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NASA NTRS2006

HSI Guidelines Outline for the Air Vehicle Control Station. Version 2

This document provides guidance to the FAA and manufacturers on how to develop UAS Pilot Vehicle Interfaces to safely and effectively integrate UASs into the NAS. Preliminary guidelines are provided for Aviate, Communicate, Navigate and Avoid Hazard functions. The pilot shall have information and control capability so that pilot-UA interactions are not adverse, unfavorable, nor compromise safety. Unfavorable interactions include anomalous aircraft-pilot coupling (APC) interactions (closed loop), pilot-involved oscillations (categories I, II or III), and non-oscillatory APC events (e.g., divergence). - Human Systems Integration Pilot-Technology Interface Requirements for Command, Control, and Communications (C3)

Source record↗

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 NTRS2013

NASA GRC UAS Project: Communications Modeling and Simulation Status

The integration of Unmanned Aircraft Systems (UAS) in the National Airspace represents new operational concepts required in civil aviation. These new concepts are evolving as the nation moves toward the Next Generation Air Transportation System (NextGen) under the leadership of the Joint Planning and Development Office (JPDO), and through ongoing work by the Federal Aviation Administration (FAA). The desire and ability to fly UAS in the National Air Space (NAS) in the near term has increased dramatically, and this multi-agency effort to develop and implement a national plan to successfully address the challenges of UAS access to the NAS in a safe and timely manner is well underway. As part of the effort to integrate UAS in the National Airspace, NASA Glenn Research Center is currently involved with providing research into Communications systems and Communication system operations in order to assist with developing requirements for this implementation. In order to provide data and information regarding communication systems performance that will be necessary, NASA GRC is tasked with developing and executing plans for simulations of candidate future UAS command and control communications, in line with architectures and communications technologies being developed and/or proposed by NASA and relevant aviation organizations (in particular, RTCA SC-203). The simulations and related analyses will provide insight into the ability of proposed communications technologies and system architectures to enable safe operation of UAS, meeting UAS in the NAS project goals (including performance requirements, scalability, and interoperability), and ultimately leading to a determination of the ability of NextGen communication systems to accommodate UAS. This presentation, compiled by the NASA GRC team, will provide a view of the overall planned simulation effort and objectives, a description of the simulation concept and status of the design and development that has occurred to date.

Kubat, Greg↗

NASA NTRS2014

NASA GRC UAS Project - Communications Modeling and Simulation Development Status

The integration of Unmanned Aircraft Systems (UAS) in the National Airspace represents new operational concepts required in civil aviation. These new concepts are evolving as the nation moves toward the Next Generation Air Transportation System (NextGen) under the leadership of the Joint Planning and Development Office (JPDO), and through ongoing work by the Federal Aviation Administration (FAA). The desire and ability to fly UAS in the National Air Space (NAS) in the near term has increased dramatically, and this multi-agency effort to develop and implement a national plan to successfully address the challenges of UAS access to the NAS in a safe and timely manner is well underway. As part of the effort to integrate UAS in the National Airspace, NASA Glenn Research Center is currently involved with providing research into Communications systems and Communication system operations in order to assist with developing requirements for this implementation. In order to provide data and information regarding communication systems performance that will be necessary, NASA GRC is tasked with developing and executing plans for simulations of candidate future UAS command and control communications, in line with architectures and communications technologies being developed and or proposed by NASA and relevant aviation organizations (in particular, RTCA SC-203). The simulations and related analyses will provide insight into the ability of proposed communications technologies and system architectures to enable safe operation of UAS, meeting UAS in the NAS project goals (including performance requirements, scalability, and interoperability), and ultimately leading to a determination of the ability of NextGen communication systems to accommodate UAS. This presentation, compiled by the NASA GRC Modeling and Simulation team, will provide an update to this ongoing effort at NASA GRC as follow-up to the overview of the planned simulation effort presented at ICNS in 2013. The objective of presentation will be to describe the progress made in developing both a NAS-Wide simulation architecture application and the detailed radiocomm system models for this research, and will present interim data and information compiled in the process of developing these simulation capabilities to date.

