Results for “NaS” — Page 32

NASA NTRSDate not supplied

TPSAS-NF1676L-14989-DND

Objective 1: Develop a research test-bed and database to provide data/proof of concept for Ground Control Station (GCS) NAS operations. Objective 2: Coordinate with standards organizations to develop human factors guidelines for GCS operation in the NAS. Interest in UAS routine access: 1) Federal government – DHS, NOAA, Commerce, Interior, FBI, DOT 2) Military 3) Local governments – police, fire, port authority 4) Commercial – utilities, news agencies, private security, photographers, hobbyists

Anna Trujillo↗

NASA NTRSDate not supplied

Unsupervised Anomaly Detection in High-Dimensional Flight Data Using Convolutional Variational Auto-Encoder

The modern National Airspace System (NAS) is an extremely safe system. The industry has experienced a steady decrease in fatalities over the years. This can be contributed to both improved flight critical systems with redundant hardware and software protections as well as an increased focus on active monitoring and response to real time and historically identified vulnerabilities by implementing more resilient procedures and protocols. The main practice for identifying vulnerabilities in operations leverages domain expertise using knowledge about how the system should behave with the expected tolerances to known safety margins. This approach works well when the system has a well-defined operating condition. However, the operations in the NAS can be highly complex with various nuances that render it difficult to clearly pre-define all known safety vulnerabilities. With the advancement of data science and machine learning techniques, the potential to automatically identify emerging vulnerabilities in the observed operations has become more practical in recent years. The state-of-the-art anomaly detection approaches in aerospace data usually rely on supervised or semi-supervised learning. However, in many real-world problems such as flight safety creating labels for the data requires huge amount of efforts and is largely expensive. As a result, in this article, we develop a Convolutional Variational Auto-Encoder (CVAE), an unsupervised learning approach for anomaly detection in high-dimensional heterogeneous time-series data. We validate performance of CVAE compared to the state-of-the-art supervised learning approach (as an upper bound) as well as an supervised clustering based on K-Means (as a lower bound) on Yahoo!'s benchmark time series anomaly detection data. Finally, we showcase performance of CVAE on a case study of identifying anomalies in the first 60 seconds of commercial flights' take-offs using Flight Operational Quality Assurance (FOQA) data.

Milad Memarzadeh↗

NASA NTRS2020

NASA Air Traffic Management – eXploration (ATM-X) Insight Assessment

The focus of this final Air Traffic Management – eXploration (ATM-X) Insight Assessment (IA) report is to summarize key findings, lessons learned, gaps, and shortfalls from 2018 to 2019 National Aeronautics and Space Administration (NASA) ATM-X research and to share the outcomes from National Airspace System (NAS) stakeholder discussions with the broader community. This report was generated from a comprehensive review of 25 NASA ATM-X research papers and augmented by interviews with 23 NASA researchers as well as three virtual seminars discussing the project findings and priorities with 47 NAS stakeholders. While these papers cover a wide range of relevant topics, they only represent a small portion of the vast amount of ongoing research in this rapidly evolving area by industry, academia, and other agencies. The research summary described here could be further refined and expanded by reviewing additional studies.

air transportation↗

NASA NTRSDate not supplied

Automated Management of Small Unmanned Aircraft System Communications and Navigation Contingency

The number of small Unmanned Aircraft System (sUAS) operating in the low-altitude of the National Airspace System (NAS) has been rapidly increasing in the past few years and this number is expected to grow in the future. However, aside from a few special cases, all sUAS must fly within visual line-of-sight (VLOS) of their operators and this limitation is blocking highly anticipated beyond visual line-of-sight (BVLOS) sUAS applications such as package delivery from practice. To enable routine low-altitude BVLOS operations, there needs to be a traffic management ecosystem that complements the FAA’s Air Traffic Management (ATM) system, which does not provide air traffic services under 400 feet above ground level (AGL). NASA has been pioneering research and development of this ecosystem under UAS Traffic Management (UTM) project since 2015 in a series of Technical Capability Levels (TCL) activities that are increasingly complex. In TCL1, completed in 2015, visual line-of-sight operations such as agriculture, firefighting, and infrastructure monitoring were addressed with a focus on geofencing and operations scheduling. Technologies and requirements needed for BVLOS operations in sparsely populated areas were examined in TCL2 in 2016, and those for operations over moderately populated areas in TCL3 in 2017 and 2018. TCL4 is building on the earlier TCLs and focuses on technologies and requirements for operations in higher-density urban areas for tasks such as newsgathering and package delivery and for managing large-scale contingencies. To coordinate and facilitate the incremental implementation of the UTM ecosystem in the NAS, a Research Transition Team (RTT) has been formed between the FAA, NASA, and industry. The RTT is divided into four subgroups, concept and use case development, data exchange and information architecture, sense and avoid, and communications and navigation (C&N). This paper focuses on C&N subgroup activities, in particular about the development of automated sUAS communications and navigation contingency management. The goal of this development is to prepare sUAS to display predictable behavior while handling C&N off-nominal events. It is expected that the adoption of the presented automated contingency management by the sUAS community will accommodate and inform rulemaking towards governing low-altitude BVLOS operations.

