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All sourcesNASA NTRSDOE OSTI
NASA NTRS2016

Simulation and Flight Test Data Collection to Support Phase 1 Detect-and-Avoid MOPS

The UAS Integration into the NAS (UASNAS) project is studying the minimum operational performance standards for unmanned aerial system (UAS) detect-and-avoid (DAA) systems in order to operate in the National Airspace System (NAS). The project is executing a series of fast-time simulation, human-in-the-loop experiments, and flight tests in support of this effort. Armstrong Flight Research Center is hosting a VIP Day in conjunction with the UAS-NAS Project's Flight Test 4 activity, and the Ames Project Engineer (or designate) will be presenting a briefing. This briefing will review the data collection and analysis activities for Flight Test 4 within the Separation assurance-Sense-and-avoid Interoperability (SSI) team.

data analysis↗
NASA NTRS2017

Unmanned Aircraft Systems (UAS) Integration in the National Airspace System (NAS) Project: Detect and Avoid Display Evaluations in Support of SC-228 Minimum Operational Performance Standards Development

The primary activity for the UAS-NAS Human Systems Integration (HSI) sub-project in Phase 1 was support of RTCA Special Committee 228 Minimum Operational Performance Standards (MOPS). We provide data on the effect of various Detect and Avoid (DAA) display features with respect to pilot performance of the remain well clear function in order to determine the minimum requirements for DAA displays.

detect and avoid↗
NASA NTRS2009

Lunar Landing Trajectory Design for Onboard Hazard Detection and Avoidance

The Autonomous Landing and Hazard Avoidance Technology (ALHAT) Project is developing the software and hardware technology needed to support a safe and precise landing for the next generation of lunar missions. ALHAT provides this capability through terrain-relative navigation measurements to enhance global-scale precision, an onboard hazard detection system to select safe landing locations, and an Autonomous Guidance, Navigation, and Control (AGNC) capability to process these measurements and safely direct the vehicle to a landing location. This paper focuses on the key trajectory design issues relevant to providing an onboard Hazard Detection and Avoidance (HDA) capability for the lander. Hazard detection can be accomplished by the crew visually scanning the terrain through a window, a sensor system imaging the terrain, or some combination of both. For ALHAT, this hazard detection activity is provided by a sensor system, which either augments the crew s perception or entirely replaces the crew in the case of a robotic landing. Detecting hazards influences the trajectory design by requiring the proper perspective, range to the landing site, and sufficient time to view the terrain. Following this, the trajectory design must provide additional time to process this information and make a decision about where to safely land. During the final part of the HDA process, the trajectory design must provide sufficient margin to enable a hazard avoidance maneuver. In order to demonstrate the effects of these constraints on the landing trajectory, a tradespace of trajectory designs was created for the initial ALHAT Design Analysis Cycle (ALDAC-1) and each case evaluated with these HDA constraints active. The ALHAT analysis process, described in this paper, narrows down this tradespace and subsequently better defines the trajectory design needed to support onboard HDA. Future ALDACs will enhance this trajectory design by balancing these issues and others in an overall system design process.

Paschall, Steve↗
NASA NTRS2021

Detect-and-Avoid Safety and Operational Suitability Analysis using an Electro-Optical/Infared Sensor Model

This report documents a closed-loop analysis of an DAA system using a Electro/Optical sensor model. Safety and operational suitability metrics are computed. Results show that the safety metrics are most sensitive to the angular rate accuracy of the intruder aircraft. Trade-off between safety and operationl suitability metrics is discussed. Results from this work directly inform the requirements of an electro/optical sensors for detect-and-avoid.

