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Communications Technology Assessment for the Unmanned Aircraft System (UAS) Control and Non-Payload Communications (CNPC) Link

The National Aeronautics and Space Administration (NASA) Glenn Research Center (GRC) is performing communications systems research for the Unmanned Aircraft System (UAS) in the National Airspace System (NAS) Project. One of the goals of the communications element is to select and test a communications technology for the UAS Control and Non-Payload Communications (CNPC) link. The GRC UAS Modeling and Simulation (M/S) Sub Team will evaluate the performance of several potential technologies for the CNPC link through detailed software simulations. In parallel, an industry partner will implement a technology in hardware to be used for flight testing. The task necessitated a technical assessment of existing Radio Frequency (RF) communications technologies to identify the best candidate systems for use as the UAS CNPC link. The assessment provides a basis for selecting the technologies for the M/S effort and the hardware radio design. The process developed for the technical assessments for the Future Communications Study1 (FCS) was used as an initial starting point for this assessment. The FCS is a joint Federal Aviation Administration (FAA) and Eurocontrol study on technologies for use as a future aeronautical communications link. The FCS technology assessment process methodology can be applied to the UAS CNPC link; however the findings of the FCS are not directly applicable because of different requirements between a CNPC link and a general aeronautical data link. Additional technologies were added to the potential technologies list from the State of the Art Unmanned Aircraft System Communication Assessment developed by NASA GRC2. This document investigates the state of the art of communications as related to UAS. A portion of the document examines potential communications systems for a UAS communication architecture. Like the FCS, the state of the art assessment surveyed existing communications technologies. It did not, however, perform a detailed assessment of the technology necessary to recommend a technology for the UAS CNPC link. The technical assessment process, as shown in Figure 1, consists of the following steps. First, candidate RF communications technologies are identified. An initial review of each of these technologies is then performed to determine if the technology appears to be a good candidate and requires further review. Any technology that can be shown to be inadequate at that point is removed from consideration to allow for more detailed analysis of the remaining technologies. Criteria for the detailed assessments are defined and a scoring methodology is devised. This is followed by the detailed review and scoring of each technology. The least favorable technologies are removed during the process until only the few best candidates remain.

Aircraft Command and Control↗

Formal Methods in the Development of Highly Assured Software for Unmanned Aircraft Systems

In traditional software development methodologies, operational and functional requirements of systems are often specified in structured natural language notations. These restricted notations provide good documentation support, but only provide limited support for semantic analysis. These notations are generally not rich enough to unambiguously specify the requirements of safety-critical systems that, for example, involve complex numerical computations or that interact with the physical environment. Examples of these safety-critical systems are autonomous vehicles such as unmanned aircraft systems. This talk advocates the use of expressive formal logics, such as higher-order logic, to specify the operational and functional requirement of unmanned systems and to prove the correctness of these requirements. Semantic analysis of requirements written in higher-order logic is supported through the use of interactive theorem provers. Formal models serve as ideal reference implementations of functional requirements. Hence, formal logics enable software validation techniques where software implementations can be checked against functional requirements in a mechanical way. The Formal Methods group in the Safety-Critical Avionics Systems Branch at NASA Langley Research Center has conducted research on the development and application of formal verification techniques to safety-critical applications of interest to NASA for more than 30 years. This talk illustrates the use of formal methods in the development of highly-assured autonomous unmanned aircraft systems.

