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NASA NTRS2014

Final Overview of ACES Simulation for Evaluation SARP Well-Clear Definitions

The UAS in the NAS project is studying the minimum operational performance standards for unmanned aerial systems (UAS's) detect-and-avoid (DAA) system in order to operate in the National Airspace System. The DoD's Science and research Panel (SARP) Well-Clear Workshop is investigating the time and spatial boundary at which an UAS violates well-clear. NASA is supporting this effort through use of its Airspace Concept Evaluation System (ACES) simulation platform. This briefing presents the final results to the SARP, which will be used to judge the three candidate well-clear definitions, and for the selection of the most operationally suitable option.

detect and avoid↗
NASA NTRS2017

The Generic Resolution Advisor and Conflict Evaluator (GRACE) for Detect-And-Avoid Systems

Java Architecture for Detect-And-Avoid (DAA) Extensibility and Modeling (JADEM) was developed at NASA Ames Research Center as a research and modeling tool for Unmanned Aircraft Systems (UAS) Integration in the National Airspace System (NAS). UAS will be required to have DAA systems in order to fulfill the regulatory requirement to remain well clear'' of other traffic. JADEM supports research on technological requirements and Minimum Operational Performance Standards (MOPS) for UAS DAA systems by providing a flexible and extensible software platform that includes models and algorithms for all major DAA functions. This paper describes one of these algorithms, the Generic Resolution Advisor and Conflict Evaluator (GRACE). GRACE supports two core DAA functions: threat evaluation and guidance. GRACE is generic in the sense that it is designed to work with any aircraft or sensor type (both cooperative and non-cooperative), and to be used in various applications and DAA guidance concepts, thus supporting evolving MOPS requirements and research. GRACE combines flexibility, robustness, and computational efficiency. It has modest memory requirements and can handle multiple cooperative and noncooperative intruders. GRACE has been used as a core JADEM component in several real-time and fast-time experiments, including human-in-the-loop simulations and live flight tests.

detect and avoid↗
NASA NTRS2024

Integration of Automated Systems Test Campaign NC-IAS

NASA’s 2022 strategic plan included the goal to catalyze economic growth and drive innovation in the aviation industry, and to address challenges in air transportation and airspace management within the National Airspace System (NAS). The Aeronautics Research Mission Directorate (ARMD) specifically was tasked with leading aviation innovation to enable safe and sustainable air transportation through revolutionary vehicle advances and efficient flight operations. As a part of meeting these objectives and advancing air mobility concepts, NASA initiated the National Campaign (NC) in the Advanced Air Mobility (AAM) Project within the Airspace Operations and Safety Program (AOSP). The NC was designed to support operational demonstrations with industry as well as the research and development needed to support NASA-led research flight demonstrations. Within NC, the Integration of Automated Systems (IAS), an NC activity, tested and evaluated flight deck automation and airspace operations management functions needed to enable Urban Air Mobility (UAM) operations. This was accomplished through a partnership with Sikorsky Aircraft (specifically Sikorsky Innovations), a Lockheed Martin company, and DARPA (Defense Advanced Research Projects Agency), by leveraging two automation-enabled helicopters equipped with unique capabilities that enabled NASA to develop and test two-ship conflict encounters to demonstrate flight path management and hazard avoidance technologies. The enabler in this testing was NASA-developed “Middleware” (MW) software (also known as Expandable Variable Autonomy Architecture, or EVAA), which among other things allowed multiple algorithms to be incorporated into one software build that was hosted on the dissimilar-type Sikorsky helicopters. The IAS test campaign period of performance was from March 2022 through October 2023 and was structured as a phased, or spiral, approach that ultimately led to the first-ever demonstration of two-ship UAM/AAM operations designed to safely choreograph specific conflict encounters and mission scenarios to test the research algorithms for strategic and tactical aircraft deconfliction. Lessons learned are included in the body of the report. Data collected will be used to inform FAA and industry standards groups on the increasingly automated systems needed for future AAM operations. The test encounters developed for these flight tests were proven to be highly predictable, repeatable, and safely exercised flight path planning and Detect and Avoid (DAA) algorithms. These same test encounters should be leveraged by future flight test campaigns to verify that operational safety is not compromised as the AAM architecture matures. Next steps include repeating similar encounters using unmanned aircraft carrying DAA sensors in the National Airspace.