Detect-and-avoid↗
NASA NTRS2017

Maintain and Regain Well Clear: Maneuver Guidance Designs for Pilots Performing the Detect-and-Avoid Task

In order to support the future expansion and integration of Unmanned Aircraft Systems (UAS), ongoing research efforts have sought to produce findings that inform the minimum display information elements required for acceptable UAS pilot response times and traffic avoidance. Previous simulations have revealed performance benefits associated with DAA displays containing predictive information and suggestive maneuver guidance tools in the form of banding. The present study investigated the impact of various maneuver guidance display configurations on detect-and-avoid (DAA) task performance in a simulated airspace environment. UAS pilots ability to maintain DAA well clear was compared between displays with either the presence or absence of green DAA bands, which indicated conflict-free flight regions. Additional display comparisons assessed pilots ability to regain DAA well clear with two different guidance presentations designed to aid in DAA well clear recovery during critical encounters. Performance implications and display considerations for future UAS DAA systems are discussed.

user interface design↗
NASA NTRS2017

Maintain and Regain Well Clear: Maneuver Guidance Designs for Pilots Performing the Detect-and-Avoid Task

In order to support the future expansion and integration of Unmanned Aircraft Systems (UAS), ongoing research efforts have sought to produce findings that inform the minimum display information elements required for acceptable UAS pilot response times and traffic avoidance. Previous simulations have revealed performance benefits associated with DAA displays containing predictive information and suggestive maneuver guidance tools in the form of banding. The present study investigated the impact of various maneuver guidance display configurations on detect-and-avoid (DAA) task performance in a simulated airspace environment. UAS pilots ability to maintain DAA well clear was compared between displays with either the presence or absence of green DAA bands, which indicated conflict-free flight regions. Additional display comparisons assessed pilots ability to regain DAA well clear with two different guidance presentations designed to aid in DAA well clear recovery during critical encounters. Performance implications and display considerations for future UAS DAA systems are discussed.

unmanned aircraft systems (UAS)↗
NASA NTRS2023

ATM-X Urban Air Mobility: Assistive Detect and Avoid for UAM Operations Safety Evaluation Metrics

This document satisfies ATM-X UAM Task UID 989 “Evaluation Report on Tactical Separation Provision Services with Advisory Detect and Avoid Safety Metrics”. The first version of this document was delivered to the UAM team on October 3, 2022, for initial revision and comments.This current version incorporates all the comments received and is being delivered to the UAM subproject for a final revision before is submitted to satisfy the L1 milestone deliverable.

UAM↗
NASA NTRS2017

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

The paper describes the Generic Resolution Advisor and Conflict Evaluator (GRACE), a novel alerting and guidance algorithm that combines flexibility, robustness, and computational efficiency. GRACE is generic since it was designed without any assumptions regarding temporal or spatial scales, aircraft performance, or its sensor and communication systems. Therefore, GRACE was adopted as a core component of the Java Architecture for Detect-And-Avoid (DAA) Extensibility and Modeling, developed by NASA as a research and modeling tool for Unmanned Aerial Systems Integration in the National Airspace System (NAS). GRACE has been used in a number of real-time and fast-time experiments supporting evolving requirements of DAA research, including parametric studies, NAS-wide simulations, human-in-the-loop experiments, and live flight tests.

Unmanned Aircraft↗
NASA NTRS2018

An Interoperability Concept for Detect and Avoid and Collision Avoidance Systems: Results from a Human-In-The-Loop Simulation

The integration of Unmanned Aircraft Systems (UAS) into the National Airspace System (NAS) poses a variety of technical challenges to UAS developers and aviation regulators. In response to growing demand for access to civil airspace in the United States, the Federal Aviation Administration (FAA) has produced a roadmap identifying key areas requiring further research and development. One such technical challenge is the development of a "detect and avoid" system (DAA) capable of providing a means of compliance with the "see and avoid" requirement in manned aviation. The purpose of the DAA system is to support the pilot, situated at a ground control station (GCS), in maintaining "DAA well clear" of nearby aircraft through the use of GCS displays and alerts. In addition to its primary function of aiding the pilot in maintaining well clear, the DAA system must also safely interoperate with existing NAS systems and operations, such as the airspace management procedures of air traffic controllers (ATC) and Collision Avoidance (CA) systems currently in use by manned aircraft, namely the Traffic alert and Collision Avoidance System (TCAS) II. It is anticipated that many UAS architectures will integrate both a DAA system and a TCAS II. It is therefore necessary to explicitly study the integration of DAA and TCAS II alerting structures and maneuver guidance formats to ensure that pilots understand the appropriate type and urgency of their response to the various alerts. This paper presents a concept of interoperability for the two systems. The concept was developed with the goal of avoiding any negative impact on the performance level of TCAS II while retaining a DAA system that still effectively enables pilots to maintain DAA well clear.

