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At least 379 records · Page 21
All sourcesNASA NTRSDOE OSTI
NASA NTRS2024

Standard Operating Procedure (SOP) for Flight Testing a Radiosonde and 3D Sonic Anemometer Configuration on a Multi-rotor Uninhabited Aerial System (UAS)

The purpose of this Standard Operating Procedure (SOP) is to establish a uniform procedure for initialization of a radiosonde, a 3D sonic anemometer, and collection of sounding data with correct sensor integration via a multi-rotor uninhabited aerial system (UAS) within the Langley Research Center’s (LaRC) Uninhabited Aerial System Operations Office (UASOO).

Tyler L. Willhite↗
NASA NTRSDate not supplied

High-Intensity Radiated Field (HIRF) Map - An Avoidance Approach for UAM, AAM, and UAS Vehicles

Advanced Air Mobility (AAM), Urban Air Mobility (UAM), and Unmanned Aerial Systems (UAS) vehicles will fly in similar airspace to Transport Category Rotorcraft, thereby requiring them to meet the most severe requirements for High Intensity Radiated Fields (HIRF) certification. The environment is severe for rotorcraft, much more so than for fixed-wing aircraft, due to lower altitude operations, potentially exposing the vehicles to close and direct view of high-power transmitters on the ground. High-level HIRF exposure potentially leads to avionic system upsets, interference, and undesirable effects. Shielding and circuit protection against HIRF will be a significant barrier to size, weight, and cost, especially for emerging electric vertical take-off and landing (eVTOL) and electric short take-off and landing (eSTOL) vehicles. This paper proposes a novel approach to HIRF protection, which reduces costs by testing and certifying vehicles to a “vehicle tolerance level” that is lower than required for Transport Category Rotorcraft. The remaining protection is achieved by maintaining a safe distance from known HIRF sources, calculated based on the vehicle's tolerance level and transmitter characteristics such as transmit power, antenna beamwidth, and direction. Tailored maps are developed, identifying transmitters and avoidance zones within an operating area or along a flight path, allowing for restricted vehicle operations. The HIRF avoidance zones could be smaller for vehicles with higher tolerance levels, enabling them to operate closer to transmitters. Transmitter data can be extracted from regulatory databases like the FCC and NOAA. A map tool is developed in Matlab to calculate and plot HIRF avoidance zones from transmitters in FCC and NOAA databases as proof of concept. Illustrations are presented for AM/FM/TV transmitters, communication satellite dishes, and weather radars. Also illustrated are HIRF zones for smaller transmitters, including land-mobile radios, pagers, microwave links, and cellular towers. An example of flight planning around the transmitters is presented. This method is a substantial deviation from the standard approach and involves slightly higher flight-planning complexity, but the potential cost savings are significant. Future AAM/UAM/UAS aeronautical charts could include these new HIRF avoidance zones.

HIRF↗
NASA NTRSDate not supplied

A Verification Framework for Runtime Assurance of Autonomous UAS

Runtime Assurance (RTA) is a design-time architecture for safety-critical systems where an internal monitor acts upon detecting a violation of a property. The simplex architecture is an instance of RTA, where the action taken is to hand control of the overall system to a trusted controller when an untrusted one violates a safety property. Simplex RTA is emerging as a method for allowing AI/ML and other unverified software to be integrated into safety-critical applications like aircraft. To this end, the American Society for Testing and Materials (ASTM) and NASA have each published guidelines on the use of RTA in such systems. In the simplex RTA framework, a system has an advanced controller (AC) and a reversionary controller (RC). The system is allowed to operate with the AC until a runtime monitor detects that some property has been violated and then the RC takes over. Assuming that the sample rate of the monitor will detect improper functioning with enough time for the RC to correct the impending problem, and that the RC is trusted, the system will operate as intended. This use of the simplex RTA framework can allow for the integration of untrusted, but possibly more performant, controllers in a safe way. This paper presents a formalization of a simplex RTA framework in the Prototype Verification System (PVS) theorem prover using an embedding of differential dynamic logic (DDL) called Plaidypvs. A novel feature of this framework is that it can be instantiated at different levels of abstraction. This feature allows for the formal verification of a system with an untrusted black box component, such as an AI/ML controller. This paper does not address the many difficulties in deploying RTA in an industrial-level system. Instead, the focus is on the formal verification of the simplex RTA framework in the language of hybrid programs. Hybrid programs are programs that include both discrete and continuous dynamics and can be used to model complex cyber-physical systems. Plaidypvs is a tool that enables formalization of hybrid programs in the PVS theorem prover. Plaidypvs enables the verification of the general simplex RTA framework and then, by specializing some components of the hybrid program, verifying instances of the framework while treating the untrusted component as a black box. A selection of Unmanned Aircraft Systems (UAS) operations are shown as instances of the general RTA framework in PVS. This offers the benefit of design time verification of relevant safety properties to the system, and it also gives requirements on the sample rate of sensors that determine the time interval in which the ‘switch’ property of the RTA framework is checked.