AAM↗
NASA NTRSDate not supplied

Integration of Automated Systems (IAS) Flight Test Overview

The Integration of Automated Systems (IAS) Project is conducting a series of 2023 flight tests supporting NASA's Advanced Air Mobility (AAM) and National Campaign efforts. These flights include crewed, test (i.e., ownship) and traffic (i.e., intruder) aircraft that will fly with unique technologies onboard. The presentation will include overviews of the Hazard Perception and Avoidance (HPA) and Flight Path Management (FPM) technical areas but will focus primarily on HPA. HPA will test the FAA's Airborne Collision Avoidance System X (ACAS X), a next-generation collision avoidance tool developed to support different aircraft types and operations. The rotorcraft variant, ACAS Xr, is designed to accommodate existing helicopter platforms and in-development, vertical takeoff and landing (VTOL) concepts, which are critical to the emerging AAM concept of operations. Two configurations of ACAS Xr will be examined: Collision Avoidance System (CAS, similar to the Traffic Collision Avoidance System [TCAS] II) and Detect and Avoid (DAA, previously developed to provide added situational awareness for uncrewed aircraft). Additionally, this system will be explored during cruise and low-speed flight as well as flights within en-route, structured (i.e., dense/urban), and terminal airspaces. Scripted flight conflicts will be conducted, and these conflicts will be mitigated through maneuvers that are manual (i.e., performed by the pilots) or automated (i.e., achieved by the cooperation of the program middleware and onboard ownship systems). Objective data will be collected involving system and pilot performance as well as pilot decisions; subjective data will include pilot opinions of ACAS Xr's alerting and guidance as well as the automated maneuvers.

detect and avoid↗
NASA NTRSDate not supplied

FT-01: Autonomous Helicopter Flight Testing Over Long Island Sound Special Session - Hazard Perception and Avoidance Tech Area

This presentation is included as part of a panel reporting on the Integration of Automated Systems (IAS) flight test series. The IAS series concluded in October 2023 and was conducted under NASA’s Advanced Air Mobility project and in partnership with Sikorsky and the Defense Advanced Research Projects Agency (DARPA). The flight test effort included two crewed rotorcraft platforms. The first, a modified S-76B helicopter, served as the “ownship” for the duration of the flight test. The second vehicle, a modified S-70, served as the intruder aircraft. One Sikorsky pilot and one NASA test pilot was onboard each aircraft for every test point, with the NASA test pilot responsible for interacting with the research systems under test. This portion of the panel presentation focuses on the results of the flight test that assessed the Federal Aviation Administration’s (FAA) next-generation collision avoidance system, the Airborne Collision Avoidance System X for Rotorcraft (ACAS Xr). The two configurations available within ACAS Xr – the Collision Avoidance System (CAS) configuration and the Detect and Avoid (DAA) configuration – were flown with an onboard pilot under Visual Flight Rules in controlled airspace over the Long Island Sound (Connecticut, USA). A total of 33 flight test cards were flown with ACAS Xr active. Results showed that the ACAS Xr alerting and guidance was largely effective and rated positively by the NASA test pilots, exemplified by zero instances of the pilots overriding an ACAS Xr Resolution Advisory (RA). Key areas of improvement, however, were noted, particularly with regards to the lack of an aural alert indicating a need to accelerate when receiving an RA at low speed and the occurrence of multiple RAs that the pilots found to be unacceptable.

detect and avoid↗
NASA NTRS2018

An Exploratory Evaluation of UAS Detect and Avoid Operations in the Terminal Environment