Unmanned Aviation System (UAS) Traffic Management↗

NASA NTRSDate not supplied

Automated Management of Small Unmanned Aircraft System (UAS) Communications and Navigation Contingency

The number of small Unmanned Aircraft System (sUAS) operating in the low-altitude of the National Airspace System (NAS) has been rapidly increasing in the past few years and this number is expected to grow in the future. However, aside from a few special cases, all sUAS must fly within visual line-of-sight (VLOS) of their operators and this limitation is blocking highly anticipated beyond visual line-of-sight (BVLOS) sUAS applications such as package delivery from practice. To enable routine low-altitude BVLOS operations, there needs to be a traffic management ecosystem that complements the FAA’s Air Traffic Management (ATM) system, which does not provide air traffic services under 400 feet above ground level (AGL). NASA has been pioneering research and development of this ecosystem under UAS Traffic Management (UTM) project since 2015 in a series of Technical Capability Levels (TCL) activities that are increasingly complex. In TCL1, completed in 2015, visual line-of-sight operations such as agriculture, firefighting, and infrastructure monitoring were addressed with a focus on geofencing and operations scheduling. Technologies and requirements needed for BVLOS operations in sparsely populated areas were examined in TCL2 in 2016, and those for operations over moderately populated areas in TCL3 in 2017 and 2018. TCL4 is building on the earlier TCLs and focuses on technologies and requirements for operations in higher-density urban areas for tasks such as newsgathering and package delivery and for managing large-scale contingencies. To coordinate and facilitate the incremental implementation of the UTM ecosystem in the NAS, a Research Transition Team (RTT) has been formed between the FAA, NASA, and industry. The RTT is divided into four subgroups, concept and use case development, data exchange and information architecture, sense and avoid, and communications and navigation (C&N). This paper focuses on C&N subgroup activities, in particular about the development of automated sUAS communications and navigation contingency management. The goal of this development is to prepare sUAS to display predictable behavior while handling C&N off-nominal events. It is expected that the adoption of the presented automated contingency management by the sUAS community will accommodate and inform rulemaking towards governing low-altitude BVLOS operations.

Unmanned Aviation Systems (UAS) Traffic Management↗

NASA NTRSDate not supplied

Achieving Equilibrium for Dense, Integrated, Vehicle Navigation

Drone usage has proliferated in recent years with many applications that have market-changing potential. Applications that include parcel delivery, wildlife protection, precision farming, law enforcement, and industrial inspection, just to name a few. In this paper, the term drone is used to mean both Unmanned Aerial Vehicle and small Unmanned Aircraft System vehicles. Flight infrastructure can currently only support a few thousand aircraft flying over the United States National Airspace System (NAS) at any given time. A delay atone airport sends ripple effects through the system, causing more delays and missed connections. Once regulations and safety policies are put in place to allow for the widespread use of unmanned drones, the number of aircraft in the NAS is expected to skyrocket to millions, potentially congesting the airspace resulting in possible separation violations. In air traffic control, separation is the concept of keeping an “ownship” aircraft outside a minimum distance from “intruder” aircraft to reduce the risk of the aircraft colliding, as well as preventing accidents due to secondary factors, such as wake turbulence. Maintaining proper separation is a safety critical property for drones in the airspace. This paper addresses separation in time and in distance for high volume corridors (en-route) and lanes(on ground). The requirements and necessary conditions for maintaining proper separation and reaching maximum throughput for a given corridor/lane are addressed assuming unidirectional corridors/lanes where an aircraft arrives from one side and departs from the opposite side. Simulation results are presented that show the presented solution guarantees a set of drones to reach the equilibrium state by adjusting their speed based on their distance to the aircraft in front of them. The equilibrium state is defined as a state when a set of n aircraft moving at a relatively constant speed and uniform spacing from each other in a congested system. A congested system is defined as a state when the aircraft cannot move at their maximum allowed speed. Unlike existing centralized and pre-planned approaches, the proposed solution is fully distributed and enables autonomous aircraft to decide to adjust their speed and distance with respect to the preceding aircraft, dynamically. Simulation results are presented that assess the feasibility of the approach using a large number of drones and evaluate the scalability of the proposed solution.