Formal Methods↗

Small Unmanned Aircraft Electromagnetic Interference (EMI) Initial Assessment

With many applications envisioned for small Unmanned Aircraft Systems (sUAS), and potentially millions of sUAS expected to be in operation in the future, the electromagnetic interference environment associated with the sUAS is of interest to understanding the potential performance impacts on the sUAS command and control communications link as well as the sUAS payload and payload links. As part of NASA's UAS Traffic Management (UTM) Project, flight experiments are planned to characterize the RF environment at altitudes up to 400 ft to better understand how UTM command and control links can be expected to perform. The flight experiments will use an RF channel sensing payload attached to an sUAS. In terms of the payload being capable of measuring relatively low level signals at altitude, electromagnetic interference (EMI) emanating from the sUAS vehicle itself could potentially complicate the measurement process. For this reason, NASA was interested in measuring the EMI performance of the sUAS planned for these flight experiments, a DJI model S1000. The S1000 was thus measured in a controlled EMI test chamber at the NASA Ames Research Center. The S1000 is a carbon fiber based platform with eight rotors. As such, the EMI test results represent potential performance of a number of similar sUAS types. sUAS platforms significantly different from the S1000 may also require EMI testing, and the method employed for NASA's S1000 EMI tests can be applied to other platforms. In this paper we describe the UTM project, the RF channel sensing payload, the EMI testing method and EMI test results for the S1000, and discuss the implications of these results.

Unmanned aircraft↗

Small Unmanned Aircraft Electromagnetic Interference (EMI) Initial Assessment

With many applications envisioned for small Unmanned Aircraft Systems (sUAS), and potentially millions of sUAS expected to be in operation in the future, the electromagnetic interference environment associated with the sUAS is of interest to understanding the potential performance impacts on the sUAS command and control communications link as well as the sUAS payload and payload links. As part of NASAâ€"TM"s UAS Traffic Management (UTM) Project, flight experiments are planned to characterize the RF environment at altitudes up to 400 ft to better understand how UTM command and control links can be expected to perform. The flight experiments will use an RF channel sensing payload attached to an sUAS. In terms of the payload being capable of measuring relatively low level signals at altitude, electromagnetic interference (EMI) emanating from the sUAS vehicle itself could potentially complicate the measurement process. For this reason, NASA was interested in measuring the EMI performance of the sUAS planned for these flight experiments, a DJI model S1000. The S1000 was thus measured in a controlled EMI test chamber at the NASA Ames Research Center. The S1000 is a carbon fiber based platform with eight rotors. As such, the EMI test results represent potential performance of a number of similar sUAS types. sUAS platforms significantly different from the S1000 may also require EMI testing, and the method employed for NASAâ€"TM"s S1000 EMI tests can be applied to other platforms. In this paper we describe the UTM project, the RF channel sensing payload, the EMI testing method and EMI test results for the S1000, and discuss the implications of these results.

traffic management↗

Flight Demonstration of Unmanned Aircraft System (UAS) Traffic Management (UTM) at Technical Capability Level 4

The NASA Unmanned Aircraft Systems (UAS) Traffic Management (UTM) Project executed the fourth and final UTM Technical Capability Level demonstration between May and August 2019. Two Federal Aviation Administration (FAA)-designated UAS test sites managed the range, partners, and operations to meet the requirements set forth by the UTM Project. All stakeholders supported the execution of the flight testing through close collaboration. Results of the demonstration indicate the viability of the UTM concept to manage large scale operations and contingencies in an urban environment. The demonstration also provided insight into key technological gaps that must be addressed before such operations are routine, safe, and efficient. Standardization efforts related to UTM and the industry participants of those efforts can leverage the results and experiences of this flight activity to accelerate and more firmly ground forthcoming standards. The FAA and other regulators will be able to leverage results to inform future rule-making and identify additional gaps that require further analysis.

Unmanned Aircraft System Traffic Management↗

Use of a Small Unmanned Aircraft System for Autonomous Fire Spotting at the Great Dismal Swamp