Modeling and Simulation↗

NASA NTRS2015

Message Latency Characterization of a Distributed Live, Virtual, Constructive Simulation Environment

A distributed test environment incorporating Live, Virtual, Constructive, (LVC) concepts was developed to execute standalone and integrated simulations and flight-tests that support unmanned aircraft research for NASA’s Unmanned Aircraft Systems (UAS) in the National Airspace System (NAS) Project. The LVC components form the core infrastructure that supports simulation of UAS operations by integrating live and virtual aircraft in a realistic air traffic environment. This LVC infrastructure enables efficient testing by leveraging the use of existing distributed assets. The LVC concepts used for the UAS in the NAS project include live aircraft, flight simulators, and virtual air traffic control assets operating at facilities distributed across multiple NASA Centers. With a distributed network, however, there is a concern that message latency could impact the realism of a simulation and its data. The latencies associated with sending data among these distributed facilities were, therefore, measured to ensure that they fall within acceptable parameters. Several live and virtual test assets were integrated into the LVC infrastructure including NASA Armstrong’s Ikhana MQ-9 unmanned aircraft, NASA Glenn’s S3-B manned aircraft, and the B747 flight simulator at NASA Ames. Average latencies from 100 to 150 milliseconds were observed between the LVC System running at NASA Ames and each of the participating NASA Centers under a light-to-moderate (fifty aircraft) traffic sample.

Murphy, James R.↗

NASA NTRS2016

Piloted Well Clear Performance Evaluation of Detect and Avoid Systems with Suggestive Guidance

Regulations to establish operational and performance requirements for unmanned aircraft systems (UAS) are being developed by a consortium of government, industry and academic institutions (RTCA, 2013). Those requirements will apply to the new detect-and-avoid (DAA) systems and other equipment necessary to integrate UAS with the United States (U.S) National Airspace System (NAS) and will be determined according to their contribution to the overall safety case. That safety case requires demonstration that DAA-equipped UAS collectively operating in the NAS meet an airspace safety threshold (AST). Several key gaps must be closed in order to link equipment requirements to an airspace safety case. Foremost among these is calculation of the systems risk ratio, the degree to which a particular system mitigates violation of an aircraft separation standard (FAA, 2013). The risk ratio of a DAA system, in combination with risk ratios of other collision mitigation mechanisms, will determine the overall safety of the airspace measured in terms of the number of collisions per flight hour. It is not known what the effectiveness is of a pilot-in-the-loop DAA system or even what parameters of the DAA system most improve the pilots ability to maintain separation. The relationship between the DAA system design and the overall effectiveness of the DAA system that includes the pilot, expressed as a risk ratio, must be determined before DAA operational and performance requirements can be finalized. Much research has been devoted to integrating UAS into non-segregated airspace (Dalamagkidis, 2009, Ostwald, 2007, Gillian, 2012, Hesselink, 2011, Santiago, 2015, Rorie 2015 and 2016). Several traffic displays intended for use as part of a DAA system have gone through human-in-the-loop simulation and flight-testing. Most of these evaluations were part of development programs to produce a deployable system, so it is unclear how to generalize particular aspects of those designs to general requirements for future traffic displays (Calhoun, 2014). Other displays have undergone testing to collect data that may generalize to new displays, but have not been evaluated in the context of the development of an overall safety case for UAS equipped with DAA systems in the NAS (Bell, 2012). Other research efforts focus on DAA surveillance performance and separation standards. Together with this work, they are expected to facilitate validation of the airspace safety case (Park, 2014 and Johnson, 2015). The contribution of the present work is to quantify the effectiveness of the pilot-automation system to remain well clear as a function of display features and surveillance sensor error. This quantification will help enable selection of a minimum set of DAA design features that meets the AST, a set that may not be unique for all UAS platforms. A second objective is to collect and analyze pilot performance parameters that will improve the modeling of overall DAA system performance in non-human-in-the-loop simulations. Simulating the DAA-equipped UAS in such batch experiments will allow investigation of a much larger number of encounters than is possible in human simulations. This capability is necessary to demonstrate that a particular set of DAA requirements meets the AST under all foreseeable operational conditions.

detect and avoid↗

NASA NTRS2016

Application of an ADS-B Sense and Avoid Algorithm

The National Aeronautics and Space Administration Armstrong Flight Research Center in Edwards, California is leading a program aimed towards integrating unmanned aircraft system into the national airspace system (UAS in the NAS). The overarching goal of the program is to reduce technical barriers associated with related safety issues as well as addressing challenges that will allow UAS routine access to the national airspace. This research paper focuses on three novel ideas: (1) A design of an integrated UAS equipped with Automatic Dependent Surveillance-Broadcast that constructs a more accurate state-based airspace model; (2) The use of Stratway Algorithm in a real-time environment; and (3) The verification and validation of sense and avoid performance and usability test results which provide a pilot's perspective on how our system will benefit the UAS in the NAS program for both piloted and unmanned aircraft.