New technical standards for Unmanned Aircraft Systems (UAS) detect and avoid (DAA) systems mark recent progress toward realizing the goal of full integration of UAS into the National Airspace System (NAS). The DAA system is intended to provide a means of compliance with operating regulations that required pilots on board manned aircraft to remain "well clear" of other aircraft which is accomplished through out-the-window visual acquisition of other aircraft and application of a subjective judgment of safe separation. The requirements for the DAA system, including the specification of a DAA well clear threshold as well as functional requirements for detecting, tracking, alerting and guidance processing, and displays, are specified in DO-365, Minimum Operational Performance Standards (MOPS) for DAA Systems developed within RTCA (Radio Technical Commission for Aeronautics) Special Committee 228 (SC-228). Intended as the first in a series of phased versions, these requirements are frequently referred to as the "Phase 1" DAA system. The Phase 1 DAA system is limited for use by aircraft transitioning to and from Class A or special use airspace, through Class D, E, and G airspace. In particular, the Phase 1 DAA MOPS are not intended for terminal airspace operations, a critical gap for enabling a full range of UAS operations. The application of the Phase 1 DAA system and DAA well clear threshold within the terminal area is predicted to result in a high number of unnecessary alerts when the UAS is safely separated from other traffic. The goal of the present study was to examine pilot performance and operational issues related to the operation of the Phase 1 DAA system in a terminal area. This experiment was intended as an exploratory study that would be used to inform the development of a new terminal area-specific DAA well clear definition, and associated alerting and guidance requirements. The two main objectives of this study were to: 1) characterize pilot behavior in the terminal environment with the Phase 1 DAA system, and 2) investigate the effect of modifications to the Phase 1 DAA alerting and guidance structure. In particular, the authors were interested in determining whether the removal of specific alerting and guidance levels, without changing the DAA well clear definition or alerting thresholds, would impact pilot performance while conducting terminal operations. The results indicate that the Phase 1 well clear definition and alerting and guidance resulted in frequent alerting that degraded pilots' ability to discriminate between encounters where another aircraft was safely separated versus when a maneuver was necessary. The resulting impact on pilot performance was slower response times and higher frequency and severity of losses of DAA well clear compared to those observed for experiments examining pilot performance in the en route environment. There was no significant effect of alerting and guidance display configuration on pilot performance.

terminal area↗
NASA NTRS2018

An Exploratory Evaluation of UAS Detect and Avoid Operations in the Terminal Environment

New technical standards for Unmanned Aircraft Systems (UAS) detect and avoid (DAA) systems mark recent progress toward realizing the goal of full integration of UAS into the National Airspace System (NAS). The DAA system is intended to provide a means of compliance with operating regulations that required pilots on board manned aircraft to remain "well clear" of other aircraft which is accomplished through out-the-window visual acquisition of other aircraft and application of a subjective judgment of safe separation. The requirements for the DAA system, including the specification of a DAA well clear threshold as well as functional requirements for detecting, tracking, alerting and guidance processing, and displays, are specified in DO-365, Minimum Operational Performance Standards (MOPS) for DAA Systems developed within RTCA Special Committee 228 (SC-228). Intended as the first in a series of phased versions, these requirements are frequently referred to as the "Phase 1" DAA system. The Phase 1 DAA system is limited for use by aircraft transitioning to and from Class A or special use airspace, through Class D, E, and G airspace. In particular, the Phase 1 DAA MOPS are not intended for terminal airspace operations, a critical gap for enabling a full range of UAS operations. The application of the Phase 1 DAA system and DAA well clear threshold within the terminal area is predicted to result in a high number of unnecessary alerts when the UAS is safely separated from other traffic. The goal of the present study was to examine pilot performance and operational issues related to the operation of the Phase 1 DAA system in a terminal area. This experiment was intended as an exploratory study that would be used to inform the development of a new terminal area-specific DAA well clear definition, and associated alerting and guidance requirements. The two main objectives of this study were to: 1) characterize pilot behavior in the terminal environment with the Phase 1 DAA system, and 2) investigate the effect of modifications to the Phase 1 DAA alerting and guidance structure. In particular, the authors were interested in determining whether the removal of specific alerting and guidance levels, without changing the DAA well clear definition or alerting thresholds, would impact pilot performance while conducting terminal operations. The results indicate that the Phase 1 well clear definition and alerting and guidance resulted in frequent alerting that degraded pilots' ability to discriminate between encounters where another aircraft was safely separated versus when a maneuver was necessary. The resulting impact on pilot performance was slower response times and higher frequency and severity of losses of DAA well clear compared to those observed for experiments examining pilot performance in the en route environment. There was no significant effect of alerting and guidance display configuration on pilot performance.