Mahyar R. Malekpour↗

NASA NTRS2022

Automatic Dependent Surveillance Rebroadcast Technology Analysis

In lieu of eminent future air traffic in the next 10-30 years for the United States North American air space, also known as the National Air Space (NAS), many technologies are being investigated for enhancing Air Traffic Control (ATC). This increase in air traffic includes the increase of manned and unmanned aerial vehicles (AVs) of all sizes, at all altitudes, and varying average speeds. The technology of Automatic Dependent Surveillance Rebroadcasting (ADS-R) combines the existing technology used with manned AVs in the NAS called, Automatic Dependent Surveillance Broadcast (ADS-B), and an ‘physical layer’ digital communications technology called flooding. Flooding allows the retransmission of the existing ADS-B AV flight information to ‘in the area’ adjacent AVs, where in a few retransmission epochs will have communicated to all AVs in the designated geographic area.

Konstantin J. Matheou↗

NASA NTRSDate not supplied

Investigation and Evaluation of Advanced Spectrum Management Concepts for Aeronautical Communications

With the emergence of new aerial vehicles into the airspace and the continued growth of aviation operations, there will be an increasing demand for voice and data communications within the National Airspace System (NAS). The continued use of existing VHF and UHF frequency allocations is not a sustainable approach, and as a result, a new spectrum management solution is required to support future mission needs. The proposed spectrum management concepts leverage modern advancements such as artificial intelligence (AI) and big data to dynamically optimize the spectrum utilization based on the predicted communications demand throughout the airspace. This technical investigation considers both air-ground and air-air communications networks, and can be applied to both existing applications such as the air traffic control (ATC) system, as well as future applications, such as the emerging Advanced Air Mobility (AAM). To support the evaluation of the proposed concepts and technologies, a modeling and simulation capability is currently under development and will continue to evolve to support new and advanced airspace applications. It is anticipated that this proposed spectrum concept will better serve the spectrum needs of future NAS applications.

Eric J Knoblock↗

NASA NTRSDate not supplied

Investigation and Evaluation of Advanced Spectrum Management Concepts for Aeronautical Communications

With the emergence of new aerial vehicles into the airspace and the continued growth of aviation operations, there will be an increasing demand for voice and data communications within the National Airspace System (NAS). The continued use of existing VHF and UHF frequency allocations is not a sustainable approach, and as a result, a new spectrum management solution is required to support future mission needs. The proposed spectrum management concepts leverage modern advancements such as artificial intelligence (AI) and big data to dynamically optimize the spectrum utilization based on the predicted communications demand throughout the airspace. This technical investigation considers both air-ground and air-air communications networks, and can be applied to both existing applications such as the air traffic control (ATC) system, as well as future applications, such as the emerging Advanced Air Mobility (AAM). To support the evaluation of the proposed concepts and technologies, a modeling and simulation capability is currently under development and will continue to evolve to support new and advanced airspace applications. It is anticipated that this proposed spectrum concept will better serve the spectrum needs of future NAS applications.

Eric J Knoblock↗

NASA NTRS2021

GA-ASI Final Report and Program Wrap-up for NASA System Integration and Operationalization (SIO)

