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NASA NTRS2015

The Role of the NASA Global Hawk Link Module as an Information Nexus For Atmospheric Mapping Missions

The Link Module described in this paper was developed for the NASA Uninhabited Aerial System (UAS) Global Hawk Pacific Mission (GloPAC) Airborne Science Campaign; four flights of 30 hour duration, supporting the Aura Validation Experiment (AVE). It was used again during the Genesis and Rapid Intensification Processes (GRIP) experiment, a NASA Earth Science field experiment to better understand how tropical storms form and develop into major hurricanes. In these missions, the Link Module negotiated all communication over the high bandwidth Ku satellite link, archived all the science data from onboard experiments in a spatially enabled database, routed command and control of the instruments from the Global Hawk Operations Center, and re-transmitted select data sets directly to experimenters control and analysis systems. The availability of aggregated information from collections of sensors, and remote control capabilities, in real-time, is revolutionizing the way Airborne Science is being conducted. The Link Module NG now being flown in support of the NASA Earth Venture missions, the Hurricane and Severe Storm Sentinel (HS3) mission, and Airborne Tropical Tropopause Experiment (A TTREX) mission, has advanced data fusion technologies that are further advancing the Scientific productivity, flexibility and robustness of these systems. On-the-fly traffic shaping has been developed to allow the high definition video, used for critical flight control segments, to dynamically allocate variable bandwidth on demand. Historically, the Link Module evolved from the instrument and communication interface controller used by NASA's Pathfinder and Pathfinder plus solar powered UAS's in the late 1990' s. It later was expanded for use in the AIRDAS four channel scanner flown on the NASA Altus UAS, and then again to a module in the AMS twelve channel multispectral scanner flying on the NASA (Predator-b) Ikhana UAS. The current system is the answer to the challenges imposed by extremely long duration UASs, with on-board multi-instrument (>= 12) Sensor Webs.

Hurricanes↗

NASA NTRS2016

Unmanned Aerial Systems Traffic Management (UTM): Safely Enabling UAS Operations in Low-Altitude Airspace

Currently, there is no established infrastructure to enable and safely manage the widespread use of low-altitude airspace and UAS flight operations. Given this, and understanding that the FAA faces a mandate to modernize the present air traffic management system through computer automation and significantly reduce the number of air traffic controllers by FY 2020, the FAA maintains that a comprehensive, yet fully automated UAS traffic management (UTM) system for low-altitude airspace is needed. The concept of UTM is to begin by leveraging concepts from the system of roads, lanes, stop signs, rules and lights that govern vehicles on the ground today. Building on its legacy of work in air traffic management (ATM), NASA is working with industry to develop prototype technologies for a UAS Traffic Management (UTM) system that would evolve airspace integration procedures for enabling safe, efficient low-altitude flight operations that autonomously manage UAS operating in an approved low-altitude airspace environment. UTM is a cloud-based system that will autonomously manage all traffic at low altitudes to include UASs being operated beyond visual line of sight of an operator. UTM would thus enable safe and efficient flight operations by providing fully integrated traffic management services such as airspace design, corridors, dynamic geofencing, severe weather and wind avoidance, congestion management, terrain avoidance, route planning re-routing, separation management, sequencing spacing, and contingency management. UTM removes the need for human operators to continuously monitor aircraft operating in approved areas. NASA envisions concepts for two types of UTM systems. The first would be a small portable system, which could be moved between geographical areas in support of operations such as precision agriculture and public safety. The second would be a Persistent system, which would support low-altitude operations in an approved area by providing continuous automated coverage. Both would require persistent communication, navigation, and surveillance (CNS) coverage to track, ensure, and monitor conformance. UTM is creating an airspace management tool that allows the ATM system to accommodate the number of UAS that will operate in the low altitude airspace. The analogy is just because we have a car, whether its autonomous or someone is driving, does not diminish the need for a road or road signs or rules of the road.

traffic management↗

NASA NTRS2016

Lighter-Than-Air (LTA) "AirStation": Unmanned Aircraft System (UAS) Carrier Concept

