEReO) project aims to apply various NASA technologies, such as Unmanned Aircraft System (UAS) Traffic Management (UTM) services, onboard-vehicle autonomy, novel approaches to communications and connectivity, and remote/virtual collaboration interfaces to current-day emergency response efforts to natural disasters. Today's emergency response efforts are based on long-standing procedures that are manaul in nature, and could benefit from modernization. In particular, the use of UAS vehicles is limited, primarily due to concerns surrounding dangerous interactions between manned/unmanned operations. STEReO hopes to introduce data exchanges that improve shared situation awareness, reduce manual coordination procedures, enable scalable and high-density air operations, collectivley bringing a positive impact to the incident response. When successful, STEReO technologies will improve efficiency and timeliness of the response and recovery phases of a disaster, resulting in substantial reductions to community harm, and will also accelerate NASAâ€™s development of high-density resilient operations, benefitting other projects relying on increasing levels of autonomy and connectivity. The prepared material provides an overview of the STEReO project, for presentation at the 2019 Convergent Aeronautics Solution (CAS) Showcase event. The CAS showcase brings together all of the current CAS execution activities, highlighting NASA's high-risk investments in aeronautics research.

Mercer, Joey↗

NASA NTRS2017

Small Propeller and Rotor Testing Capabilities of the NASA Langley Low Speed Aeroacoustic Wind Tunnel

The Low Speed Aeroacoustic Wind Tunnel (LSAWT) at NASA Langley Research Center has recently undergone a configuration change. This change incorporates an inlet nozzle extension meant to serve the dual purposes of achieving lower free-stream velocities as well as a larger core flow region. The LSAWT, part of the NASA Langley Jet Noise Laboratory, had historically been utilized to simulate realistic forward flight conditions of commercial and military aircraft engines in an anechoic environment. The facility was modified starting in 2016 in order to expand its capabilities for the aerodynamic and acoustic testing of small propeller and unmanned aircraft system (UAS) rotor configurations. This paper describes the modifications made to the facility, its current aerodynamic and acoustic capabilities, the propeller and UAS rotor-vehicle configurations to be tested, and some preliminary predictions and experimental data for isolated propeller and UAS rotor con figurations, respectively. Isolated propeller simulations have been performed spanning a range of advance ratios to identify the theoretical propeller operational limits of the LSAWT. Performance and acoustic measurements of an isolated UAS rotor in hover conditions are found to compare favorably with previously measured data in an anechoic chamber and blade element-based acoustic predictions.

Zawodny, Nikolas S.↗

NASA NTRS2020

Fit2Fly: A Proof of Concept for Testing the Commercial Feasibility of Unmanned Aerial System Operations

As autonomous Unmanned Aerial Systems (UAS) become more prevalent, improvements in airworthiness assessments, data security, establishing vehicle trust, and more will become necessary to make fleet operations of these systems routine. Currently, these are verified for every UAS vehicle through a time-intensive manual inspection performed by human individuals. This process becomes infeasible when introduced into large-scale operations, so the Fit2Fly project is attempting to address these concerns. Fit2Fly is a multi-year project with a large scope, so we chose to narrow our focus to building a proof-of-concept feasibility simulation in tandem with physical UAS demonstration. This work resulted in a software simulation capable of running asynchronous commercial operations with persistent data modeling in coordination with several autonomous drones using integrated radio and GPS configurations.

