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At least 217 records · Page 12

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NASA NTRS2017

Safely Enabling UAS Operations in Low-Altitude Airspace

NASA is developing a system to safely enable low altitude unmanned aerial system (UAS) operations. The system is referred to as UAS Traffic Management (UTM). The UTM will safely enable a variety of business models and multiple operations in the same airspace. The UTM will provide services such as airspace configuration and geo-fencing, weather and wind integration, demand-capacity imbalance management, and separation management, and contingency management. The UTM research and development has been conducted in collaboration with many in industry, academia, and government. The UTM system will evolve through four builds. Each build will be collaboratively tested with partners. The final prototype will be available for persistent daily use of UAS operations beyond visual line of sight (BVLOS).

low-altitude airspace↗

NASA NTRS2017

Requirements for an Integrated UAS CNS Architecture

Communications, Navigation and Surveillance (CNS) requirements must be developed in order to establish a CNS architecture supporting Unmanned Air Systems integration in the National Air Space (UAS in the NAS). These requirements must address cybersecurity, future communications, satellite-based navigation and APNT, and scalable surveillance and situational awareness. CNS integration, consolidation and miniaturization requirements are also important to support the explosive growth in small UAS deployment. Air Traffic Management (ATM) must also be accommodated to support critical Command and Control (C2) for Air Traffic Controllers (ATC). This document therefore presents UAS CNS requirements that will guide the architecture.

Templin, Fred L.↗

NASA NTRS2017

Implicitly Coordinated Detect and Avoid Capability for Safe Autonomous Operation of Small UAS

As the airspace becomes increasingly shared by autonomous small Unmanned Aerial Systems (UAS), there would be a pressing need for coordination strategies so that aircraft can safely and independently maneuver around obstacles, geofences, and traffic aircraft. Explicitly coordinating resolution strategies for small UAS would require additional components such as a reliable vehicle-to-vehicle communication infrastructure and standardized protocols for information exchange that could significantly increase the cost of deploying small UAS in a shared airspace. This paper explores a novel approach that enables multiple aircraft to implicitly coordinate their resolution maneuvers. By requiring all aircraft to execute the proposed approach deterministically, it is possible for all of them to implicitly agree on the region of airspace each will be occupying in a given time interval. The proposed approach lends itself to the construction of a suitable feedback mechanism that enables the real-time execution of an implicitly conflict-free path in a closed-loop manner dealing with uncertainties in aircraft speed. If a network infrastructure is available, the proposed approach can also exploit the benefits of explicit information.

Balachandran, Swee↗

NASA NTRS2017

Safely Enabling UAS Operations in Low-Altitude Airspace

low-altitude airspace↗

NASA NTRS2017

Safely Enabling UAS Operations in Low-Altitude Airspace

low-altitude airspace↗

NASA NTRS2016

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

The advantages of utilizing an airship as an airborne carrier for support and deployment of Unmanned Aircraft Systems (UAS) are examined. Whether as a stand-alone platform or in concert with conventional aircraft, the airship UAS carrier provides a number of compelling benefits for both military and civilian missions. As a mobile base it can remain operational despite political fallout that may render ground or ocean based UAS sites unavailable. It offers the psychological impact of a power projection tool that has few geographical limits, and holds promise as a new method for cost-saving intelligence gathering. It is also adaptable for civilian variants for supporting: emergency response, security/surveillance, delivery of medical/food supplies, as well as commercial package delivery to metropolitan and remote communities. This paper presents the background on airship-aircraft operations, and explores the general airship carrier concept. Additionally, a catalog of contemporary technologies available to support the airship carrier concept are discussed, and essential elements for an Air-Station Development program proposed.

Hochstetler, Ronald D.↗

NASA NTRS2014

UAS Contingency Management: The Effect of Different Procedures on ATC in Civil Airspace Operations

Current study examined the impact of four, currently-employed, unmanned aerial system (UAS) contingency procedures on air traffic controller (ATC) workload and performance. Controllers managed a Terminal Radar Approach Control (TRACON) sector while a single UAS passed through their sector. In four of the five scenarios, the UAS was scripted to experience an emergency (e.g., loss of command and control link, sudden drop in oil pressure) and then execute one of four possible contingency maneuvers. The fifth scenario was a baseline and contained no emergency. Results showed no significant differences in performance or workload among the four the study's design discussed.