Proposals for adapting modern airship technologies for military missions have mostly focused on exploiting the airships high flight endurance and low fuel requirement to conduct direct surveillance missions requiring high degrees of persistence over the areas to be observed. While this mission has value, it constrains the airship in two regards. (1) It places all the surveillance sensors, communication systems, and other mission equipment in the airship itself. (2) It requires the airship to be physically in the vicinity of the areas to be directly observed. A more advanced utilization of airship technology would be to add the capability to deploy a separate set of surveillance equipment, thereby enabling indirect and distributed observation operations. This can be undertaken by installing surveillance equipment in a squadron of unmanned aircraft systems (UAS) that can be carried and operated remotely from the airship, and then return to the airship as a base of support. This could be accomplished by deploying 20-30 UASs on an optionally manned (5 person crew) airship. The mission focus of the airship UAS carrier would be for support of distributed intelligence, surveillance and reconnaissance (ISR), close air support (CAS), maritime patrol and interdiction, electronic warfare (EW), persistent area dominance and missile defense. The logic for utilizing an airship carrier over a ground base to deploy UAS will be examined. Whether to be used as a stand-alone platform or in concert with conventional intelligence gathering techniques, the airship UAS carrier can provide the following benefits: a mobile base that will remain accessible despite political fallout which may render a ground base unavailable for use, the psychological impact of a power projection tool that has no geographical limits (imagined in the same way a naval carrier group projects power), cost-saving intelligence gathering over manned alternatives (assumption), and a wider area of influence when compared to an immobile ground base that must facilitate the transfer of UAS to other bases in order to overfly particular areas (all operations, launch, recover, etc. take place from the airship).

Hochstetler, Ron↗

NASA NTRS2018

Ubiquitous Surveillance Notional Architecture for System-Wide DAA Capabilities in the NAS

There is an increasing demand for access to the national airspace system (NAS) by new entrants such as unmanned aircraft systems (UASs) and space vehicles. The need is driving the research into the development of a ubiquitous surveillance framework. A framework where all means of aircraft position tracking systems, both cooperative and noncooperative, would be correlated and made available to all NAS users. The architecture of an envisioned surveillance system was the focus of a recent Volpe National Transportation Systems Center research activity. In this work, the term ''Framework'' is used to characterize an operational environment that forms the context for future UAS operations. Within this framework, the use of all existing and future surveillance technologies is envisioned. Included would be all airspace locations; including coverage for airspace not under surveillance today. While these surveillance means and methods of air traffic control may currently constrain new entrant operations, they also provide the opportunity for the plethora of enabling technological capabilities with associated policies and procedures that can result in the safe, orderly and efficient operation. The focus of this paper is to survey and identify surveillance technologies to support the integration of new entrants in the NAS, and how those technologies can be aggregated.

Surveillance↗

NASA NTRS2019

Remote ID for Rapid Assessment of Flight and Vehicle Information

The ability to rapidly identify UAS (Unmanned Aircraft Systems) 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 percent 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.

USS (UAS Service Supplier)↗

NASA NTRS2019

Scenario Complexity for Unmanned Aircraft System Traffic

UTM↗

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

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

Urban Area Unmanned Aerial Systems Sensor Capabilities for Ensuring Ground Hazards Safety

Unmanned aerial systems (UASs) in urban areas can pose significant safety risks to dynamic ground objects (DGOs) such as people, pets, and bikes; especially for off-nominal emergency traverses and landings. This paper will examine a framework for evaluating the UAS safety benefits which can be achieved by classifying DGO hazards, modeling their behavior, and assigning collision costs. DGOs are assumed to be any ground objects which are either moving or capable of moving. Safety benefits will be assessed by analyzing metrics computed from UAS and DGO trajectories which take into account intent and uncertainties. This paper will establish the theoretical relationships mapping these trajectories and DGO classifications to safety levels. Sensor capabilities will be mapped to DGO trajectory uncertainties, so that safety can be directly estimated from the sensor specifications for a given UAS trajectory.

Bouyssounouse, Xavier↗

NASA NTRS2019

"Sensor Web Evolution - Webs of Webs for NASA Science - Focus on small Uninhabited Aerial Systems (sUAS)"