The NASA SIO demonstration flight of April 3, 2020 represents a successful culmination of 18 months of coordinated effort between GA-ASI, NASA, the FAA, Collins Aerospace, and Honeywell Aerospace to operate a Medium Altitude, Long Endurance (MALE) Unmanned Aircraft System (UAS) safely in the National Airspace System (NAS) using industry leading prototype technologies. The GA-ASI team consisted of technical experts, program managers, engineers, mechanics, flight technicians, flight crews, and numerous other subject matter experts. This final report describes the most significant and potentially impactful aspects of the planning, integration, test, and flight aspects of this effort. GA-ASI successfully integrated the key technologies needed for UAS to fly in the NAS onto our prototype SkyGuardian UAS, which was designed to meet the most stringent airworthiness standards applicable to an aircraft of its size category. A proven Detect and Avoid (DAA) system, developed by GA-ASI and utilizing Honeywell Aerospace technology was integrated onto SkyGuardian for the first time, along with datalink radios from Collins Aerospace that meet the new civil standard for Control and Non-Payload Communication (CNPC) links. GA-ASI also obtained approvals from the FAA and FCC to operate the reconfigured UAS. The SIO demonstration flight represented a commercial aerial surveying operation conducted at medium altitude (>10,000ft above mean sea level). The aircraft’s onboard sensors were used to capture photographic, infrared and radar imagery of public and commercial infrastructure and land, and to subsequently produce the types of data products that would provide business value to potential customers. These survey services would supplement or replace services currently provided by manned airplanes and helicopters, small drones or satellites. A “virtual” mission was also planned, to show what additional survey data could have been captured during the flight if additional sensors had been installed on the aircraft’s external hardpoints. This revision of the final report focuses on information of value to the wider UAS community, and avoids propriety data to facilitate broad dissemination. It also includes a description of GA-ASI’s engagement with the FAA following the SIO flight, which led to the award of an updated Special Airworthiness Certificate in the Experimental Category (SAC-EC) and a Certificate of Waiver or Authorization (COA) allowing operation of the SkyGuardian UAS using its DAA system to satisfy right-of-way rules, instead of a chase plane. The associated operational limitations are described to illustrate the further steps that would be needed to remove those limitations for unhindered commercial operations.

Flight demonstration↗

NASA NTRSDate not supplied

Establishing the Framework for e-VTOL Flight Mission Scenario Development for Urban Air Mobility Research using Cognitive Task Analysis

This paper focuses on applying specific protocol aspects of Cognitive Task Analysis (CTA) methods to formulate non-routine flight mission use-case scenarios in support of a potential research study at the National Aeronautics and Space Administration (NASA) Langley Research Center under the Air Traffic Management – eXploration (ATM-X) Urban Air Mobility (UAM) sub-project. The objective of use-case scenarios is to provide a hypothetical situation to elicit expert knowledge and feedback in a specific subject matter area. Use-case scenarios in the field of aviation, including UAM, can help to support the safe integration of these vehicles into the National Airspace System (NAS) through the examination of airspace procedures during non-routine events. Inherent in this type of research is the need to study in-flight non-routine scenarios that the UAM vehicle could encounter. Situations categorized as non-routine events are any events that occur outside of the original flight plan such as a mechanical malfunction or other in-flight emergency requiring special procedures, which can include diversions to a specified, or non-specified, emergency landing area. In specific instances, some non-routine events could be considered as “routine” during in-flight operations, such as the need to perform a go-around due to a balked landing. As the rate of technological expansion surrounding UAM grows rapidly in modern aviation, so does the need for research that focuses on the safe integration of these vehicles including research with a focus on the methods and development of airspace operational procedures. Research rooted in CTA methods provides a framework for developing use-case scenarios appropriate for environments where mental demands are substantial. Substantial mental demands exist while operating in the NAS for pilots, airline dispatchers, and air traffic controllers among many others. With the focus on UAM in mind, it is critical to frame a baseline use-case scenario using information as it pertains to current-day airspace operations. According to Dr. Robert R. Hoffman’s “Protocols for Cognitive Task Analysis,” one of the first steps to applying CTA methods to research is the concept of “bootstrapping” in which the researcher(s) familiarize themselves with the domain that is being studied. To formulate the non-routine flight mission use-case scenarios for the purpose of this potential NASA ATM-X UAM research study, and to inform the baseline use-case scenario, the practice of bootstrapping was utilized to acquire knowledge of current-day airspace procedures.

Heidi S Glaudel↗

NASA NTRSDate not supplied

Visualizing UPSP Data with Python

The Unsteady Pressure-Sensitive Paint (uPSP) projects uses Pressure-Sensitive paint applied over aerospace models during wind tunnel testing to collect pressure data with high spatial and temporal resolution in order to inform unsteady aerodynamics studies. For each of the 800+ experimental runs, four cameras generate up to 50 GB of video data, which must then be processed, analyzed, and visualized on the NASA Advanced Supercomputing system (NAS) to assess the result. One of the final data analysis products is the dynamic modal decomposition (DMD) results, which decomposes the pressure reading signals by their frequency component. The goal of this project is to visualize the DMD results over a 3D rendering of the model, using efficient and parallelized python routines. The software uses the pytecplot library, a high-level API that connects python scripting to a Tecplot 360 engine. Tecplot is an industry standard high-performance visualization tool that can handle large datasets and workflow. Various animation, rendering, and image-combination techniques were investigated to generate the final videos using OpenCV on the NAS. The final result is a software tool that takes in data products from the uPSP processing chain and generates high resolution visualization videos in parallel for every data file, allowing researchers to view their results efficiently and at an unprecedentedly detailed level.

