Results for “small Unmanned Aircraft System (sUAS)” — Page 4

NASA NTRSDate not supplied

Monocular Ranging for Small Unmanned Aerial Systems in the Far-Field

Recent proliferation of small Unmanned Aerial Systems (sUAS) applications requires onboard collision avoidance systems to mitigate the risk of collision with non-cooperative aircraft and manned aircraft, which may not see sUAS in time to perform an avoidance maneuver. An attractive avenue for onboard collision avoidance is the utilization of machine vision cameras due to their low size, weight and power (SWaP) requirements. In this paper, we characterize the range performance of a machine vision system developed in-house and mounted onto an sUAS. The technique was designed to estimate the performance of a sense-and-avoid system to ensure that the sensing components meet the well-clear requirements for the chosen platform and avoidance strategy. Experimental flight-test data was acquired from test-flights flown along multiple collision geometries for two intruders: a general Aviation (GA) aircraft and a fixed-wing sUAS. The ownship and both intruders were instrumented with inertial navigation systems (INS) recording position and attitude information. The range at first detection, 𝑹𝟎, was extracted from in-flight imagery of head-on collision course geometry synchronized with INS data from both aircraft and ground-truth values extracted from the raw imagery. This initial detection distance, 𝑹𝟎, scales with atmospheric attenuation. Therefore, under clear sky conditions, the derived 𝑹𝟎 value represents the upper bound on the detection range achievable by the test configuration of the detector. Results indicate that the maximum initial detection distance for a 4k resolution action camera fitted with a 41º Field of View (FOV) lens is 2.763 ± 0.037 km for a GA aircraft and 0.881 ± 0.061 km for a fixed-wing sUAS, respectively. The in results this study suggest that a vision-based detect and track system may be analyzed using the sensor characterization and contextualized within aircraft well-clear volumes.

Chester V. Dolph↗

NASA NTRS2019

Analysis of At-Altitude LTE Power Spectra for C2 Communications for UAS Traffic Management

The National Aeronautics and Space Administration’s (NASA) Unmanned Aircraft Systems Traffic Management (UTM) project works to develop tools and technologies essential for safely enabling civilian low-altitude small Unmanned Aerial Systems (sUAS, also known as drones) operations. This paper presents results of work completed in the paper [1] presented at the 2018 ICNS conference where proposed approaches were explored for evaluating and analyzing sUAS Command and Control (C2) links based on commercial cellular networks. This paper focuses on the UTM Project’s Technology Capability Level 3 (TCL-3) test results which address the communications portion identified within the same paper. A software defined radio (SDR) was flown as a sUAS payload to capture received signal spectrum in Long Term Evolution (LTE) frequency bands of interest. The purpose was to measure the RF environment at UTM altitudes to characterize the interference potential. The SDR payload was flown at various stationary altitudes where the LTE over-the-air complex (I/Q) samples were captured by the SDR and later post-processed. The SDR received inputs through an omnidirectional antenna. The complex samples captured were an aggregate of transmissions received from all line-of-sight (LOS) towers within the geographic area for the specific radio frequency bandwidth the SDR is programmed to capture. Using this approach, the complex samples captured do not distinguish between the various eNodeB's (Long Term Evolution (LTE) transmitting towers). The complex samples were post processed via a Discrete Fourier Transform (DFT) algorithm to view the captured spectrum along with the power levels across the captured LTE bandwidth. This SDR payload process of capturing complex samples was done at two different regions within the US: 1) NASA's Ames Research Center (ARC) in Moffett Field, CA, and 2) Griffiss Airfield in Rome, NY. The data capture at the ARC site was done at two physical locations within the Ames campus where many stationary altitude captures where done as high as 800 ft. above ground level (AGL). The data captured at the Griffiss Airport (also known as the NY Corridor Site) were acquired at one location with three specific stationary altitude levels – {Ground Level (GL), 300 ft., and 400 ft.}. The LTE spectrum power levels were captured for two LTE carriers, AT&T and Verizon, at both sites where their respective spectra and power levels were measured and compared at various altitudes. The overall results show that there is an increase in LTE spectrum power levels at higher altitudes for drones. A detailed analysis of this data and conclusions drawn from the results are presented in this paper.