unmanned aircraft systems↗
NASA NTRS2017

DANTi: Detect and Avoid iN The Cockpit

Mid-air collision risk continues to be a concern for manned aircraft operations, especially near busy non-towered airports. The use of Detect and Avoid (DAA) technologies and draft standards developed for unmanned aircraft systems (UAS), either alone or in combination with other collision avoidance technologies, may be useful in mitigating this collision risk for manned aircraft. This paper describes a NASA research effort known as DANTi (DAA iN The Cockpit), including the initial development of the concept of use, a software prototype, and results from initial flight tests conducted with this prototype. The prototype used a single Automatic Dependent Surveillance - Broadcast (ADS-B) traffic sensor and the own aircraft's position, track, heading and air data information, along with NASA-developed DAA software to display traffic alerts and maneuver guidance to manned aircraft pilots on a portable tablet device. Initial flight tests with the prototype showed a successful DANTi proof-of-concept, but also demonstrated that the traffic separation parameter set specified in the RTCA SC-228 Phase I DAA MOPS may generate excessive false alerts during traffic pattern operations. Several parameter sets with smaller separation values were also tested in flight, one of which yielded more timely alerts for the maneuvers tested. Results from this study may further inform future DANTi efforts as well as Phase II DAA MOPS development.

Chamberlain, James↗
NASA NTRS2014

Assuring Ground-Based Detect and Avoid for UAS Operations

One of the goals of the Marginal Ice Zones Observations and Processes Experiment (MIZOPEX) NASA Earth science mission was to show the operational capabilities of Unmanned Aircraft Systems (UAS) when deployed on challenging missions, in difficult environments. Given the extreme conditions of the Arctic environment where MIZOPEX measurements were required, the mission opted to use a radar to provide a ground-based detect-and-avoid (GBDAA) capability as an alternate means of compliance (AMOC) with the see-and-avoid federal aviation regulation. This paper describes how GBDAA safety assurance was provided by interpreting and applying the guidelines in the national policy for UAS operational approval. In particular, we describe how we formulated the appropriate safety goals, defined the processes and procedures for system safety, identified and assembled the relevant safety verification evidence, and created an operational safety case in compliance with Federal Aviation Administration (FAA) requirements. To the best of our knowledge, the safety case, which was ultimately approved by the FAA, is the first successful example of non-military UAS operations using GBDAA in the U.S. National Airspace System (NAS), and, therefore, the first nonmilitary application of the safety case concept in this context.

Detect-and-Avoid↗
NASA NTRS2017

Validation of Minimum Display Requirements for a UAS Detect and Avoid System

The full integration of Unmanned Aircraft Systems (UAS) into the National Airspace System (NAS), a prerequisite for enabling a broad range of public and commercial UAS operations, presents several technical challenges to UAS developers, operators and regulators. A primary barrier is the inability for UAS pilots (situated at a ground control station, or GCS) to comply with Title 14 Code of Federal Regulations sections 91.111 and 91.113, which require pilots to see and avoid other aircraft in order to maintain well clear. The present study is the final in a series of human-in-the-loop experiments designed to explore and test the various display and alerting requirements being incorporated into the minimum operational performance standards (MOPS) for a UAS-specific detect and avoid system that would replace the see and avoid function required of manned aircraft. Two display configurations were tested - an integrated display and a standalone display - and their impact on pilot response times and ability to maintain DAA well clear were compared. Results indicated that the current draft of the MOPS result in high-level performance and did not meaningfully differ by display configuration.

unmanned aircraft systems↗
NASA NTRS2019

Detect-and-Avoid Alerting Performance for High-Speed UAS and Non-Cooperative Aircraft