Ryan Bonk↗

NASA NTRS2017

Considerations for an Integrated UAS CNS Architecture

The National Aeronautics and Space Administration (NASA) Glenn Research Center (GRC) is investigating revolutionary and advanced universal, reliable, always available, cyber secure and affordable Communication, Navigation, Surveillance (CNS) options for all altitudes of UAS operations. In Spring 2015, NASA issued a Call for Proposals under NASA Research Announcements (NRA) NNH15ZEA001N, Amendment 7 Subtopic 2.4. Boeing was selected to conduct a study with the objective to determine the most promising candidate technologies for Unmanned Air Systems (UAS) air-to-air and air-to-ground data exchange and analyze their suitability in a post-NextGen NAS environment. The overall objectives are to develop UAS CNS requirements and then develop architectures that satisfy the requirements for UAS in both controlled and uncontrolled air space. This contract is funded under NASAs Aeronautics Research Mission Directorates (ARMD) Aviation Operations and Safety Program (AOSP) Safe Autonomous Systems Operations (SASO) project and proposes technologies for the Unmanned Air Systems Traffic Management (UTM) service.There is a need for accommodating large-scale populations of Unmanned Air Systems (UAS) in the national air space. Scale obviously impacts capacity planning for Communication, Navitation, and Surveillance (CNS) technologies. For example, can wireless communications data links provide the necessary capacity for accommodating millions of small UASs (sUAS) nationwide? Does the communications network provide sufficient Internet Protocol (IP) address space to allow air traffic control to securely address both UAS teams as a whole as well as individual UAS within each team? Can navigation and surveillance approaches assure safe route planning and safe separation of vehicles even in crowded skies?Our objective is to identify revolutionary and advanced CNS alternatives supporting UASs operating at all altitudes and in all airspace while accurately navigating in the absence of navigational aids. These CNS alternatives must be reliable, redundant, always available, cyber-secure, and affordable for all types of vehicles including small UAS to large transport category aircraft. The approach will identify CNS technology candidates that can meet the needs of the range of UAS missions to specific air traffic management applications where they will be most beneficial and cost effective.

Templin, Fred L.↗

NASA NTRS2017

Considerations for an Integrated UAS CNS Architecture

The National Aeronautics and Space Administration (NASA) Glenn Research Center (GRC) is investigating revolutionary and advanced universal, reliable, always available, cyber secure and affordable Communication, Navigation, Surveillance (CNS) options for all altitudes of UAS operations. In Spring 2015, NASA issued a Call for Proposals under NASA Research Announcements (NRA) NNH15ZEA001N, Amendment 7 Subtopic 2.4. Boeing was selected to conduct a study with the objective to determine the most promising candidate technologies for Unmanned Air Systems (UAS) air-to-air and air-to-ground data exchange and analyze their suitability in a post-NextGen NAS environment. The overall objectives are to develop UAS CNS requirements and then develop architectures that satisfy the requirements for UAS in both controlled and uncontrolled air space. This contract is funded under NASAs Aeronautics Research Mission Directorates (ARMD) Aviation Operations and Safety Program (AOSP) Safe Autonomous Systems Operations (SASO) project and proposes technologies for the Unmanned Air Systems Traffic Management (UTM) service.There is a need for accommodating large-scale populations of Unmanned Air Systems (UAS) in the national air space. Scale obviously impacts capacity planning for Communication, Navigation, and Surveillance (CNS) technologies. For example, can wireless communications data links provide the necessary capacity for accommodating millions of small UASs (sUAS) nationwide? Does the communications network provide sufficient Internet Protocol (IP) address space to allow air traffic control to securely address both UAS teams as a whole as well as individual UAS within each team? Can navigation and surveillance approaches assure safe route planning and safe separation of vehicles even in crowded skies?Our objective is to identify revolutionary and advanced CNS alternatives supporting UASs operating at all altitudes and in all airspace while accurately navigating in the absence of navigational aids. These CNS alternatives must be reliable, redundant, always available, cyber-secure, and affordable for all types of vehicles including small UAS to large transport category aircraft. The approach will identify CNS technology candidates that can meet the needs of the range of UAS missions to specific air traffic management applications where they will be most beneficial and cost effective.

Templin, Fred L.↗

NASA NTRSDate not supplied

Intelligent Change Detection System: Autonomous Intelligent Machine Agent Model Development

NASA’s significant role in facilitating the harmonious integration of unmanned aircraft systems (UAS), with other aerial vehicles operating in the National Airspace System (NAS), has revealed a need for more advanced technological tools than are being utilized currently. This technology would lend itself to significantly assisting Direct-Action Aviation Personnel (DAAP) with the ingress and egress of UAS operations within the NAS. Providing research findings that would reduce technical barriers, associated with UAS-NAS integration, has been a persistent effort by both NASA and the FAA. One such research effort, pursued by NASA’s Transformative Tools and Technologies – Revolutionary Aviation Mobility (T3-RAM) project, is the development of an autonomous intelligent machine (AIM) agent that would aid DAAP functioning as implemented in remote ground control stations (RGCS). This evolution of the “human-machine” symbiosis, within the aviation environment, is necessary for many reasons. For example, there are projections of large increases to the 864,000 registered UAS and 45,000 aviation operations taking place in the NAS each day. With a data output range from 1 to 20 terabytes per flight or each aerial vehicle, which is projected to have proportional rate increase to that of registered UASs. It is evident, that due to the projected increase of UASs and their generated data, the human-agent’s data managing capabilities will be quickly overwhelmed by the enormous amounts of data emanating in the NAS. The research efforts presented in this paper puts forward results from the development, assessment, and verification of a previously conceptualized AIM-Agent that combats actionable-data (information) errors resulting from the visual perception phenomenon known as “change blindness” (CB). CB has been identified as one of the main culprits of information erroring encountered within the ground control station operator (GCSO) community.