Kerczewski, Robert J.↗

NASA NTRS2018

A Summary of NASA Research Exploring the Acoustics of Small Unmanned Aerial Systems

Proposed uses of small unmanned aerial systems (sUAS) have the potential to expose large portions of communities to a new noise source. In order to understand the potential noise impact of sUAS, NASA initiated acoustics research as one component of the 3-year DELIVER project, with the goal of documenting the feasibility of using existing aircraft design tools and methods on this class of vehicles. This paper summarizes the acoustics research conducted within the DELIVER project. The research described here represents an initial study, and subsequent research building on the findings of this work has been proposed for other NASA projects. The paper summarizes acoustics research in four areas: measurements of noise generated by flyovers of small unmanned aerial vehicles, measurements in controlled test facilities to understand the noise generated by components of these vehicles, computational predictions of component and full vehicle noise, and psychoacoustic tests including auralizations conducted to assess human annoyance to the noise generated by these vehicles.

Zawodny, Nikolas S.↗

NASA NTRS2019

Cellular Based Small Unmanned Aircraft Systems MIMO Communications

The use of remotely piloted unmanned aircraft systems/vehicles (UAS/UAV or drones) increases dramatically in recent years. This paper discusses the use of multiple-input and multiple-output (MIMO) technologies in cellular (i.e., LTE) based small UAS (sUAS) communications. More specifically, we will first provide background information about this work, followed by a review of state-of-the-art. Then, we will discuss the benefits of MIMO technologies and propose practical MIMO configurations (e.g., the type, size and number of antennas) that are suitable for NASA's sUAS research and operations. Finally, the design tradeoff among multiplexing, diversity, and interference/jamming cancellation will also be discussed.

Li, Hongxiang↗

NASA NTRS2017

A Fuzzy Logic Approach for Separation Assurance and Collision Avoidance for Unmanned Aerial Systems

In the coming years, operations in low altitude airspace will vastly increase as the capabilities and applications of small Unmanned Aerial Systems (sUAS) continue to multiply. Therefore, solutions to managing sUAS in highly congested airspace must be explored. In this study, a Fuzzy Logic based approach was used to help mitigate the risk of collisions between aircraft using separation assurance and collision avoidance techniques. The system was evaluated for its effectiveness to mitigate the risk of mid-air collisions between aircraft. This system utilizes only current state information and can resolve potential conflicts without knowledge of intruder intent. The avoidance logic was verified using formal methods and shown to select the correct action in all instances. Additionally, the Fuzzy Logic Controllers were shown to always turn the vehicles in the correct direction. Numerical testing demonstrated that the avoidance system was able to prevent a mid-air collision between two sUAS in all tested cases. Simulations were also performed in a three-dimensional environment with a heterogenous fleet of sUAS performing a variety of realistic missions. Simulations showed that the system was 99.98 effective at preventing mid-air collisions when separation assurance was disabled (unmitigated case) and 100 effective when enabled (mitigated case).

Verification & Validation of a Fuzzy Logic Control↗

NASA NTRS2019

Indoor Ground Testing of a Small UAS Sense and Avoid Airborne Doppler Radar

The National Aeronautics and Space Administration’s Unmanned Aircraft System (UAS) Traffic Management (UTM) project is researching prototype technologies needed to ensure safe integration of UAS operations into the National Airspace System (NAS). Within the UTM Concept of Operations, UAS would be equipped with on-board Sense and Avoid (SAA) technology to continually monitor for manned and unmanned aircraft in its vicinity while operating beyond visual line of sight in uncontrolled airspace. To support this effort, a candidate commercially available 24.5 GHz Doppler radar was selected and evaluated to determine if the technology could reliably support minimum requirements for SAA applications of small UAS (sUAS). Indoor ground tests were conducted inside the NASA Langley Research Center’s Experimental Test Range (ETR) from a stationary platform to evaluate the Doppler radar performance characteristics and gain operational proficiency before the radar was authorized to transmit outdoors. A high speed linear rail system was developed for the radar evaluation and was shown to be an effective method to generate Doppler radar targets of known radar cross section. The accuracy of the range and velocity reported by the radar was shown to be dependent on the Kalman filter state variance parameter settings. Antenna measurements were collected with the radar installed both on and off a sUAS to quantify the relative antenna gain, beam width and side lobe levels of the radar’s Metamaterial Electronically Scanning Array (MESA) antennas at boresight and extreme field of view pointing vectors. The relative antenna gain measured 2.6 dB lower at extreme field view angles compared to the boresight radiation pattern.