This paper presents a set of experiments designed to assess the viability of using a smaller Detect and Avoid (DAA) volume for large Unmanned Aircraft Systems (UAS) when they are trying to remain well clear of non-cooperative visual flight rules (VFR) aircraft, in compliance with Federal regulations. The current DAA volume was defined for both cooperative and non-cooperative VFR traffic by the work of RTCA Special Committee 228 in 2017, in what is referred to in this paper as the Phase 1 standards. Subsequent work by the committee has been focused on enabling operations by smaller UAS that cannot carry the heavy radars required for the Phase 1 DAA Minimum Operational Performance Standards (MOPS). The work discussed in this paper will explore whether a Phase 1 UAS using a Phase 1 radar can use the reduced non-cooperative DAA alerting volume being studied for smaller, slower Phase 2 UAS without significantly degrading system safety. The study uses UAS models and background traffic from previous Phase 1 and Phase 2 research to run an unmitigated simulation that will examine alerting performance using different DAA well clear definitions. The primary metrics are also tied to the alerting performance of the DAA system, and include average alerting times, probabilities of missed and late alerts, and the probability of a near mid-air collision given a loss of "well clear," as defined by the DAA system. Results are expected to help RTCA make the determination whether or not the DAA well clear definition for Phase 1 UAS can be reduced for non-cooperative VFR aircraft.

Cone, Andrew C.↗
NASA NTRS2019

Detect-and-Avoid Alerting Performance for High-Speed UAS and Non-Cooperative Aircraft

This paper presents a set of experiments designed to assess the viability of using a smaller Detect and Avoid (DAA) volume for large Unmanned Aircraft Systems (UAS) when they are trying to remain well clear of non-cooperative visual flight rules (VFR) aircraft, in compliance with Federal regulations. The current DAA volume was defined for both cooperative and non-cooperative VFR traffic by the work of RTCA (Radio Technical Commission for Aeronautics) Special Committee 228 in 2017, in what is referred to in this paper as the Phase 1 standards. Subsequent work by the committee has been focused on enabling operations by smaller UAS that cannot carry the heavy radars required for the Phase 1 DAA Minimum Operational Performance Standards (MOPS). The work discussed in this paper will explore whether a Phase 1 UAS using a Phase 1 radar can use the reduced non-cooperative DAA alerting volume being studied for smaller, slower Phase 2 UAS without significantly degrading system safety. The study uses UAS models and background traffic from previous Phase 1 and Phase 2 research to run an unmitigated simulation that will examine alerting performance using different DAA well clear definitions. The primary metrics are also tied to the alerting performance of the DAA system, and include average alerting times, probabilities of missed and late alerts, and the probability of a near mid-air collision given a loss of "well clear," as defined by the DAA system. Results are expected to help RTCA make the determination whether or not the DAA well clear definition for Phase 1 UAS can be reduced for non-cooperative VFR aircraft.

UAS↗
NASA NTRS2017

The Effects of Severity of Losses of Well Clear on Minimum Operations Performance Standards End-To-End Verification and Validation Simulation Study for Integrating Unmanned Aircraft Systems into the National Airspace System Using Detect and Avoid Systems

As Unmanned Aircraft Systems (UAS) make their way to mainstream aviation operations within the National Airspace System (NAS), research efforts are underway to develop a safe and effective environment for their integration into the NAS. Detect and Avoid (DAA) systems are required to account for the lack of “eyes in the sky” due to having no human on-board the aircraft. The technique, results, and lessons learned from a detailed End-to-End Verification and Validation (E2-V2) simulation study of a DAA system representative of RTCA Special Committee(SC)-228’s proposed Phase I DAA Minimum Operational Performance Standards (MOPS), based on specific test vectors and encounter cases, will be presented in this paper.

Ghatas, Rania W.↗
NASA NTRS1992

Autonomous hazard detection and avoidance

During GFY 91, Draper Laboratory was awarded a task by NASA-JSC under contract number NAS9-18426 to study and evaluate the potential for achieving safe autonomous landings on Mars using an on-board autonomous hazard detection and avoidance (AHDA) system. This report describes the results of that study. The AHDA task had four objectives: to demonstrate, via a closed-loop simulation, the ability to autonomously select safe landing sites and the ability to maneuver to the selected site; to identify key issues in the development of AHDA systems; to produce strawman designs for AHDA sensors and algorithms; and to perform initial trade studies leading to better understanding of the effect of sensor/terrain/viewing parameters on AHDA algorithm performance. This report summarizes the progress made during the first year, with primary emphasis on describing the tools developed for simulating a closed-loop AHDA landing. Some cursory performance evaluation results are also presented.