Emma Dolores McMillian↗

NASA NTRS2021

Evolution of National Airspace System Protection for Space Shuttle Launch and Landing

The breakup of the Space Shuttle Columbia on 1 February 2003 during the entry phase of the STS-107mission occurred above a significant number of aircraft operating in the National Airspace System (NAS).Although no aircraft were struck by falling debris, the incident led the Federal Aviation Administration(FAA) and the National Aeronautics and Space Administration (NASA) to seek cooperative ways to betterprotect aircraft operating in the NAS during Space Shuttle launch and landing operations. Applicationswere developed and improved by both the FAA and NASA to provide pre-operation and near real-timegroundtracks and debris footprints to enable Air Traffic Controllers (ATC) to vector aircraft away from thedebris field in the event of a Space Shuttle breakup. Real-time coordination processes were also developedto provide the FAA data and insight into ongoing Space Shuttle operations in order to protect the NAS.The processes and procedures developed for Space Shuttle operations are extensible and applicable tofuture NASA and commercial spacecraft.

Doyle W Hensley↗

NASA NTRSDate not supplied

Trajectory Based Operations (TBO)

Today, the FAA is fully engaged in the development and deployment of TBO for the NAS. To realize TBO, the FAA and NAS user community recognize the importance of systems-of-systems thinking and of greater integration across systems, programs, teams, and between research and the field. The ATD-1 Operational Integration Assessment (OIA), helped blaze the trail for this important transition while moving TBFM Terminal Sequencing and Spacing (TSAS) down the path to deployment. Only a few years later, a comprehensive flight test of Flight Deck Interval Management (FIM) capabilities was executed, complementary and interoperable with traffic flow capabilities that were then emerging for TBO. Together, the ATD-1 tech transfers helped pave the way for the highly integrated systems-of-systems development and acquisition being undertaken for TBO. This session will chart that path to where we are today, and where we are going in the future.

ATD-1, TSAS, FIM, trajectory based operations↗

NASA NTRS2022

Applicability of Digital Flight to the Operations of Self-Piloted Unmanned Aircraft Systems in the National Airspace System

Unmanned Aircraft Systems (UAS) hold great promise for a new era of specialized missions, including personal air transportation, cargo flight operations, aerial surveys, inspections, firefighting and more. The anticipated market growth is significant. To unlock its scalability and incumbent benefits requires a human to oversee multiple flights simultaneously, focusing on multi-vehicle mission management and relinquishing to autonomous systems their active role in controlling the aircrafts’ flight paths. Key to the realization of these scalability benefits is minimally-encumbered access to the National Airspace System (NAS), which poses some unique challenges for self-piloted UAS aircraft operations. These include the requirement for compatibility with existing airspace structures and operations including Visual Flight Rules (VFR) and Instrument Flight Rules (IFR), neither of which were developed to accommodate the unique needs and capabilities of UAS. This paper explores the applicability of Digital Flight to the operations of self-piloted UAS. As proposed by NASA, Digital Flight is a flight operations capability, enabled by a set of cooperative procedures and digital technologies, in which flight operators ensure flight-path safety through automated separation and flight path management in lieu of visual procedures and Air Traffic Control separation services. Flights operating under potentially-forthcoming rules of Digital Flight employ advanced automation technologies, information sharing, connectivity to operational data, and cooperative behaviors through distributed decision-making to maintain safety and achieve mission objectives. Designed for integration with VFR and IFR operations in shared NAS airspace, potentially as a third set of flight rules, Digital Flight may provide the mechanism for UAS operators – and all aircraft operators – to scale and diversify their operations beyond what is achievable under current regulations.