Szatkowski, George N.↗

NASA NTRS2019

Optical Geolocation for Small Unmanned Aerial Systems

This paper presents an airborne optical geolocation system using four optical targets to provide position and attitude estimation for a sUAS supporting the NASA Acoustic Research Mission (ARM), where the goal is to reduce nuisance airframe noise during approach and landing. A large precision positioned microphone array captures the airframe noise for multiple passes of a Gulfstream III aircraft. For health monitoring of the microphone array, the Acoustic Calibration Vehicle (ACV) sUAS completes daily flights with an onboard speaker emitting tones at frequencies optimized for determining microphone functionality. An accurate position estimate of the ACV relative to the array is needed for microphone health monitoring. To this end, an optical geolocation system using a downward facing camera mounted to the ACV was developed. The 3D positioning of the ACV is computed using the pinhole camera model. A novel optical geolocation algorithm first detects the targets, then a recursive algorithm tightens the localization of the targets. Finally, the position of the sUAS is computed using the image coordinates of the targets, the 3D world coordinates of the targets, and the camera matrix. A Real-Time Kinematic GPS system is used to compare the optical geolocation system.

Dolph, Chester V.↗

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

A Cognitive Walkthrough of Multiple Drone Delivery Operations

Advances of early twenty-first century aviation and transportation technologies provide opportunities for enhanced aerial projects, and the overall integration of unmanned aircraft systems (UAS) into the National Airspace System (NAS) has applications across a wide range of operations. Through these, remote operators have learned to manage several UAS at the same time in a variety of operational environments. The present work details a component piece of an ongoing body of research into multi-UAS operations. Beginning in early 2020, NASA has collaborated with Uber Technologies to design and develop concepts of operations, roles and responsibilities, and ground control station (GCS) concepts to enable food delivery operations via multiple, small UAS (sUAS). A cognitive walkthrough was chosen as the method for data collection. This allowed information to be gathered from UAS subject matter experts (SMEs) that could further mature designs for future human-in-the-loop (HITL) simulations; in addition, it allowed information to be collected remotely during the stringent restrictions of the COVID-19 pandemic. Consequently, the described cognitive walkthrough activity utilized remote data collection protocols mediated through the usage of programs designed for presentation and telecommunications. Scenarios were designed, complete with airspace, contingencies, and remedial actions, to be presented to the SMEs. Information was collected using a combination of rating scales and open-ended questions. Results received from the SMEs revealed expected hazards, workloads, and information concerns inherent in the contingency scenarios. SMEs also provided insight into the design of GCS tools and displays as well as the duties and relationships of human operators (i.e., monitors) and automation (i.e., informers and flight managers). Implications of these findings are discussed.