Contingency Management↗

NASA NTRS2016

Developing an Adaptable NextGen Interface for the UAS Ground Control Station

Motivation: NextGen traffic infrastructure is in place to support manned aircraft operations. However, the UAS ground control station (GCS) adds a data interface requirement that is not yet fully accounted for in the NextGen data service architecture. Existing NextGen data service is focused on aircraft, not the GCS. Smaller UAS may not have the payload or power capacity to support the additional equipment. Innovation: Provide a mechanism for a UAS regardless of size, payload, bandwidth, and power capacity to gain access to NextGen data-sourced traffic information in real-time.

LVC↗

NASA NTRS2019

TCL3 UTM (UAS Traffic Management) Flight Tests, Airspace Operations Laboratory (AOL) Report

The Technology Capability Level-3 (TCL3) flight tests were conducted at six different test sites located across the USA from March to May of 2018. The campaign resulted in over 830 data collection flights using 28 different aircraft and involving 20 flight crews. Flights not only varied in duration, but also in the environments and terrains over which they flew. The TCL3 tests highlighted four different types of tests: three tests focused on Communication, Navigation and Surveillance (CNS); six tests focused on Sense and Avoid (SAA) technologies; six tests focused on USS Data and Information Exchange (DAT); and five tests focused on exploring fundamental Concepts of the project (CON). This document presents data collected during the TCL3 tests that informed the operator’s experiences—the quality of the unmanned aerial system (UAS) Service Supplier (USS) information that the operator was provided with, the usefulness of this information, and the usability of the automation, both while airborne and on the ground. It is intended to complement the reports written by the test sites and the quantitative reports and presentations of the UAS Traffic Management (UTM) project. With the goal of instructing what the minimum information requirements and/or best practices might be in TCL3 operations, the driving enquiry was: How do you get the information you need, when you need it, to successfully fly a UAS in UTM airspace? This enquiry touches on two requirements for displays, which are to provide adequate situation awareness (SA) and to share information through a USS. The six test sites participating in the TCL3 tests flew a subset of the 20 tests (outlined above), with most sites working on a subset of each of the four types: Communications, Navigation and Surveillance (CNS); DAT; CON; and Sense and Avoid (SAA). The, mainly qualitative, data addressed in this report was collected by the AOL (Airspace Operations Laboratory) both on-site and remotely for each test. The data consists of the contents of end-of-day debriefs, end-of-day surveys, observer notes, and flight test information, all submitted as part of the Data Management Plan (DMP).

Martin, Lynne↗

NASA NTRS2020

UAS Service Supplier Network Performance

This report summarizes the performance of Unmanned Aircraft System (UAS) Service Suppliers (USS) in the Technical Capability Level 4 (TCL4) flight test performed by NASA and its partners in support of the UAS Traffic Management (UTM) concept. TCL4 is the final in a series of TCL demonstrations of a traffic management system for small UAS (sUAS). All demonstrations have been executed in collaboration with industry partners. The [FAA 2018] UTM Concept of Operations document describes UTM as:...the manner in which the FAA will support operations for predominantly sUAS operating in low altitude airspace. UTM utilizes industry’s ability to supply services under FAA’s regulatory authority where these services do not currently exist. It is a community-based traffic management system, where the Operators are responsible for the coordination, execution, and management of operations, with rules of the road established by FAA. UTM is designed to support the demand and expectations for a broad spectrum of operations with ever-increasing complexity and risk. UTM should be considered a collection of services rather than a monolithic application. The following section describes the architecture at a high level. For further insight, the FAA’s concept document [FAA 2018] or NASA’s earlier concept publication [NASA 2016] should be consulted.