This paper will describe the evolution of information collection, derivation and delivery mechanisms in webs of NASA sensor webs, with a focus on recent advancements in small Uninhabited Aerial Systems (sUAS). I will discuss the movement to "Fog Computing", also known as Edge Computing. Fog Computing facilitates the distribution of common operations and networking between edge devices and cloud computing facilities, optimizing the production of actionable intelligence. Initially, sUASs utilized onboard data collection as standard, with minimal data downloaded directly. Information products were derived in conventional computational environments, generally desk top computers, and information products made available to the Science Community in weeks or months. With the increased availability, and increasingly lower costs, of beyond line of sight (BLOS) satellite based communication, transmission rates and data volumes increased, and processing migrated to Cloud based services. Contemporary sUASs are moving some of that information product derivation to on vehicle services, and are creating a distributed Cloud/Fog environment. I will describe the technological advances that have made this possible, including low power multi-core Central Processing Units (CPU), and, more recently, the availability of high end Graphical Processing Units (GPU) that consume only a few watts. Intelligent system software, leveraging these hardware advances, finally allows for information product generation on-board, rather than simple data collection. Additionally, intelligent flight control systems now support mutual vehicle to vehicle collaboration, allowing sUASs to create ad-hoc sensor webs on demand, as required. Also discussed will be the lessons learned by the Authors' development of data systems for NASA's large High Altitude Long Endurance (HALE) UASs like Predator and Global Hawk, and how those lessons are being applied to sUAS development. This paper will focus on application, rather a deep dive into the technology, and will highlight improving data management through these new technologies.

Sensor Web↗

NASA NTRS2019

Airborne Radar for sUAS Sense and Avoid

A primary challenge for the safe integration of small UAS operations into the National Airspace System (NAS) is traffic deconfliction, both from manned and unmanned aircraft. The UAS Traffic Management (UTM) project being conducted at the National Aeronautics and Space Administration (NASA) considers a layered approach to separation provision, ranging from segregation of operations through airspace volumes (geofences) to autonomous sense and avoid (SAA) technologies for higher risk, densely occupied airspace. Cooperative SAA systems, such as Automatic Dependent Surveillance-Broadcast (ADS-B) and/or vehicle-to-vehicle communication systems provide significant additional risk mitigation but they fail to adequately mitigate collision risks for non-cooperative (non-transponder equipped) airborne aircraft. The RAAVIN (Radar on Autonomous Aircraft to Verify ICAROUS Navigation) flight test being conducted by NASA and the Mid-Atlantic Aviation Partnership (MAAP) was designed to investigate the applicability and performance of a prototype, commercially available sUAS radar to detect and track non-cooperative airborne traffic, both manned and unmanned. The radar selected for this research was a Frequency Modulated Continuous Wave (FMCW) radar with 120 degree azimuth and 80 degree elevation field of view operating at 24.55GHz center frequency with a 200 MHz bandwidth. The radar transmits 2 watts of power thru a Metamaterial Electronically Scanning Array antenna in horizontal polarization. When the radar is transmitting, personnel must be at least 1 meter away from the active array to limit nonionizing radiation exposure. The radar physical dimensions are 18.7cm by 12.1cm by 4.1cm and it weighs less than 820 grams making it well suited for installation on small UASs. The onboard, SAA capability, known as ICAROUS, (Independent Configurable Architecture for Reliable Operations of Unmanned Systems), developed by NASA to support sUAS operations, will provide autonomous guidance using the traffic radar tracks from the onboard radar. The RAAVIN set of studies will be conducted in three phases. The first phase included outdoor, ground-based radar evaluations performed at the Virginia Tech’s Kentland Farm testing range in Blacksburg, VA. The test was designed to measure how well the radar could detect and track a small UAS flying in the radar’s field of view. The radar was used to monitor 5 test flights consisting of outbound, inbound and crossing routes at different ranges and altitudes. The UAS flown during the ground test was the Inspire 2, a quad copter weighing less than 4250 grams (10 pounds) at maximum payload. The radar was set up to scan and track targets over its full azimuthal field of view from 0 to 40 degrees in elevation. The radar was configured to eliminate tracks generated from any targets located beyond 2000 meters from the radar and moving at velocities under 1.45 meters per second. For subsequent phases of the study the radar will be integrated with a sUAS platform to evaluate its performance in flight for SAA applications ranging from sUAS to manned GA aircraft detections and tracking. Preliminary data analysis from the first outdoor ground tests showed the radar performed well at tracking the vehicle as it flew outbound and repeatedly maintained a track out to 1000 meters (maximum 1387 meters) until the vehicle slowed to a stop to reverse direction to fly inbound. As the Inspire flew inbound tracks from beyond 800 meters, a reacquisition time delay was consistently observed between when the Inspire exceeds a speed of 1.45 meters per second and when the radar indicated an inbound target was present and maintained its track. The time delay varied between 6 seconds to over 37 seconds for the inbound flights examined, and typically resulted in about a 200 meter closure distance before the Inspire track was maintained. The radar performed well at both acquiring and tracking the vehicle as it flew crossing routes out past 400 meters across the azimuthal field of view. The radar and ICAROUS software will be integrated and flown on a BFD-1400-SE8-E UAS during the next phase of the RAAVIN project. The main goal at the conclusion of this effort is to determine if this radar technology can reliably support minimum requirements for SAA applications of sUAS. In particular, the study will measure the range of vehicle detections, lateral and vertical angular errors, false and missed/late detections, and estimated distance at closest point of approach after an avoidance maneuver is executed. This last metric is directly impacted by sensor performance and indicates its suitability for the task.