unmanned aircraft systems↗

NASA NTRS2021

A Cognitive Walkthrough of Multiple Drone Delivery Operations

Advances of early twenty-first century aviation and transportation technologies provide opportunities for enhanced aerial projects, and the overall integration of unmanned aircraft systems (UAS) into the National Airspace System (NAS) has applications across a wide range of operations. Through these, remote operators have learned to manage several UAS at the same time in a variety of operational environments. The present work details a component piece of an ongoing body of research into multi-UAS operations. Beginning in early 2020, NASA has collaborated with Uber Technologies to design and develop concepts of operations, roles and responsibilities, and ground control station (GCS) concepts to enable food delivery operations via multiple, small UAS (sUAS). A cognitive walkthrough was chosen as the method for data collection. This allowed information to be gathered from UAS subject matter experts (SMEs) that could further mature designs for future human-in-the-loop (HITL) simulations; in addition, it allowed information to be collected remotely during the stringent restrictions of the COVID-19 pandemic. Consequently, the described cognitive walkthrough activity utilized remote data collection protocols mediated through the usage of programs designed for presentation and telecommunications. Scenarios were designed, complete with airspace, contingencies, and remedial actions, to be presented to the SMEs. Information was collected using a combination of rating scales and open-ended questions. Results received from the SMEs revealed expected hazards, workloads, and information concerns inherent in the contingency scenarios. SMEs also provided insight into the design of GCS tools and displays as well as the duties and relationships of human operators (i.e., monitors) and automation (i.e., informers and flight managers). Implications of these findings are discussed.

unmanned aircraft systems↗

NASA NTRSDate not supplied

Fire Front Detection and Tracking for Autonomous sUAS in STEReO

The Scalable Traffic Management Emergency Response Operations (STEReO) project aims to incorporate unmanned aerial systems (UAS) into wildfire incident response to safely quicken response times, improve operator awareness, and scale-up aircraft operations.Autonomous UAS can be used to relieve human operators of dull, dirty, and dangerous tasks such as checking for re-ignitions and geo-locating fires. To geo-locate fires, the UAS must be able to detect whether a fire is present and also have the necessary information to stamp a location. Furthermore, the UAS should be able to track the fire front to determine the extent of the fire. This study presents a fire front detection and tracking methodology for an autonomous small UAS (sUAS). The methodology is evaluated in simulation.

Autonomous UAV,Wildfire,Detection,Tracking↗

NASA NTRS2018

Small Unmanned Aerial System (UAS) Flight Testing of Enabling Vehicle Technologies for the UAS Traffic Management Project

Small unmanned aerial systems (sUAS) have been studied and results indicate that there is a large array of highly-beneficial applications. These applications are too numerous to list, but include search and rescue, fire spotting, precision agriculture, etc. to name a few. Typically sUAS vehicles weigh less than 55 pounds and will be performing flight operations in the presence of manned aircraft and other sUAS. Certain sUAS applications, such as package delivery, will include operations in the close proximity of the general public. The full benefit from sUAS is contingent upon the resolution of several technological areas to enable free and widespread use of these vehicles. Technological areas in question include, but are not limited to: autonomous sense and avoid and deconfliction of sUAS from other sUAS and manned aircraft, communications and interfaces between the vehicle and human operators, and high-reliability autonomous systems. The NASA UAS Traffic Management (UTM) project is endeavoring to develop a traffic management system and concept of operations for these types of vehicles. An extensive sUAS flight test effort was performed to partially address vehicle-related technological areas and to shape an understanding of future developmental and test efforts for vehicles intended to use the UTM traffic management system. The flight testing described herein had the following objectives: 1) Install and test Dedicated Short Range Communications (DSRC) systems developed for the automotive industry for potential sense and avoid sUAS applications; 2) Evaluate the use of cellular 4G systems to provide vehicle control; 3) Obtain high-resolution video imagery in support of image-based optical detection sense and avoid systems; 4) Acquire data in fixed-wing flight to support validation and maturation of an autonomous range containment system known as Safeguard in fixed-wing flight. A total of 53 flights were performed over 12 operational days at Beaver Dam Airpark in Elberon, VA. This work was sponsored by the UTM project that is part of the Aviation Operations and Safety Program (AOSP) at NASA.