Rios, Joseph L.↗

NASA NTRSDate not supplied

UAS Pilot Performance Comparisons with Different Low Size, Weight and Power Sensor Ranges

The present study evaluated the performance of UAS pilots under four simulated low size, weight, and power (SwaP) sensor ranges: 1.5nmi, 2.0nmi, 2.5nmi, and 3.0nmi. Nine active-duty UAS pilots responded to scripted DAA conflicts against non-cooperative intruders while flying a simulated RQ-7 Shadow at varied speeds along a pre-filed flight path in Class E airspace. Findings revealed a linear effect of sensor range on alerting time and separation performance, with nearly every DAA well clear (DWC) violation and all Near Mid-Air Collision (NMAC) events occurring below 2.5nmi. Response time differences at these reduced ranges were negligible due to the high frequency of warning-level alerts that require an immediate response. Since caution alert duration was truncated to some degree by each tested declaration range, pilots were often unable to coordinate their avoidance maneuvers with ATC prior to their uploads. Nonetheless, the 2.5nmi range allowed minimum alerting times that were sufficient for acceptable pilot performance. The study findings will inform DAA system requirements for UAS with alternative surveillance equipment and aircraft performance capabilities. Implications on DAA display and sensor requirements are discussed.

unmanned aircraft systems↗

NASA NTRSDate not supplied

UAS Pilot Performance Comparisons with Different Low Size, Weight and Power Sensor Ranges

The present study evaluated the performance of UAS pilots under four simulated low size, weight, and power (SwaP) sensor ranges: 1.5nmi, 2.0nmi, 2.5nmi, and 3.0nmi. Nine active-duty UAS pilots responded to scripted DAA conflicts against non-cooperative intruders while flying a simulated RQ-7 Shadow at varied speeds along a pre-filed flight path in Class E airspace. Findings revealed a linear effect of sensor range on alerting time and separation performance, with nearly every DAA well clear (DWC) violation and all Near Mid-Air Collision (NMAC) events occurring below 2.5nmi. Response time differences at these reduced ranges were negligible due to the high frequency of warning-level alerts that require an immediate response. Since caution alert duration was truncated to some degree by each tested declaration range, pilots were often unable to coordinate their avoidance maneuvers with ATC prior to their uploads. Nonetheless, the 2.5nmi range allowed minimum alerting times that were sufficient for acceptable pilot performance. These findings will inform DAA system requirements for UAS with alternative surveillance equipment and aircraft performance capabilities. Implications on DAA display and sensor requirements are discussed.

unmanned aircraft systems↗

NASA NTRS2020

UAS Pilot Performance Comparisons with Different Low Size, Weight and Power Sensor Ranges

The present study evaluated the performance of UAS pilots under four simulated low size, weight, and power (SwaP) sensor ranges: 1.5nmi, 2.0nmi, 2.5nmi, and 3.0nmi. Nine active-duty UAS pilots responded to scripted DAA conflicts against non-cooperative intruders while flying a simulated RQ-7 Shadow at varied speeds along a pre-filed flight path in Class E airspace. Findings revealed a linear effect of sensor range on alerting time and separation performance, with nearly every DAA well clear (DWC) violation and all Near Mid-Air Collision (NMAC) events occurring below 2.5nmi. Response time differences at these reduced ranges were negligible due to the high frequency of warning-level alerts that require an immediate response. Since caution alert duration was truncated to some degree by each tested declaration range, pilots were often unable to coordinate their avoidance maneuvers with ATC prior to their uploads. Nonetheless, the 2.5nmi range allowed minimum alerting times that were sufficient for acceptable pilot performance. These findings will inform DAA system requirements for UAS with alternative surveillance equipment and aircraft performance capabilities. Implications on DAA display and sensor requirements are discussed.

unmanned aircraft systems↗

NASA NTRS2021

Assuring Intelligent Systems: Contingency Management for UAS

Unmanned aircraft systems (UAS) collaborate with humans to operate in diverse, safety-critical applications. However, assurance technologies need to be integrated into the design process in order to guarantee safe behavior, thereby enabling UAS operations in the National Airspace System (NAS). In this paper, formal methods are integrated with learning-enabled systems representations. The generation and representation of knowledge are captured via monadic second-order logic rules in the cognitive architecture Soar. These rules are translated into timed automata, and a proof of correctness for the translation is provided so that safety and liveness properties can be checked in the formal verification environment Uppaal. This approach is agnostic to the learning mechanism used to generate the learned rules (e.g., chunking, etc.). An example of a fault-tolerant, learning-enabled UAS deciding which of four contingency procedures to execute under a lost link scenario while overflying an urban area is used to illustrate the approach.