Szatkowski, George N.↗

NASA NTRS2022

Uncrewed Aerial Vehicles and Systems Support Safer Aeronautics Research

Area-I partnered with the NASA SBIR/STTR program to develop Uncrewed Aircraft Systems (UASs) that supported advanced aeronautics research. The company’s developments with NASA culminated in the Prototype-Technology Evaluator and Research Aircraft (PTERA), a versatile UAS enabling low-risk flight experiments that are safer than piloted tests and more dynamic than wind tunnel testing. From the initial seed funding from NASA, Area-I continued to hone its abilities in UAS development, finding success with the Department of Defense and leading to the company’s acquisition by Anduril Industries—a $4.6 billion defense technology company—in 2021.

Bruce R Cogan↗

NASA NTRS2022

UAM Research – X4: Introduction to Community Based Rules (CBRs)

Recent advances in technology have enabled industry development of new and innovative vehicle types, offering lower operating costs and highly automated functionality that facilitates the introduction of new types of operations. These include low-altitude airspace operations with small Unmanned Aircraft Systems (UASs), short distance urban and intercity operations, and high- altitude Upper Class E operations. These and other new operations are expected to result in a much higher operational tempo than is currently experienced across the National Airspace System (NAS). The projected increase in operations, as well as the introduction of new aircraft form factors and supporting technologies—including increasing autonomy—will present challenges to the existing Air Traffic Management (ATM) system, which is currently unable to cost-effectively scale and deliver needed services. In response to these challenges and opportunities, a highly automated, cooperative environment incorporating a federated network has been envisioned and described through multiple operational concepts, depicting the future operating environment as part of the NAS. Foundational to the success of this future operating environment is the establishment of common business rules and understandings across relevant stakeholders, referred to as Community Based Rules (CBRs). Development, adoption, and implementation of CBRs will require collaboration across multiple stakeholders, including operators, support services (industry), and the Federal Aviation Administration (FAA), to identify and resolve a broad range of questions and challenges. Examples of these questions include “what rules are needed?”, “how are they expressed?”, and “how will they be managed?” This document identifies and describes an initial set of questions and considerations to be examined as efforts begin to create the innovative, automated, cooperative operating environment of the future. The goal is to establish a common frame of reference to support discussions and decisions regarding the future implementation of CBRs as part of the NAS.

Community Based Rules↗

NASA NTRSDate not supplied

Developing and Testing Two Interfaces for Supplemental Data Service Provider (SDSP) Tools to Support UAS Traffic Management (UTM)

Researchers conducted a usability study using two graphical user interfaces (GUIs) to explore how individuals interpret and interact with different preflight information displays, and to inform the development of Uncrewed Aircraft System (UAS) preflight planning predictive support tools to assess and mitigate flight hazards and risks. A series of preflight risk-assessment tasks were developed to evaluate participant performance using the Supplemental Data Service Provider-Consolidated Dashboard (SDSP-CD) and the Human Automation Team Interface System (HATIS) GUIs. Participants were trained to use both interfaces and their performance was evaluated. These evaluations focused on participants’ preflight planning activities. Objective data on performance tasks across different scenarios involving multi-UASs, as well as self-reports of interactions and subjective experiences using the GUIs were collected. Scores on the system usability scale (SUS) and on a simple task set were examined, as well as user feedback on open-ended questions, to inform development and identify potential improvements to the interfaces.

sUAAV interfaces↗

NASA NTRSDate not supplied

Developing and Testing Two Interfaces for Supplemental Data Service Provider (SDSP) Tools to Support UAS Traffic Management (UTM)

sUAAV interfaces↗