Rorie, Conrad↗
NASA NTRS2018

UAS Integration in the NAS: Detect and Avoid

This presentation will cover the structure of the unmanned aircraft systems (UAS) integration into the national airspace system (NAS) project (UAS-NAS Project). The talk also details the motivation of the project to help develop standards for a detect-and-avoid (DAA) system, which is required in order to comply with requirements in manned aviation to see-and-avoid other traffic so as to maintain well clear. The presentation covers accomplishments reached by the project in Phase 1 of the research, and touches on the work to be done in Phase 2. The discussion ends with examples of the display work developed as a result of the Phase 1 research.

unmanned aircraft systems↗
NASA NTRS2017

Unmanned Aircraft Systems (UAS) Integration in the National Airspace System (NAS) Project: Terminal Operations HITL 1: Primary Results

This presentation covers the primary results of the Unmanned Aircraft Systems (UAS) Integration in the National Airspace System (NAS) Project Terminal Operations Foundational Human-in-the-Loop (HITL) simulation. The study tasked 16 pilots (half with manned piloting experience, and the other half with unmanned piloting experience) with maintaining "well clear" from other traffic while performing three different types of approaches into the Santa Rosa airport. A detect and avoid (DAA) system was provided to pilots to assist their ability to manage separation. The DAA system used in this test conformed to the criteria defined by RTCA Special Committee 228 (SC-228) in their Phase 1 Minimum Operational Performance Standards (MOPS) for UAS intending to operate in the NAS. The Phase 1 system was not designed to account for terminal operations, focusing instead on en route operations. To account for this, three different alerting and guidance configurations were presently tested in order to determine their effect on pilots operating the system in the terminal area. Results indicated that pilots with the alerting and guidance condition that provided the least amount of assistance (fewer alert levels and guidance types) experienced slightly increased pilot response times and rates of losses of separation. Additional data is presented on the effects of approach type and descriptive data on pilot maneuver preferences and ATC interoperability.

terminal environmen↗
NASA NTRS2015

Pilot Evaluation of a UAS Detect-and-Avoid System's Effectiveness in Remaining Well Clear

Unmanned aircraft will equip with a detect-and-avoid (DAA) system that allows them to comply with the requirement to see and avoid other aircraft, an important layer in the overall set of procedural, strategic and tactical separation methods designed to prevent mid-air collisions. Although the effectiveness of the DAA system will be set to a minimum threshold by regulators, different combinations of algorithms, displays and procedures could be used to meet that minimum. The research presented in this paper indicates the effectiveness of the combined pilot-DAA system as a function of the DAA design requirements and provides data that may be used to model the behavior of pilots when employing such systems. Over the course of two simulations 21 professional UAS pilots evaluated eight different DAA system designs and metrics were collected on their ability to maintain the well clear separation standard. The independent variables were the time horizon at which pilots were alerted to potential losses of well clear, the location of the traffic display, and the tools and informational elements available on the display to aid the pilot in detecting and resolving those potential losses. In the second experiment the UAS encountered two categories of aircraft: those equipped with simulated transponders that could be seen dozens of miles away and those without that were only detectable by a simulated radar within a range of six nautical miles. The data indicate that integrating the traffic display with the primary mission map directly in front of the pilot reduced the frequency of losses of well clear. Improved detection and resolution tools, including explicit maneuver guidance and a trial planning capability, had less of an effect in reducing the frequency of losses but significantly reduced the time in loss when they occurred. The amount of warning time provided to the pilot had a strong effect on their ability to remain well clear: when alerts were first presented with less than about 15 seconds to a predicted loss of well clear pilots were able to maneuver successfully in only 26 percent of encounters, whereas they were about 83 percent successful when they had more than 15 seconds. Pilots' ability to separate from the two categories of aircraft was nearly the same after accounting for the amount of alert time provided in each encounter, although the limited surveillance volume for the non-transponder equipped aircraft meant alerts tended to occur later and therefore were more difficult to resolve.