Change Blindness↗

NASA NTRSDate not supplied

Acoustic and Performance Measurements Obtained in the NASA Langley Small Hover Anechoic Chamber

The emergence of small Unmanned Aircraft Systems (UAS) and Advanced Air Mobility (AAM) vehicles has motivated the need to acoustically characterize the rotors found on these vehicle platforms. Hover chamber tests of small rotors are beneficial in assessing the noise impact of UAS, and potentially larger AAM vehicles. Various experiments have been conducted in the NASA Langley Small Hover Anechoic Chamber (SHAC), formerly known as the Small Anechoic Jet Facility (SAJF), in order to investigate the noise and performance of small rotors. One of these tests was that of an “ideally twisted rotor”, which was designed in order to simplify the theoretical rotor inflow for a target thrust condition in hover. This rotor was fabricated using state-of-the-art rapid prototyping and tested in the SHAC. Aerodynamic load and acoustic data were acquired across a range of rotation rates and rotor collective settings. Both tonal and broadband components were identified in the acoustic data, with broadband noise being a prominent contributor to the overall rotor system noise.

Nicole Pettingill↗

NASA NTRS2022

Overview of NASA’s Extensible Traffic Management (xTM) Research

NASA’s Unmanned Aircraft Systems (UAS) Traffic Management (UTM) project introduced a new Air Traffic Management (ATM) architecture that utilizes industry’s ability to supply industry-developed, third-party services that work complementarily with the FAA-provided Air Traffic Service (ATS) to exchange relevant air vehicle information among the UAS operations and between the UTM and the conventional ATM system. The UTM architecture was used to successfully demonstrate the feasibility of safe, efficient, and scalable small UAS operations in low altitudes below 400 feet above ground level. Following the success and adoption of UTM architecture, the foundational UTM requirements and core properties were generalized to become Extensible Traffic Management (xTM) requirements to support operations of new entrants beyond small UAS, such as operations in high altitudes over 60,000 feet, designated as upper Class E in the United States National Airspace System (NAS). In this paper, the generalization of UTM to xTM and NASA’s approach for developing an xTM system for upper Class E Traffic Management (ETM) are discussed. The paper also discusses the planned research to examine the potential xTM-Air Traffic Control (ATC) interactions across multiple xTM systems and identify common coordination procedures, ATC roles/responsibilities, and data exchange requirements. This work is one of the steps for improving interoperability between the xTM systems and ATS, which is critical for safe and efficient sharing of the airspace among the new entrants served by the xTM systems and conventional ATS-serviced operations.

air traffic management↗

NASA NTRSDate not supplied

Overview of NASA’s Extensible Traffic Management (xTM) Work

air traffic management↗

NASA NTRS2016

Systems and Methods for Collaboratively Controlling at Least One Aircraft

An unmanned vehicle management system includes an unmanned aircraft system (UAS) control station controlling one or more unmanned vehicles (UV), a collaborative routing system, and a communication network connecting the UAS and the collaborative routing system. The collaborative routing system being configured to receive flight parameters from an operator of the UAS control station and, based on the received flight parameters, automatically present the UAS control station with flight plan options to enable the operator to operate the UV in a defined airspace.

