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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 NTRS2014

NASA's UAS Integration into the NAS: A Report on the Human Systems Integration Phase 1 Simulation Activities

In 2011 the National Aeronautics and Space Administration (NASA) began a five-year Project to address the technical barriers related to routine access of Unmanned Aerial Systems (UAS) in the National Airspace System (NAS). Planned in two phases, the goal of the first phase was to lay the foundations for the Project by identifying those barriers and key issues to be addressed to achieve integration. Phase 1 activities were completed two years into the five-year Project. The purpose of this paper is to review activities within the Human Systems Integration (HSI) subproject in Phase 1 toward its two objectives: 1) develop GCS guidelines for routine UAS access to the NAS, and 2) develop a prototype display suite within an existing Ground Control Station (GCS). The first objective directly addresses a critical barrier for UAS integration into the NAS - a lack of GCS design standards or requirements. First, the paper describes the initial development of a prototype GCS display suite and supporting simulation software capabilities. Then, three simulation experiments utilizing this simulation architecture are summarized. The first experiment sought to determine a baseline performance of UAS pilots operating in civil airspace under current instrument flight rules for manned aircraft. The second experiment examined the effect of currently employed UAS contingency procedures on Air Traffic Control (ATC) participants. The third experiment compared three GCS command and control interfaces on UAS pilot response times in compliance with ATC clearances. The authors discuss how the results of these and future simulation and flight-testing activities contribute to the development of GCS guidelines to support the safe integration of UAS into the NAS. Finally, the planned activities for Phase 2, including an integrated human-in-the-loop simulation and two flight tests are briefly described.

National Airspace System↗

NASA NTRS2013

An Application of UAV Attitude Estimation Using a Low-Cost Inertial Navigation System

Unmanned Aerial Vehicles (UAV) are playing an increasing role in aviation. Various methods exist for the computation of UAV attitude based on low cost microelectromechanical systems (MEMS) and Global Positioning System (GPS) receivers. There has been a recent increase in UAV autonomy as sensors are becoming more compact and onboard processing power has increased significantly. Correct UAV attitude estimation will play a critical role in navigation and separation assurance as UAVs share airspace with civil air traffic. This paper describes attitude estimation derived by post-processing data from a small low cost Inertial Navigation System (INS) recorded during the flight of a subscale commercial off the shelf (COTS) UAV. Two discrete time attitude estimation schemes are presented here in detail. The first is an adaptation of the Kalman Filter to accommodate nonlinear systems, the Extended Kalman Filter (EKF). The EKF returns quaternion estimates of the UAV attitude based on MEMS gyro, magnetometer, accelerometer, and pitot tube inputs. The second scheme is the complementary filter which is a simpler algorithm that splits the sensor frequency spectrum based on noise characteristics. The necessity to correct both filters for gravity measurement errors during turning maneuvers is demonstrated. It is shown that the proposed algorithms may be used to estimate UAV attitude. The effects of vibration on sensor measurements are discussed. Heuristic tuning comments pertaining to sensor filtering and gain selection to achieve acceptable performance during flight are given. Comparisons of attitude estimation performance are made between the EKF and the complementary filter.

Eure, Kenneth W.↗

NASA NTRS2007

NASA Global Hawk: A Unique Capability for the Pursuit of Earth Science

For more than 2 years, the NASA Dryden Flight Research Center has been preparing for the receipt of two Advanced Concept Technology Demonstration Global Hawk air vehicles from the United States Air Force. NASA Dryden intends to establish a Global Hawk Project Office, which will be responsible for developing the infrastructure required to operate this unmanned aerial system and establishing a trained maintenance and operations team. The first flight of a NASA Global Hawk air vehicle is expected to occur in 2008. The NASA Global Hawk system can be used by a variety of customers, including U.S. Government agencies, civilian organizations, universities, and state governments. A combination of the vehicle s range, endurance, altitude, payload power, payload volume, and payload weight capabilities separates the Global Hawk unmanned aerial system from all other platforms available to the science community.