loss of well clear↗
NASA NTRSDate not supplied

Detect and Avoid and Collision Avoidance Flight Test Results with ACAS Xr

In October 2023, the National Aeronautics and Space Administration (NASA) completed its Integration of Automated Systems flight test series, conducted under NASA’s Advanced Air Mobility project and in partnership with Sikorsky and the Defense Advanced Research Projects Agency (DARPA). The flight test effort included two crewed rotorcraft platforms. The first, a modified S-76B helicopter, served as the “ownship” for the duration of the flight test. The second vehicle, a modified S-70, served as the intruder aircraft. One Sikorsky pilot and one NASA test pilot was onboard each aircraft for every test point, with the NASA test pilot responsible for interacting with the research systems under test. Approximately half of the flight test was devoted to assessing the Federal Aviation Administration’s (FAA) next-generation collision avoidance system, the Airborne Collision Avoidance System X for Rotorcraft (ACAS Xr). The two configurations available within ACAS Xr – the Collision Avoidance System (CAS) configuration and the Detect and Avoid (DAA) configuration – were flown with an onboard pilot under Visual Flight Rules in controlled airspace over the Long Island Sound (Connecticut, USA). A total of 33 flight test cards were flown with ACAS Xr active. The ownship was equipped with ACAS Xr and the intruder was equipped with Automatic Dependent Surveillance-Broadcast (ADS-B). The test points were blocked by ACAS Xr configuration, with individual encounters varying the ownship speed (90 knots or 20 knots), the intruder designation (en-route, terminal area, or structured airspace), and method of RA execution (automated or manually executed). Results showed that the ACAS Xr alerting and guidance was largely effective and rated positively by the NASA test pilots, exemplified by zero instances of the pilots overriding an ACAS Xr Resolution Advisory (RA). Key areas of improvement, however, were noted, particularly with regards to the lack of an aural alert indicating a need to accelerate when receiving an RA at low speed and the occurrence of multiple RAs that the pilots found to be unacceptable.

detect and avoid↗
NASA NTRSDate not supplied

Detect and Avoid and Collision Avoidance Flight Test Results with ACAS Xr

In October 2023, the National Aeronautics and Space Administration (NASA) completed its Integration of Automated Systems flight test series, conducted under NASA’s Advanced Air Mobility project and in partnership with Sikorsky and the Defense Advanced Research Projects Agency (DARPA). The flight test effort included two crewed rotorcraft platforms. The first, a modified S-76B helicopter, served as the “ownship” for the duration of the flight test. The second vehicle, a modified S-70, served as the intruder aircraft. One Sikorsky pilot and one NASA test pilot was onboard each aircraft for every test point, with the NASA test pilot responsible for interacting with the research systems under test. Approximately half of the flight test was devoted to assessing the Federal Aviation Administration’s (FAA) next-generation collision avoidance system, the Airborne Collision Avoidance System X for Rotorcraft (ACAS Xr). The two configurations available within ACAS Xr – the Collision Avoidance System (CAS) configuration and the Detect and Avoid (DAA) configuration – were flown with an onboard pilot under Visual Flight Rules in controlled airspace over the Long Island Sound (Connecticut, USA). A total of 33 flight test cards were flown with ACAS Xr active. The ownship was equipped with ACAS Xr and the intruder was equipped with Automatic Dependent Surveillance-Broadcast (ADS-B). The test points were blocked by ACAS Xr configuration, with individual encounters varying the ownship speed (90 knots or 20 knots), the intruder designation (en-route, terminal area, or structured airspace), and method of RA execution (automated or manually executed). Results showed that the ACAS Xr alerting and guidance was largely effective and rated positively by the NASA test pilots, exemplified by zero instances of the pilots overriding an ACAS Xr Resolution Advisory (RA). Key areas of improvement, however, were noted, particularly with regards to the lack of an aural alert indicating a need to accelerate when receiving an RA at low speed and the occurrence of multiple RAs that the pilots found to be unacceptable.