ADS-B↗

NASA NTRS2010

Integrated Tests and Evaluations

NASA has developed a project plan to address issues related to UAS access to the NAS The plan is being formulated with inputs from our stakeholders. NASA will work with our stakeholders to develop ConOps and a national roadmap to determine key research technologies and policy issues to enable UAS access to the NAS. NASA will use ConOps and roadmap to either validate current NASA research investment areas and make any necessary changes to proposed UAS research portfolio. NASA will conduct integration and testing of key research areas to enable UAS access to the NAS. Use phase I to do detailed test planning for phase II Assist subelements with test planning Assist with documenting test objectives, data and facilities/infrastructure requirements, and detailed test planning Provide facilities/infrastructure to meet test requirements Provide interfaces between tools Develop, document, and execute data handling and dissemination plans Provide a test engineer to facilitate scheduling of facilities, support specific equipment and software needs, track schedule progress, and monitor changes to schedule Provide guidance for alternative facilities or equipment to mitigate risk associated with loss of availability Provide opportunities for subelements to gather data in relevant and increasingly complex environments

Bixby, C. J.↗

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

A Detect and Avoid System in the Context of Multiple-Unmanned Aircraft Systems Operations

NASA's Unmanned Aircraft Systems Integration into the National Airspace System (UAS in the NAS) project examines the technical barriers associated with the operation of UAS in civil airspace. For UAS, the removal of the pilot from onboard the aircraft has eliminated the ability of the ground-based pilot in command (PIC) to use out-the-window visual information to make judgements about a potential threat of a loss of well clear with another aircraft. NASA's Phase 1 research supported the development of a Detect and Avoid (DAA) system that supports the ground-based pilot's ability to detect potential traffic conflicts and determine a resolution maneuver, but existing display/alerting requirements did not account for multiple UAS control (1:N). Demands for increased scalability of UAS in the NAS operations are expected to create a need for simultaneous control of UAs, and thus, a new DAA HMI design will likely be necessary. Previous research, however, has found performance degradations as the number of vehicles under operator control has increased. The purpose of the current human-in-the-loop (HITL) simulation was to examine the viability of 1:N operations with the Phase 1 DAA alerting and guidance. Sixteen UAS pilots flew three scenarios with varying number of UAs under their control (1:1, 1:3, 1:5). In addition to their supervisory and sensor mission responsibilities, pilots were to utilize the DAA system to remain DAA well clear (DWC) during scripted conflicts of mixed severity. Measured response times, separation performance, mission task data, and subjective feedback were collected to assess how the multi-UAS control configuration impacted pilots' ability to maintain DAA well clear and perform the mission tasks. Overall, the DAA system proved surprisingly adaptive to multi-UAS control for preventing losses of DAA well clear (LoDWC). The findings suggest that, while multi-UAS operators are able to maintain safe separation (DWC) from other traffic, their ability to efficiently perform missions drastically decreases with their number of controlled vehicles. Pilot feedback indicated that, for this context, the use of automation support tools for completing and managing mission tasks would be appropriate and desired, especially for ensuring efficient use of assets. Finally, human-machine interface (HMI) design considerations for multi-UAS operations are discussed.