Naftel, J. Chris↗

NASA NTRS2007

NASA Global Hawk: A Unique Capability for the Pursuit of Earth Science

For more than 2 years, the NASA Dryden Flight Research Center has been preparing for the receipt of two Advanced Concept Technology Demonstration Global Hawk air vehicles from the United States Air Force. NASA Dryden intends to establish a Global Hawk Project Office, which will be responsible for developing the infrastructure required to operate this unmanned aerial system and establishing a trained maintenance and operations team. The first flight of a NASA Global Hawk air vehicle is expected to occur in 2008. The NASA Global Hawk system can be used by a variety of customers, including U.S. Government agencies, civilian organizations, universities, and state governments. Initially, the main focus of the research activities is expected to be Earth science related. A combination of the vehicle s range, endurance, altitude, payload power, payload volume, and payload weight capabilities separates the Global Hawk unmanned aerial system from all other platforms available to the science community. This report describes the NASA Global Hawk system and current plans for the NASA air vehicle concept of operations, and provides examples of potential missions with an emphasis on science missions.

Naftel, J. Chris↗

NASA NTRS2010

Hardware Implementation of COTS Avionics System on Unmanned Aerial Vehicle Platforms

Unmanned Aerial Vehicles (UAVs) can serve as low cost and low risk platforms for flight testing in Aeronautics research. The NASA Exploration Aerial Vehicle (EAV) and Experimental Sensor-Controlled Aerial Vehicle (X-SCAV) UAVs were developed in support of control systems research at NASA Ames Research Center. The avionics hardware for both systems has been redesigned and updated, and the structure of the EAV has been further strengthened. Preliminary tests show the avionics operate properly in the new configuration. A linear model for the EAV also was estimated from flight data, and was verified in simulation. These modifications and results prepare the EAV and X-SCAV to be used in a wide variety of flight research projects.

Yeh, Yoo-Hsiu↗

NASA NTRS2019

Usability Test of a Prototype UAS Awareness Interface for Public Users

A tool to give the public a window into Unmanned Aerial Systems (UAS) Traffic Management (UTM) operations was created from an existing data collection tool. The interface included a map and a table showing details about UAS operations that could be queried in a number of ways. Eleven participants attended the study, successfully completing a 19-item task set in about 30 minutes. They correctly found information for 87% of the non-subjective tasks at a rate of around a minute per task, and rated the usability of the tool at the end of the session above the industry benchmark. Participants gave favorable reviews of the "public portal tool", even reporting that they would be satisfied with less information that it presented. There were one or two elements of the display that users found distracting and some navigation functions that need improvement, but on balance, the public representatives liked the features they saw in, and had few criticisms of, the public portal tool. One important issue for the small Unmanned Aerial System community to resolve will be how much or how little information should be available about UTM operations to members of the public.

Martin, Lynne H.↗

NASA NTRS2021

Anomaly Detection, Active Learning, Precursor Identification,and Human Knowledge for Autonomous System Safety

The project Autonomy Teaming and TRajectories for ComplexTrusted Operational Reliability (ATTRACTOR) researched and developed Artificial Intelligence with application to multi-Unmanned Aerial Systems (UAS) missions. Such missions, like other complex systems-of-systems, are likely to have previously-unknown, safety relevant anomalies occur due to many possible factors including system failures or degradations, emergent behavior, changes in the environment in which the systems operate, changes in the way the systems are operated. We discuss the application of anomaly detection, active learning, and precursor identification to identify such anomalies and the conditions under which they are more likely to appear. We demonstrate results on simulated multi-UAS missions that show promise to be applied to real missions.

machine learning↗

NASA NTRS2011

Self-Contained Avionics Sensing and Flight Control System for Small Unmanned Aerial Vehicle

A self-contained avionics sensing and flight control system is provided for an unmanned aerial vehicle (UAV). The system includes sensors for sensing flight control parameters and surveillance parameters, and a Global Positioning System (GPS) receiver. Flight control parameters and location signals are processed to generate flight control signals. A Field Programmable Gate Array (FPGA) is configured to provide a look-up table storing sets of values with each set being associated with a servo mechanism mounted on the UAV and with each value in each set indicating a unique duty cycle for the servo mechanism associated therewith. Each value in each set is further indexed to a bit position indicative of a unique percentage of a maximum duty cycle for the servo mechanism associated therewith. The FPGA is further configured to provide a plurality of pulse width modulation (PWM) generators coupled to the look-up table. Each PWM generator is associated with and adapted to be coupled to one of the servo mechanisms.