Pien, Homer↗
NASA NTRS2019

A Detect and Avoid System in the Context of Multiple-Unmanned Aircraft Systems Operations

NASA's Unmanned Aircraft Systems Integration into the National Airspace System (UAS in the NAS) project examines the technical barriers associated with the operation of UAS in civil airspace. For UAS, the removal of the pilot from onboard the aircraft has eliminated the ability of the ground-based pilot in command (PIC) to use out-the-window visual information to make judgements about a potential threat of a loss of well clear with another aircraft. NASA's Phase 1 research supported the development of a Detect and Avoid (DAA) system that supports the ground-based pilot's ability to detect potential traffic conflicts and determine a resolution maneuver, but existing display/alerting requirements did not account for multiple UAS control (1:N). Demands for increased scalability of UAS in the NAS operations are expected to create a need for simultaneous control of UAs, and thus, a new DAA HMI design will likely be necessary. Previous research, however, has found performance degradations as the number of vehicles under operator control has increased. The purpose of the current human-in-the-loop (HITL) simulation was to examine the viability of 1:N operations with the Phase 1 DAA alerting and guidance. Sixteen UAS pilots flew three scenarios with varying number of UAs under their control (1:1, 1:3, 1:5). In addition to their supervisory and sensor mission responsibilities, pilots were to utilize the DAA system to remain DAA well clear (DWC) during scripted conflicts of mixed severity. Measured response times, separation performance, mission task data, and subjective feedback were collected to assess how the multi-UAS control configuration impacted pilots' ability to maintain DAA well clear and perform the mission tasks. Overall, the DAA system proved surprisingly adaptive to multi-UAS control for preventing losses of DAA well clear (LoDWC). The findings suggest that, while multi-UAS operators are able to maintain safe separation (DWC) from other traffic, their ability to efficiently perform missions drastically decreases with their number of controlled vehicles. Pilot feedback indicated that, for this context, the use of automation support tools for completing and managing mission tasks would be appropriate and desired, especially for ensuring efficient use of assets. Finally, human-machine interface (HMI) design considerations for multi-UAS operations are discussed.

Monk, Kevin J.↗
NASA NTRS2016

An Inertial Dual-State State Estimator for Precision Planetary Landing with Hazard Detection and Avoidance

The navigation filter architecture successfully deployed on the Morpheus flight vehicle is presented. The filter was developed as a key element of the NASA Autonomous Landing and Hazard Avoidance Technology (ALHAT) project and over the course of 15 free fights was integrated into the Morpheus vehicle, operations, and flight control loop. Flight testing completed by demonstrating autonomous hazard detection and avoidance, integration of an altimeter, surface relative velocity (velocimeter) and hazard relative navigation (HRN) measurements into the onboard dual-state inertial estimator Kalman flter software, and landing within 2 meters of the vertical testbed GPS-based navigation solution at the safe landing site target. Morpheus followed a trajectory that included an ascent phase followed by a partial descent-to-landing, although the proposed filter architecture is applicable to more general planetary precision entry, descent, and landings. The main new contribution is the incorporation of a sophisticated hazard relative navigation sensor-originally intended to locate safe landing sites-into the navigation system and employed as a navigation sensor. The formulation of a dual-state inertial extended Kalman filter was designed to address the precision planetary landing problem when viewed as a rendezvous problem with an intended landing site. For the required precision navigation system that is capable of navigating along a descent-to-landing trajectory to a precise landing, the impact of attitude errors on the translational state estimation are included in a fully integrated navigation structure in which translation state estimation is combined with attitude state estimation. The map tie errors are estimated as part of the process, thereby creating a dual-state filter implementation. Also, the filter is implemented using inertial states rather than states relative to the target. External measurements include altimeter, velocimeter, star camera, terrain relative navigation sensor, and a hazard relative navigation sensor providing information regarding hazards on a map generated on-the-fly.

Bishop, Robert H.↗