This paper describes the results of a set of experiments and analyses conducted to evaluate the capability of small unmanned aircraft systems (sUAS) to spot nascent fires in the Great Dismal Swamp (GDS) National Wildlife Refuge. This work is the result of a partnership between the National Aeronautics and Space Administration and the US Fish and Wildlife service specifically to investigate sUAS usage for fire-spotting. The objectives of the current effort were to: 1) Determine suitability and utility of low-cost Small Unmanned Aircraft Systems (sUAS) to detect nascent fires at GDS; 2) Identify and assess the necessary National Airspace System (NAS) integration issues; and 3) Provide information to GDS and the community on system requirements and concepts-of-operation (CONOPS) for conducting fire detection/support mission in the National Airspace and (4) Identify potential applications of intelligent autonomy that would enable or benefit this high-value mission. In addition, data on the ability of various low-cost sensors to detect smoke plumes and fire hot spots was generated during the experiments as well as identifying a path towards a future practical mission utility by using sUAS in beyond visual-line-of-sight operation in the National Airspace System (NAS).

Logan, Michael J.↗

Unmanned Aircraft Hazards and their Implications for Regulation

Use of unmanned aircraft systems (UASs) has been characterized as the next great step forward in the evolution of civil aviation. Indeed, UASs are in limited civil use in the United States today, and many believe that the time is rapidly approaching when they will move into the commercial marketplace, too. To make this a reality, a number of challenges must be overcome to develop the necessary regulatory framework for assuring safe operation of this special class of aircraft. This paper discusses some of what must be done to establish that framework. In particular, we examine hazards specific to the design, operation, and flight crew of UASs, and discuss implications of these hazards for existing policy and guidance. Understanding unique characteristics of UASs that pose new hazards is essential to developing a cogent argument, and the corresponding regulatory framework, for safely integrating these aircraft into civil airspace.

Hayhurst, Kelly J.↗

The Development of Human Factor Guidelines for Unmanned Aircraft System Control Stations

Despite being referred to as unmanned some of the major challenges confronting unmanned aircraft systems (UAS) relate to human factors. NASA is conducting research to address the human factors relevant to UAS access to non-segregated airspace. This work covers the issues of pilot performance, interaction with ATC, and control station design. A major outcome of this research will be recommendations for human factors design guidelines for UAS control stations to support routine beyond-line-of-sight operations in the US national airspace system (NAS). To be effective, guidelines must be relevant to a wide range of systems, must not be overly prescriptive, and must not impose premature standardization on evolving technologies. In developing guidelines, we recognize that existing regulatory and guidance material may already provide adequate coverage of certain issues. In other cases suitable guidelines may be found in existing military or industry human factors standards. In cases where appropriate existing standards cannot be identified, original guidelines will be proposed.

guidelines↗

A Review of Current and Prospective Factors for Classification of Civil Unmanned Aircraft Systems

While progress is being made on integrating unmanned aircraft systems (UAS) into our national airspace on a broad scale, much work remains to establish appropriate certification standards and operational procedures, particularly with respect to routine commercial operations. This paper summarizes research to examine the extent to which today's civil aircraft taxonomy applies to UAS, and, if needed, how that taxonomy could be amended to better cover different UAS designs and operations. Factors that shape the current taxonomy, as defined in the Federal Aviation Regulations, were assessed for applicability to UAS, potential incompatibilities were identified, and additional factors were proposed that might be useful for an updated aircraft taxonomy intended to cover UAS. The results suggest the possibility of constructing new groups in the taxonomy for UAS under a restricted category that share common airworthiness standards. Establishing distinct groups for UAS and associated standards that enable low risk operations for compensation or hire could be a timely step toward full integration. Such a step would allow the civil aviation industry and regulators to gain valuable experience with UAS while carefully controlling access and potential harm to the aviation system as a whole.

Hayhurst, Kelly J.↗

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↗

Flight Test Evaluation of an Unmanned Aircraft System Traffic Management (UTM) Concept for Multiple Beyond-Visual-Line-of-Sight Operations

This study evaluates a traffic management concept designed to enable simultaneous operations of multiple small unmanned aircraft systems (UAS) in the national airspace system (NAS). A five-day flight-test activity is described that examined the feasibility of operating multiple UAS beyond visual line of sight (BVLOS) of their respective operators in the same airspace. Over the five-day campaign, three groups of five flight crews operated a total of eleven different aircraft. Each group participated in four flight scenarios involving five simultaneous missions. Each vehicle was operated BVLOS up to 1.5 miles from the pilot in command. Findings and recommendations are presented to support the feasibility and safety of routine BVLOS operations for small UAS.