DFR↗

NASA NTRS2022

A Generalized Approach to Aircraft Trajectory Prediction via Supervised Deep Learning

As research advances diverse forms and missions of aircraft, the National Airspace System (NAS) will become increasingly crowded, limiting current communications resources to accommodate aviation operations. Ongoing research proposes a paradigm of airspace communications, such that resources are autonomously and dynamically allocated via intelligent agents; this allocation requires accurate representations of the NAS, including the predicted positions of aircraft. State-of-the-art research emphasizes the importance of a hybrid-recurrent framework for trajectory prediction and compares the impact of commonly considered weather data on prediction accuracy. However, current research has been limited in its scope of efforts, frequently utilizing a unique flight route, architecture, set of weather data, and date range. This article considers the challenges of generalizing hybrid-recurrent predictive models for flight trajectories. Results illustrate an increase in error variance when identical models are trained over a generalized set of flights; this may be mitigated with careful tuning of hyperparameters, both in the network structure and optimization algorithms. Even so, an irreducible vertical error was identified, resulting from the complex takeoff and landing procedures which can not be correlated to functions of weather or additional assumptions of aircraft behavior. Finally, the use of a test route indicates that generalized models still do not possess sufficient knowledge for general aircraft predictions, with mean error increases ranging from 70-500%. These results illustrate the need for continued efforts on improving model versatility, as well as potential limitations for spectrum allocation near airports and other centers.

Nathan Schimpf↗

NASA NTRSDate not supplied

Identifying Common Coordination Procedures across Extensible Traffic Management (xTM) to Integrate xTM Operations into the National Airspace System

New categories of missions and vehicle types, such as drone delivery services, on-demand air taxi, and high-altitude long-endurance (HALE) vehicles are being proposed to operate using a novel, highly automated information exchange infrastructure and a community-based, cooperative traffic management concept. Collectively, these new operations are called Extensible Traffic Management (xTM). As these xTM vehicles become more prevalent, their operations will increasingly overlap with existing conventional aircraft and with each other. In order to seamlessly co-exist with current conventional aircraft operations, new coordination procedures, tools and services will be needed to integrate xTM into the future National Airspace System (NAS). In our prior work, we have identified a set of use cases for xTM interactions with air traffic control (ATC), categorized across different xTM operations based on trigger events. Events consisted of ones such as nominal xTM vehicle transition into the ATC environment or an off-nominal emergency landing situation. In this paper, we have extended the prior work to identify commonalities in the coordination procedures across xTM, as well as differences that are specific to the individual xTM operations. The overall results showed that two types of xTM-ATC interactions were prevalent: 1) xTM vehicles transitioning between xTM and ATC operational environments; 2) xTM vehicles being allowed to continue xTM operations in areas that are normally controlled by ATC. The results also suggested that emergency and rare off-nominal events may need specialized procedures for each vehicle type. The overall results suggest that there is a pathway to define a common method of handling and integrating diverse xTM operations in the future NAS, but there need to be procedures for individualized handling of xTM vehicles in infrequent, safety-critical events.

Extensible Traffic Management (xTM)↗

NASA NTRSDate not supplied

A Blockchain Case Study for Urban Air Mobility Operational Intent

The next generation of aerial passenger and cargo transportation may leverage the concept of Urban Air Mobility (UAM). UAM is a concept that proposes to develop short-range, point-to-point transportation systems in metropolitan areas using vertical takeoff and landing (VTOL) or short takeoff and landing (STOL) aircraft to overcome increasing surface congestion [1]. The UAM concept leverages a decentralized service-based architecture for airspace solutions. Within the environment, UAM operators work collaboratively to manage aerial vehicles in the urban environment. Providers of Services for UAM (PSU), UAM operators, and Supplemental Data Service Providers (SDSP) provide services to support flight operations within the UAM environment. Also, various views of UAM flight information are provided to the public and public safety entities [2]. The Federal Aviation Administration (FAA) can coordinate flight information between the FAA controlled National Airspace System (NAS) and the UAM environments through the FAA-Industry Data Exchange Protocol (FIDXP). To realize the potential of UAM, an assurance of cybersecurity is critical for public acceptance. Cybersecurity has come to the forefront highlighting the need to protect these networks and systems from cyberattacks. The growth in the development of UAM systems, and the associated data exchange and service interactions will be at risk due to numerous types of cybersecurity attacks. As these threats evolve, the UAM cybersecurity capabilities must adapt to these changes as well [3]. This research focuses on the secure data exchange and storage of this decentralized UAM environment to address these challenges. This research intends to leverage a permissioned blockchain approach to address cybersecurity threats that may impact a UAM environment. Blockchain technologies can be used for tracking transactions and verifying negotiated agreements between stakeholders in the NAS environment. For example, the record of the submitted flight plan and the approved flight plan could be verified using the Blockchain-based immutable ledger.

UAM↗