Shams, Qamar A.↗

NASA NTRSDate not supplied

Miniature Unmanned Airborne Sunphotometer for Sun-Tracking Atmospheric Research (muSSTAR)

The miniature unmanned Airborne Sunphotometer for Sun-Tracking Atmospheric Research (muSSTAR) will provide a link between local aerosols in the boundary layer and the global measurements of Aerosol Optical Thickness (AOT). We describe a path towards a prototype small airborne sunphotometer hosted on an unmanned aerial system for enabling air-quality and climate science by profiling the lower atmospheric boundary layer over land and boundary layer in coastal environments. This project aims to miniaturize NASA Ames’ world-leading instrumentation for use on unmanned aerial vehicles.

aerosol↗

NASA NTRS2007

CIRA: Cooperative Institute for Research in the Atmosphere Newsletter, Volume 28, Fall 2007

The articles in this issue of the Cooperative Institute for Research in the Atmosphere (CIRA) Newsletter are: "Unmanned Aerial Systems: An Overview of NOAA's Unmanned Aircraft System Program," "International Activities: Weather Briefings and Training Via the Internet," "Cloudsat's One-Year Anniversary: An Abundance of Exciting New Cloud Observations," and "The Migration of NCAR'S Auto-Nowcaster into NWS AWIPS."

McInnis-Efaw, Mary↗

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

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 NTRS2014

UAS Measured Response: The Effect of GCS Control Mode Interfaces on Pilot Ability to Comply with ATC Clearances

The present study examines the effects of three different control mode interfaces on unmanned aerial system (UAS) pilots ability to comply with air traffic controller traffic clearances. Pilots controlled a simulated UAS with a waypoint-only interface, an auto-pilot interface and a manual, stick and throttle interface. Results indicate that pilots are best able to get in-the-loop when provided with auto-pilot and manual control inputs. Limitations to the present study and future analyses are discussed.

Measured Response↗

NASA NTRS2017

GPS/Optical/Inertial Integration for 3D Navigation Using Multi-Copter Platforms

In concert with the continued advancement of a UAS traffic management system (UTM), the proposed uses of autonomous unmanned aerial systems (UAS) have become more prevalent in both the public and private sectors. To facilitate this anticipated growth, a reliable three-dimensional (3D) positioning, navigation, and mapping (PNM) capability will be required to enable operation of these platforms in challenging environments where global navigation satellite systems (GNSS) may not be available continuously. Especially, when the platform's mission requires maneuvering through different and difficult environments like outdoor opensky, outdoor under foliage, outdoor-urban and indoor, and may include transitions between these environments. There may not be a single method to solve the PNM problem for all environments. The research presented in this paper is a subset of a broader research effort, described in [1]. The research is focused on combining data from dissimilar sensor technologies to create an integrated navigation and mapping method that can enable reliable operation in both an outdoor and structured indoor environment. The integrated navigation and mapping design is utilizes a Global Positioning System (GPS) receiver, an Inertial Measurement Unit (IMU), a monocular digital camera, and three short to medium range laser scanners. This paper describes specifically the techniques necessary to effectively integrate the monocular camera data within the established mechanization. To evaluate the developed algorithms a hexacopter was built, equipped with the discussed sensors, and both hand-carried and flown through representative environments. This paper highlights the effect that the monocular camera has on the aforementioned sensor integration scheme's reliability, accuracy and availability.

Dill, Evan T.↗

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 NTRS2017

Safe Autonomous Flight Environment (SAFE50) for the Notional Last 50 ft of Operation of 55 lb Class of UAS

The most difficult phase of small Unmanned Aerial System (sUAS) deployment is autonomous operations below the notional 50 ft in urban landscapes. Understanding the feasibility of safely flying sUAS autonomously below 50 ft is a game changer for many civilian applications. This paper outlines three areas of research currently underway which address key challenges for flight in the urban landscape. These are: (1) Off-line and On-board wind estimation and accommodation; (2) Real-time trajectory planning via characterization of obstacles using a LIDAR; (3) On-board information fusion for real-time decision-making and safe trajectory generation.

Autonomy↗