Monk, Kevin J.↗

NASA NTRSDate not supplied

An Examination of Two Non-Cooperative Detect and Avoid Well Clear Definitions

NASA’s Unmanned Aircraft Systems Integration into the National Airspace System (UAS in the NAS) project examines the technical barriers associated with the operation of UAS in civil airspace. The present study explored the differential effects of two candidate non-cooperative Detect-and-Avoid Well Clear (DWC)definitions on pilot and system performance in a human-in-the-loop simulation. Active-duty UAS pilots were recruited to maintain DWC against representative Class 4 encounter types with a low size, weight, and power (SWaP) radar declaration range of 3.5 nautical miles (nmi). Objective performance indicated that pilots could consistently maintain DWC against non-cooperative intruders with either DWC candidate, with negligible differences in response times and separation performance against caution and warning-level threats. While losses of DWC were avoided at rates comparable to Phase 1 findings, pilots uploaded their responses to caution-level alerts over 5 seconds faster in the current setup relative to Phase 1. Encounters with faster closure rates were susceptible to shortened caution-level alert durations, especially when employing the DWC criterion with the additional ‘Tau’ (temporal) component. Consequently, caution-level threats frequently elevated to warning-level status (nearly twice as often with theTau candidate). The variable caution alert durations appeared to impact pilots’ coordination with air traffic control (ATC), as ATC approval rates were lower with the ‘Tau’and ‘Disc’ candidates relative to Phase 1 research. Ultimately, the increased alerting time enabled by the Disc candidate deemed it more suitable for any reductions to the assumed radar declaration range requirement, which was re-evaluated in a follow-on study. Findings from this study will inform Phase 2 Minimum Operational Performance Standards (MOPS)development for UAS with alternative surveillance equipment and performance capabilities.

Kevin J Monk↗

NASA NTRS2016

Crowd Sourcing Approach for UAS Communication Resource Demand Forecasting

Congressional attention to Unmanned Aircraft Systems (UAS) has caused the Federal Aviation Administration (FAA) to move the National Airspace System (NAS) Integration project forward, but using guidelines, practices and procedures that are yet to be fully integrated with the FAA Aviation Management System. The real drive for change in the NAS will to come from both UAS operators and the government jointly seeing an accurate forecast of UAS usage demand data. This solid forecast information would truly get the attention of planners. This requires not an aggregate demand, but rather a picture of how the demand is spread across small to large UAS, how it is spread across a wide range of missions, how it is expected over time and where, in terms of geospatial locations, will the demand appear. In 2012 the Volpe Center performed a study of the overall future demand for UAS. This was done by aggregate classes of aircraft types. However, the realistic expected demand will appear in clusters of aircraft activities grouped by similar missions on a smaller geographical footprint and then growing from those small cells. In general, there is not a demand forecast that is tightly coupled to the real purpose of the mission requirements (e.g. in terms of real locations and physical structures such as wind mills to inspect, farms to survey, pipelines to patrol, etc.). Being able to present a solid basis for the demand is crucial to getting the attention of investment, government and other fiscal planners. To this end, Mosaic ATM under NASA guidance is developing a crowd sourced, demand forecast engine that can draw forecast details from commercial and government users and vendors. These forecasts will be vetted by a governance panel and then provide for a sharable accurate set of projection data. Our paper describes the project and the technical approach we are using to design and create access for users to the forecast system.

air traffic↗

NASA NTRS2018

An Interoperability Concept for Detect and Avoid and Collision Avoidance Systems: Results from a Human-In-The-Loop Simulation

The integration of Unmanned Aircraft Systems (UAS) into the National Airspace System (NAS) poses a variety of technical challenges to UAS developers and aviation regulators. In response to growing demand for access to civil airspace in the United States, the Federal Aviation Administration (FAA) has produced a roadmap identifying key areas requiring further research and development. One such technical challenge is the development of a "detect and avoid" system (DAA) capable of providing a means of compliance with the "see and avoid" requirement in manned aviation. The purpose of the DAA system is to support the pilot, situated at a ground control station (GCS), in maintaining "DAA well clear" of nearby aircraft through the use of GCS displays and alerts. In addition to its primary function of aiding the pilot in maintaining DAA well clear, the DAA system must also safely interoperate with existing NAS systems and operations, such as the airspace management procedures of air traffic controllers (ATC) and Collision Avoidance (CA) systems currently in use by manned aircraft, namely the Traffic Alert and Collision Avoidance System (TCAS II). It is anticipated that many UAS architectures will integrate both a DAA system and a TCAS II. It is therefore necessary to explicitly study the integration of DAA and TCAS II alerting structures and maneuver guidance formats to ensure that pilots understand the appropriate type and urgency of their response to the various alerts. This paper presents a concept of interoperability for the two systems. The concept was developed with the goal of avoiding any negative impact on the performance level of TCAS II while retaining a DAA system that still effectively enables pilots to maintain DAA well clear. The interoperability concept described in the paper focuses primarily on facilitating the transition from a late-stage DAA encounter (where a loss of DAA well clear is imminent) to a TCAS II Corrective Resolution Advisory (RA), which requires pilot compliance within five seconds of its issuance. The interoperability concept was presented to 10 participants (6 active UAS pilots and 4 active commercial pilots) in a medium-fidelity, human-in-the-loop simulation designed to stress different aspects of the DAA and TCAS II systems. Pilots' ability to maintain separation, their rate of compliance and response times using the interoperability concept are reported. Results indicated that pilots exhibited comprehension of, and appropriate prioritization within, the DAA-TCAS II combined alert structure. Pilots demonstrated a high rate of compliance with TCAS II RAs and were also seen to respond to corrective RAs within the five second requirement established for manned aircraft. The DAA system presented under test was also shown to be effective in supporting pilots' ability to maintain DAA well clear in the overwhelming majority of cases in which pilots had sufficient time to respond.