UTM↗

Automated Management of Small Unmanned Aircraft System Communications and Navigation Contingency

The number of small Unmanned Aircraft System (sUAS) operating in the low-altitude of the National Airspace System (NAS) has been rapidly increasing in the past few years and this number is expected to grow in the future. However, aside from a few special cases, all sUAS must fly within visual line-of-sight (VLOS) of their operators and this limitation is blocking highly anticipated beyond visual line-of-sight (BVLOS) sUAS applications such as package delivery from practice. To enable routine low-altitude BVLOS operations, there needs to be a traffic management ecosystem that complements the FAA’s Air Traffic Management (ATM) system, which does not provide air traffic services under 400 feet above ground level (AGL). NASA has been pioneering research and development of this ecosystem under UAS Traffic Management (UTM) project since 2015 in a series of Technical Capability Levels (TCL) activities that are increasingly complex. In TCL1, completed in 2015, visual line-of-sight operations such as agriculture, firefighting, and infrastructure monitoring were addressed with a focus on geofencing and operations scheduling. Technologies and requirements needed for BVLOS operations in sparsely populated areas were examined in TCL2 in 2016, and those for operations over moderately populated areas in TCL3 in 2017 and 2018. TCL4 is building on the earlier TCLs and focuses on technologies and requirements for operations in higher-density urban areas for tasks such as newsgathering and package delivery and for managing large-scale contingencies. To coordinate and facilitate the incremental implementation of the UTM ecosystem in the NAS, a Research Transition Team (RTT) has been formed between the FAA, NASA, and industry. The RTT is divided into four subgroups, concept and use case development, data exchange and information architecture, sense and avoid, and communications and navigation (C&N). This paper focuses on C&N subgroup activities, in particular about the development of automated sUAS communications and navigation contingency management. The goal of this development is to prepare sUAS to display predictable behavior while handling C&N off-nominal events. It is expected that the adoption of the presented automated contingency management by the sUAS community will accommodate and inform rulemaking towards governing low-altitude BVLOS operations.

Unmanned Aviation System (UAS) Traffic Management↗

Unmanned Aircraft Systems (UAS) Traffic Management (UTM) National Campaign II

The Unmanned Aircraft System (UAS) Traffic Management (UTM) effort at NASA aims to enable access to low-altitude airspace for small UAS. This goal is being pursued partly through partnerships that NASA has developed with the UAS stakeholder community, the FAA, other government agencies, and the designated FAA UAS Test Sites. By partnering with the FAA UAS Test Sites, NASA's UTM project has performed a geographically diverse, simultaneous set of UAS operations at locations in six states. The demonstrations used an architecture that was developed by NASA in partnership with the FAA to safely coordinate such operations. These demonstrations-the second or 'Technical Capability Level (TCL 2)' National Campaign of UTM testing-was performed from May 15 through June 9, 2017. Multiple UAS operations occurred during the testing at sites located in Alaska, Nevada, Texas, North Dakota, Virginia, and New York with multiple organizations serving as UAS Service Suppliers and/or UAS Operators per the specifications provided by NASA. By engaging various members of the UAS community in development and operational roles, this campaign provided initial validation of different aspects of the UTM concept including: UAS Service Supplier technologies and procedures; geofencing technologies/conformance monitoring; ground-based surveillance/sense and avoid; airborne sense and avoid; communication, navigation, surveillance; and human factors related to UTM data creation and display. Additionally, measures of performance were defined and calculated from the flight data to establish quantitative bases for comparing flight test activities and to provide potential metrics that might be routinely monitored in future operational UTM systems.

Aweiss, Arwa S.↗