Glaab, Louis J.↗

NASA NTRSDate not supplied

A Remote, Human-in-the-Loop Evaluation of a Multiple-Drone Delivery Operation

Over time, advances in unmanned aircraft systems (UAS) have enabled a shift in the operational paradigm from one operator managing one aircraft to that of multiple operators working together to manage multiple aircraft. This shift has highlighted the need for effective human-autonomy teaming methods to maintain manageable workload levels for operators as well as high standards of system performance and safety. This paper presents a study aimed at evaluating whether automation can help operators manage workload during small UAS (sUAS) package delivery scenarios featuring contingency situations. These contingency situations, resulting from unplanned UAS Volume Reservations (UVRs), required flight path reroutes for multiple aircraft simultaneously. The study manipulated the number of aircraft affected by the UVRs and the level of automation support. The presence of terrain conflicts was also controlled within each scenario. Due to the COVID-19 pandemic, subjects were not able to gain direct access to the Ground Control System (GCS). Therefore, the study was conducted using a subject-surrogate paradigm that required subjects to relay commands through a verbal protocol from remote locations outside of the lab to a researcher surrogate who had direct control of the GCS interfaces at the lab location. Results show that the automated support condition was associated with faster reroute response times, more efficient reroute maneuvers, and significantly lower levels of perceived workload than the manual reroute condition. However, the automation support level did not significantly impact pilots’ ability to avoid the UVR successfully; pilots were overwhelmingly capable of avoiding the UVR in all conditions. The presence of terrain conflicts primarily impacted pilot performance by leading to multiple uploads per vehicle, which was not typically required when pilots only needed to maneuver laterally. Although subjects did not have direct control over the GCS, subjective ratings indicate that the displays under test provided them with sufficient information to manage their aircraft and promptly respond to the unplanned UVRs. Overall, the objective and subjective data strongly suggest that the verbal protocol and subject-surrogate paradigm were effective methods for collecting data remotely amid the COVID-19 pandemic.

multi-UAS↗

NASA NTRSDate not supplied

Developing an Unmanned Aircraft System Pilot (UASP-kit) for Wildland Fire UAS Operators

The use of unmanned aircraft systems (UAS) to support disaster management is becoming more widespread. Uninhibited by many of the operational constraints imposed on crewed aircraft, UAS have the potential to augment the aerial response in a number of ways, including supporting situation awareness, thereby accelerating disaster management efforts. The intent of the Scalable Traffic management for Emergency Response Operations (STEReO) activity is to build an ecosystem that will allow small UAS (sUAS) operations to fly safely in the airspace during disaster management events. The first step toward this goal is to develop a small, single-user tool (the UASP-kit) that will enhance an sUAS pilot’s situation awareness of the airspace. User needs for the functions and features of this tool were collected during a walkthrough over multiple days with subject matter experts from the US Forest Service. A prototype of the UASP-kit was then taken on an extended demonstration to multiple users, who were able to interact with it. User feedback was largely positive and users discussed the information they needed to support situation awareness in context. The demonstration also highlighted features that were unintuitive to use, and functions that need to be modified to make the kit more user-friendly and robust.

STEReO↗

NASA NTRSDate not supplied

Developing an Unmanned Aircraft System Pilot Kit (UASP-kit) for Wildland Fire UAS Operators

The use of unmanned aircraft systems (UAS) to support disaster management is becoming more widespread. Uninhibited by many of the operational constraints imposed on crewed aircraft, UAS have the potential to augment the aerial response in a number of ways, including supporting situation awareness, thereby accelerating disaster management efforts. The intent of the Scalable Traffic management for Emergency Response Operations (STEReO) activity is to build an ecosystem that will allow small UAS (sUAS) operations to fly safely in the airspace during disaster management events. The first step toward this goal is to develop a small, single-user tool (the UASP-kit) that will enhance an sUAS pilot’s situation awareness of the airspace. User needs for the functions and features of this tool were collected during a walkthrough over multiple days with subject matter experts from the US Forest Service. A prototype of the UASP-kit was then taken on an extended demonstration to multiple users, who were able to interact with it. User feedback was largely positive and users discussed the information they needed to support situation awareness in context. The demonstration also highlighted features that were unintuitive to use, and functions that need to be modified to make the kit more user-friendly and robust.