detect and avoid↗
NASA NTRSDate not supplied

Pathfinding for Airspace with Autonomous Vehicles (PAAV) ACAS Xr Terminal Area Simulation Overview

This presentation provides an overview of an upcoming human-in-the-loop simulation planned by the Pathfinding for Airspace with Autonomous Vehicles (PAAV) subproject, as part of the Air Traffic Management eXploration project. The study will investigate Detect and Avoid (DAA) concepts in and around the DAA terminal area (DTA). The DTA has received little investigation in real-time, pilot-in-the-loop simulation. This study proposes to use current remotely piloted aircraft system (RPAS) pilots to investigate the effectiveness of current DTA requirements using the FAA's Airborne Collision Avoidance System X for Rotorcraft (ACAS Xr) as the DAA system under test. The findings of this stufy will be used to inform DTA and ACAS Xr standards development. This presentation will be provided to RTCA Special Committee 228 as an overview and as an opportunity to collect feedback from the larger RPAS/DAA community on the study design and key scenarios and metrics. The presentation provides a brief overview of open areas of research with ACAS Xr, the experimental design, the simulation environment and the simulation schedule.

advanced air mobility↗
NASA NTRS2014

Pilot Evaluation of a UAS Detect-and-Avoid System's Effectiveness in Remaining Well Clear

Unmanned aircraft will equip with a detect-and-avoid (DAA) system that enables them to comply with the requirement to "see and avoid" other aircraft, an important layer in the overall set of procedural, strategic and tactical separation methods designed to prevent mid-air collisions. Regulators will establish minimum operating standards for DAA effectiveness, but different combinations of algorithms, displays and procedures could be used to meet those standards. The research presented in this paper indicates the effectiveness of the combined pilot-DAA system as a function of the DAA design requirements and provides data that may be used to model the behavior of pilots when employing such systems. Two simulations involving 21 professional unmanned aircraft system (UAS) pilots evaluated eight different DAA system designs in order to assess their ability to maintain the "well clear" separation standard, i.e., the state of maintaining a safe distance from other aircraft that would not normally cause the initiation of a collision avoidance maneuver by either aircraft. When the traffic display was integrated with the primary mission map directly in front of the pilot, there were fewer losses of well clear. Greater warning time provided to the pilot was strongly correlated with success in remaining well clear. Pilots' ability to separate from aircraft with cooperative and non-cooperative surveillance systems was nearly the same after accounting for the amount of alert time provided in each encounter, although the limited surveillance volume for the airborne-equipped aircraft meant alerts tended to occur later and therefore were more difficult to resolve.

detect-and-avoid↗
NASA NTRS2017

UAS Well Clear Recovery Against Non-Cooperative Intruders Using Vertical Maneuvers

This paper documents a study that drove the development of a mathematical expression in the detect-and-avoid (DAA) minimum operational performance standards (MOPS) for unmanned aircraft systems (UAS). This equation describes the conditions under which vertical maneuver guidance should be provided during recovery of DAA well clear separation with a non-cooperative VFR aircraft. Although the original hypothesis was that vertical maneuvers for DAA well clear recovery should only be offered when sensor vertical rate errors are small, this paper suggests that UAS climb and descent performance should be considered-in addition to sensor errors for vertical position and vertical rate-when determining whether to offer vertical guidance. A fast-time simulation study involving 108,000 encounters between a UAS and a non-cooperative visual-flight-rules aircraft was conducted. Results are presented showing that, when vertical maneuver guidance for DAA well clear recovery was suppressed, the minimum vertical separation increased by roughly 50 feet (or horizontal separation by 500 to 800 feet). However, the percentage of encounters that had a risk of collision when performing vertical well clear recovery maneuvers was reduced as UAS vertical rate performance increased and sensor vertical rate errors decreased. A class of encounter is identified for which vertical-rate error had a large effect on the efficacy of horizontal maneuvers due to the difficulty of making the correct left/right turn decision: crossing conflict with intruder changing altitude. Overall, these results support logic that would allow vertical maneuvers when UAS vertical performance is sufficient to avoid the intruder, based on the intruder's estimated vertical position and vertical rate, as well as the vertical rate error of the UAS' sensor.