Estkowski, Regina I.↗

NASA NTRS2011

The Proposed Use of Unmanned Aerial System Surrogate Research Aircraft for National Airspace System Integration Research

Research is needed to determine what procedures, aircraft sensors and other systems will be required to allow Unmanned Aerial Systems (UAS) to safely operate with manned aircraft in the National Airspace System (NAS). This paper explores the use of Unmanned Aerial System (UAS) Surrogate research aircraft to serve as platforms for UAS systems research, development, and flight testing. These aircraft would be manned with safety pilots and researchers that would allow for flight operations almost anywhere in the NAS without the need for a Federal Aviation Administration (FAA) Certificate of Authorization (COA). With pilot override capability, these UAS Surrogate aircraft would be controlled from ground stations like true UAS s. It would be possible to file and fly these UAS Surrogate aircraft in the NAS with normal traffic and they would be better platforms for real world UAS research and development over existing vehicles flying in restricted ranges or other sterilized airspace. These UAS surrogate aircraft could be outfitted with research systems as required such as computers, state sensors, video recording, data acquisition, data link, telemetry, instrumentation, and Automatic Dependent Surveillance-Broadcast (ADS-B). These surrogate aircraft could also be linked to onboard or ground based simulation facilities to further extend UAS research capabilities. Potential areas for UAS Surrogate research include the development, flight test and evaluation of sensors to aide in the process of air traffic "see-and-avoid". These and other sensors could be evaluated in real-time and compared with onboard human evaluation pilots. This paper examines the feasibility of using UAS Surrogate research aircraft as test platforms for a variety of UAS related research.

Howell, Charles T., III↗

NASA NTRSDate not supplied

Experiments for Securing Air Traffic Against Cyber-Physical System Attacks

This presentation describes experiments conducted with single board computers to investigate methods for creating trust for enabling the development of cyber-resilient air transportation systems. Methods included secure communication to prevent unauthorized access to data, consistency of data obtained via sensors and by processing, and built-in safeguards to prevent mission failure. The motivation for this work are the following. The future air transportation system needs to ensure availability, integrity, confidentiality and safety of operations. Safety of vehicles and operations is paramount for successful integration of Urban Air Mobility (UAM), Unmanned Aerial Systems (UAS), supersonic aircraft and launch vehicles with conventional aviation operations in the National Airspace System. Security is becoming critical because the sensors, networks and computers are far more vulnerable to bad actors than their mechanical or human predecessors. The goal therefore is to design and develop cyber-resilient systems that continue to function even in degraded states. The main findings are (1) off-the-shelf hardware can support development of cyber-resilient onboard flight computers and (2) trust in system design and implementation can be accomplished by integrating layers in depth (detail) and in breadth (scope).

cyber-resilient autonomy, trust, secure communicat↗

NASA NTRSDate not supplied

Design Considerations of an Ascent Abort Monitor Algorithm for Use During Service Module Aborts

In support of human rating the Artemis missions, NASA's Orion program requires continuous abort coverage from liftoff through mission destination. During a portion of the ascent trajectory, the currently achievable abort mode is determined by an Orion algorithm using the onboard navigated vehicle state. This ascent abort monitor determines achievability for Orion's Mode 2 abort, Untargeted Abort Splashdown (UAS), by propagating the current vehicle state through ascent abort events to determine sufficient timing to perform the abort and to a ballistic touchdown point to approximate landing location relative to prescribed keep out boundaries. The algorithm was updated for Artemis 2 to allow the capability to limit loads for the majority of ascent. Performance of the algorithm has been demonstrated and verified through dispersed trajectory analysis with emulated flight software, unit testing, and hardware in the loop testing.

Esteban Guzman↗

NASA NTRS2015

Enabling UAS Research at the NASA EAV Laboratory

The Exploration Aerial Vehicles (EAV) Laboratory at NASA Ames Research Center leads research into intelligent autonomy and advanced control systems, bridging the gap between simulation and full-scale technology through flight test experimentation on unmanned sub-scale test vehicles.

UTM↗

NASA NTRS2019

Modular Unmanned Aerial System with Multi-Mode Propulsion

A modular Unmanned Aerial System (UAS) includes an Unmanned Aerial Vehicle (UAV) parent module and UAV child modules. A main wing extends from a respective fuselage of the modules. The UAS includes docking mechanisms coupled to wingtips of the main wings. The child modules dock with the wingtips of the parent or an adjacent child module. Docking forms a linked-flight configuration, with undocking and separation from the parent or adjacent child module achieving an independent-flight configuration. The modules have booms arranged transverse to the main wings and parallel to the longitudinal axis, as well as front and rear rotors/propellers. The front and rear propellers have axes of rotation that are normal to a plane of the longitudinal axis in a vertical takeoff and landing (VTOL) configuration, with the axis of rotation of the rear propellers parallel to the longitudinal axis in a forward-flight configuration.

Patterson, Michael D.↗