STEReO↗

NASA NTRSDate not supplied

Advanced Capabilities for Emergency Response Operations (ACERO)

The use of unmanned aircraft systems (UAS) to support disaster management is becoming more widespread. Uninhibited by many of the operational constraints imposed on crewed aircraft, UAS have the potential to augment the aerial response in a number of ways, including supporting situation awareness, thereby accelerating disaster management efforts. The intent of the Scalable Traffic management for Emergency Response Operations (STEReO) activity is to build an ecosystem that will allow small UAS (sUAS) operations to fly safely in the airspace during disaster management events. The first step toward this goal was to develop a small, single-user tool (the UASP-kit) that will enhance an sUAS pilot’s situation awareness of the airspace. In a subsequent project (Advanced Capabilities for Emergency Response Operations (ACERO)) the UASP-kit will be expanded and built upon to develop and airspace management tool.

STEReO↗

NASA NTRS2013

Flight Testing of Novel Compliant Spines for Passive Wing Morphing on Ornithopters

Unmanned Aerial Vehicles (UAVs) are proliferating in both the civil and military markets. Flapping wing UAVs, or ornithopters, have the potential to combine the agility and maneuverability of rotary wing aircraft with excellent performance in low Reynolds number flight regimes. The purpose of this paper is to present new free flight experimental results for an ornithopter equipped with one degree of freedom (1DOF) compliant spines that were designed and optimized in terms of mass, maximum von-Mises stress, and desired wing bending deflections. The spines were inserted in an experimental ornithopter wing spar in order to achieve a set of desired kinematics during the up and down strokes of a flapping cycle. The ornithopter was flown at Wright Patterson Air Force Base in the Air Force Research Laboratory Small Unmanned Air Systems (SUAS) indoor flight facility. Vicon motion tracking cameras were used to track the motion of the vehicle for five different wing configurations. The effect of the presence of the compliant spine on wing kinematics and leading edge spar deflection during flight is presented. Results show that the ornithopter with the compliant spine inserted in its wing reduced the body acceleration during the upstroke which translates into overall lift gains.

Wissa, Aimy↗

NASA NTRS2017

High-Fidelity Multi-Rotor Unmanned Aircraft System Simulation Development for Trajectory Prediction Under Off-Nominal Flight Dynamics

The NASA Unmanned Aircraft System (UAS) Traffic Management (UTM) project is conducting research to enable civilian low-altitude airspace and UAS operations. A goal of this project is to develop probabilistic methods to quantify risk during failures and off nominal flight conditions. An important part of this effort is the reliable prediction of feasible trajectories during off-nominal events such as control failure, atmospheric upsets, or navigation anomalies that can cause large deviations from the intended flight path or extreme vehicle upsets beyond the normal flight envelope. Few examples of high-fidelity modeling and prediction of off-nominal behavior for small UAS (sUAS) vehicles exist, and modeling requirements for accurately predicting flight dynamics for out-of-envelope or failure conditions are essentially undefined. In addition, the broad range of sUAS aircraft configurations already being fielded presents a significant modeling challenge, as these vehicles are often very different from one another and are likely to possess dramatically different flight dynamics and resultant trajectories and may require different modeling approaches to capture off-nominal behavior. NASA has undertaken an extensive research effort to define sUAS flight dynamics modeling requirements and develop preliminary high fidelity six degree-of-freedom (6-DOF) simulations capable of more closely predicting off-nominal flight dynamics and trajectories. This research has included a literature review of existing sUAS modeling and simulation work as well as development of experimental testing methods to measure and model key components of propulsion, airframe and control characteristics. The ultimate objective of these efforts is to develop tools to support UTM risk analyses and for the real-time prediction of off-nominal trajectories for use in the UTM Risk Assessment Framework (URAF). This paper focuses on modeling and simulation efforts for a generic quad-rotor configuration typical of many commercial vehicles in use today. An overview of relevant off-nominal multi-rotor behaviors will be presented to define modeling goals and to identify the prediction capability lacking in simplified models of multi-rotor performance. A description of recent NASA wind tunnel testing of multi-rotor propulsion and airframe components will be presented illustrating important experimental and data acquisition methods, and a description of preliminary propulsion and airframe models will be presented. Lastly, examples of predicted off-nominal flight dynamics and trajectories from the simulation will be presented.

Foster, John V.↗