Intelligent Systems↗

NASA NTRS2021

Automated UAS Measurements of Reflectance and Solar Induced Florescence (SIF) for Assessment of the Dynamics in Photosynthetic Function, Application for Maize (Zea Mays L.) in Greenbelt, Maryland, US

To enable monitoring of the parameters governing photosynthesis at the temporal frequency relevant to their dynamics and at a spatial scale that allows practical assessment and management there is a strong need for advancement in the UAS remote sensing methods and instruments. Currently, no single sensor can provide data at the desired high temporal, spectral and spatial resolutions. Our field measurements obtained using the integrated UAS Piccolo system during the summers of 2017 and 2018 demonstrate that science quality reflectance and solar induced fluorescence (SIF) data can be retrieved with high temporal frequency using small Unmanned Aerial Systems (UAS). The implemented approach facilitates consistent data comparisons in space and time and facilitates their integration with other spectral satellite and airborne data.

Petya Campbell↗

NASA NTRS2021

Dense 3D-Reconstruction from Monocular Image Sequences for Computationally Constrained UAS

The ability to find safe landing sites over complex 3D terrain is an essential safety feature for fully autonomous small unmanned aerial systems (UAS), which requires on-board perception for 3D reconstruction and terrain analysis if the overflown terrain is unknown. This is a challenge for UAS that are limited in size, weight and computational power, such as small rotorcrafts executing autonomous missions on Earth, or in planetary applications such as the Mars Helicopter. For such a computationally constraint system, we propose a structure from motion approach that uses inputs from a single downward facing camera to produce dense point clouds of the overflown terrain in real time. In contrast to existing approaches, our method uses metric pose information from a visual-inertial odometry algorithm as camera pose priors, which allows deploying a fast pose refinement step to align camera frames such that a conventional stereo algorithm can be used for dense 3D reconstruction. We validate the performance of our approach with extensive evaluations in simulation, and demonstrate the feasibility with data from UAS flights.

Brockers, Roland↗

NASA NTRS2021

Automated Uas Measurements of Reflectance and Solar Induced Florescence (SIF) for Assessment Of the Dinamics in Photosynthetic Function, Application for Maze (Zea Mays L.) in Greenbelt, Maryland, Us

For accurate assessment of vegetation function there is a strong need for advancement in the remote sensing methods and instruments, to enable monitoring of the parameters governing photosynthesis at the temporal frequency relevant to their dynamics and at a spatial scale that allows practical assessment and management. Currently, no single sensor can provide data at the desired high temporal, spectral and spatial resolutions. Our field measurements obtained using the integrated UAS Piccolo system during the summers of2017 and 2018 demonstrate that science quality reflectance and solar induced fluorescence (SIF) data can be retrieved with high temporal frequency using small Unmanned Aerial Systems (UAS). The implemented approach facilitates data comparisons through space and time, and the integration with other spectral satellite and airborne data. This investigation contributes for bridging the gap in Earth observation between field and airborne measurements by implementing autonomous methods for obtaining high temporal frequency spectroscopy measurements from an Unmanned Aerial Systems (UAS) at various illumination conditions. An advancement in the Intelligent Payload Module (IPM) facilitated the implementation of an optimization workflow to collect spectral data for characterizing vegetation reflectance and solar induced fluorescence (SIF).

Petya Campbell↗

NASA NTRSDate not supplied

Assessing the Use of UAS-Related Terms in ASRS Using Seed Topic Modeling

Context: The NASA Aviation Safety Reporting System (ASRS) is a voluntary confidential system that disseminates reports received from personnel involved in aviation operations after de-identifying them. These reports are used by the community to improve overall aviation system safety. Aim: We propose and execute an experiment to assess the use of seed term topic modeling over the database narratives to identify Unmanned Aircraft System (UAS) reports. The use of seed term topic modeling enables users to identify groups of conceptually similar narratives associated to a topic of their interest. Method: We use a collection of narratives, expert-selected words, and report metadata that separates UAS from non-UAS reports to assess if seed topic modeling can be used to improve ASRS searches. Results: For simpler queries, seed topic search observes a higher recall and lower precision than the existing DBOL (DataBase OnLine) search in operation. However, the best results are obtained when seed topic search is used as a search suggestion system to be executed on the DBOL. Conclusion: Utilizing a combination of both the existing method and the proposed method, users can expand their search vocabulary about subjects of interest while improving the quality of results.

Text Mining↗