PVS↗
NASA NTRSDate not supplied

UAS Payload Design for In-Situ Smoke Plume Sensing

To aid in the detection of harmful aerosols and trace gases emitted in wildfires and prescribed burns, we are designing a smoke-specific payload which can be flown on the Black Swift S2™ Uncrewed Aerial System (UAS) platform. The payload will be custom and mounted within the nosecone, equipped with a trace gas sensor suite and particle spectrometer for characterization of wildfire and prescribed burn emissions. This data will aid in the improvement of HYSPLIT3 modeling to make more informed decisions regarding prescribed burns, particularly for mountain valleys in the Pacific Northwest. The trace gas suite will be composed of 8 low-cost trace gas sensors (CH4, CO2, CO, HCN, NO2, NO, O3, and Volatile Organic Compounds (VOCs)). Portable Optical Particle Spectrometer (POPS) measures particle size range between 0.14 to 3 µm, which is crucial for assessing public health impact, air quality, and visibility.

Henry Miller↗
NASA NTRS2017

Detection, Localization, and Tracking of Unauthorized UAS and Jammers

Small unmanned aircraft systems (UASs) are expected to take major roles in future smart cities, for example, by delivering goods and merchandise, potentially serving as mobile hot spots for broadband wireless access, and maintaining surveillance and security. Although they can be used for the betterment of the society, they can also be used by malicious entities to conduct physical and cyber attacks to infrastructure, private/public property, and people. Even for legitimate use-cases of small UASs, air traffic management (ATM) for UASs becomes of critical importance for maintaining safe and collusion-free operation. Therefore, various ways to detect, track, and interdict potentially unauthorized drones carries critical importance for surveillance and ATM applications. In this paper, we will review techniques that rely on ambient radio frequency signals (emitted from UASs), radars, acoustic sensors, and computer vision techniques for detection of malicious UASs. We will present some early experimental and simulation results on radar-based range estimation of UASs, and receding horizon tracking of UASs. Subsequently, we will overview common techniques that are considered for interdiction of UASs.

surveillance↗
NASA NTRS2014

UAS Integration in the NAS Project - ICAO Visit

This briefing will be given to ICAO Visitors to discuss project alignment with NASA, project overview, technical challenges, technology development approach and FY14 technical accomplishments.

UAS in the NAS↗
NASA NTRS2015

Enabling UAS Research at the NASA EAV Laboratory

The Exploration Aerial Vehicles (EAV) Laboratory at NASA Ames Research Center leads research into intelligent autonomy and advanced control systems, bridging the gap between simulation and full-scale technology through flight test experimentation on unmanned sub-scale test vehicles.

UTM↗
NASA NTRS2016

Flight Test Overview for UAS Integration in the NAS Project

The National Aeronautics and Space Administration is conducting a series of flight tests intended to support the reduction of barriers that prevent unmanned aircraft from flying without the required waivers from the Federal Aviation Administration. The most recent testing supported two separate test configurations. The first investigated the timing of Detect and Avoid (DAA) alerting thresholds using a radar-equipped unmanned vehicle and multiple live intruders flown at varying encounter geometries. The second configuration included a surrogate unmanned vehicle (flown from a ground control station, with a safety pilot on board) flying a mission in a virtual air traffic control airspace sector using research pilot displays and DAA advisories to maintain separation from live and virtual aircraft. The test was conducted over a seven-week span in the summer of 2015. The data from over 100 encounter sorties will be used to inform the RTCA Phase 1 Detect and Avoid and Command and Control Minimum Operating Performance Standards (MOPS) intended to be completed by the summer of 2016. Follow-on flight-testing is planned for the spring of 2016 to capture remaining encounters and support validation of the MOPS.

UAS↗