UAS in the NAS↗
NASA NTRS2018

ADS-B Mixed sUAS and NAS System Capacity Analysis and DAA Performance

Automatic Dependent Surveillance-Broadcast (ADS-B) technology was introduced more than twenty years ago to improve surveillance within the US National Airspace Space (NAS) as well as in many other countries. Via the NextGen initiative, implementation of ADS-B technology across the US is planned in stages between 2012 and 2025. ADS-B's automatic one second epoch packet transmission exploits on-board GPS-derived navigational information to provide position information, as well as other information including vehicle identification, ground speed, vertical rate and track angle. The purpose of this technology is to improve surveillance data accuracy and provide access to better situational awareness to enable operational benefits such as shorter routes, reduced flight time and fuel burn, and reduced traffic delays, and to allow air traffic controllers to manage aircraft with greater safety margins. Other than the limited amount of information bits per packet that can be sent, ADS-B's other hard-limit limitation is capacity. Small unmanned aircraft systems (sUAS) can utilize limited ADS-B transmission power, in general, thus allowing this technology to be considered for use within a combined NAS and sUAS environment, but the potential number and density of sUAS predicted for future deployment calls into question the ability of ADS-B systems to meet the resulting capacity requirement. Hence, studies to understand potential limitations of ADS-B to fulfill capacity requirements in various sUAS scenarios are of great interest. In this paper we, validate/improve on, previous work performed by the MITRE Corporation concerning sUAS power and capacity in a sUAS and General Aviation (GA) mixed environment. In addition, we implement its inherent media access control layer capacity limitations which was not shown in the MITRE paper. Finally, a simple detect and avoid (DAA) algorithm is implemented to display that ADS-B technology is a viable technology for a mixed NAS/sUAS environment even in proposed larger mixed density environments.

Matheou, Konstantin J.↗
NASA NTRS2018

ADS-B Mixed sUAS and NAS System Capacity Analysis and DAA Performance

Automatic Dependent Surveillance-Broadcast (ADS-B) technology was introduced more than twenty years ago to improve surveillance within the US National Airspace Space (NAS) as well as in many other countries. Via the NextGen initiative, implementation of ADS-B technology across the US is planned in stages between 2012 and 2025. ADS-B's automatic one second epoch packet transmission exploits on-board GPS-derived navigational information to provide position information, as well as other information including vehicle identification, ground speed, vertical rate and track angle. The purpose of this technology is to improve surveillance data accuracy and provide access to better situational awareness to enable operational benefits such as shorter routes, reduced flight time and fuel burn, and reduced traffic delays, and to allow air traffic controllers to manage aircraft with greater safety margins. Other than the limited amount of information bits per packet that can be sent, ADS-B's other hard-limit limitation is capacity. Small unmanned aircraft systems (sUAS) can utilize limited ADS-B transmission power, in general, thus allowing this technology to be considered for use within a combined NAS and sUAS environment, but the potential number and density of sUAS predicted for future deployment calls into question the ability of ADS-B systems to meet the resulting capacity requirement. Hence, studies to understand potential limitations of ADS-B to fulfill capacity requirements in various sUAS scenarios are of great interest. In this paper we, validate/improve on, previous work performed by the MITRE Corporation concerning sUAS power and capacity in a sUAS and General Aviation (GA) mixed environment. In addition, we implement its inherent media access control layer capacity limitations which was not shown in the MITRE paper. Finally, a simple detect and avoid (DAA) algorithm is implemented to display that ADS-B technology is a viable technology for a mixed NAS/sUAS environment even in proposed larger mixed density environments.

Matheou, Konstantin↗