Rorie, R. Conrad↗

NASA NTRS2018

An Interoperability Concept for Detect and Avoid and Collision Avoidance Systems: Results from a Human-In-The-Loop Simulation

unmanned aircraft systems↗

NASA NTRS2018

Performing a Comprehensive Unmanned Aircraft System Full Integration Analysis for NASA ARMD

For many years, the concept of routinely flying unmanned aircraft systems (UAS) within the national airspace system (NAS) has been a long-term goal with numerous known and unknown technology and policy obstacles. Just within the last few years, the efforts and advancements from government, industry, and academia-sponsored research and development have greatly shortened the distance to the goal. The National Aeronautics and Space Administration (NASA) Aeronautics Research Mission Directorate (ARMD) has recognized that it is uniquely positioned to play a lead role in addressing the remaining UAS airspace integration (AI) challenges. To fully understand the magnitude and scope of these challenges, NASA ARMD initiated a study in 2015 to identify what would be needed to enable full integration of UAS for civil/commercial operations within the NAS by 2025. The desired outcome was a comprehensive analysis framework that ARMD could use to develop a research portfolio focused on retiring the remaining gaps and challenges standing in the way of full UAS integration. This document is a comprehensive assessment of UAS integration research to date.

UAS in the NAS↗

NASA NTRS2021

Bell Unmanned Aircraft Systems Integration and Operationalization (SIO) Demonstration: Final Report, Summary of Research

National Aeronautics and Space Administration (NASA) initiated the Unmanned Aircraft Systems Integration and Operationalization (SIO) demonstration as a partnership between NASA and Industry with the goal of accelerating routine unmanned aircraft systems (UAS) operations in the national airspace (NAS). In order to accomplish this goal, NASA partnered separately with Bell and two other industry teams each pioneering the development, integration, and testing of their UAS, with the intent to make progress towards type certification. The program culminated in flight demonstrations representing future commercial operations by each partner.

Flight Demonstration↗

NASA NTRS2019

Airborne Radar for sUAS Sense and Avoid

A primary challenge for the safe integration of small UAS operations into the National Airspace System (NAS) is traffic deconfliction, both from manned and unmanned aircraft. The UAS Traffic Management (UTM) project being conducted at the National Aeronautics and Space Administration (NASA) considers a layered approach to separation provision, ranging from segregation of operations through airspace volumes (geofences) to autonomous sense and avoid (SAA) technologies for higher risk, densely occupied airspace. Cooperative SAA systems, such as Automatic Dependent Surveillance-Broadcast (ADS-B) and/or vehicle-to-vehicle communication systems provide significant additional risk mitigation but they fail to adequately mitigate collision risks for non-cooperative (non-transponder equipped) airborne aircraft. The RAAVIN (Radar on Autonomous Aircraft to Verify ICAROUS Navigation) flight test being conducted by NASA and the Mid-Atlantic Aviation Partnership (MAAP) was designed to investigate the applicability and performance of a prototype, commercially available sUAS radar to detect and track non-cooperative airborne traffic, both manned and unmanned. The radar selected for this research was a Frequency Modulated Continuous Wave (FMCW) radar with 120 degree azimuth and 80 degree elevation field of view operating at 24.55GHz center frequency with a 200 MHz bandwidth. The radar transmits 2 watts of power thru a Metamaterial Electronically Scanning Array antenna in horizontal polarization. When the radar is transmitting, personnel must be at least 1 meter away from the active array to limit nonionizing radiation exposure. The radar physical dimensions are 18.7cm by 12.1cm by 4.1cm and it weighs less than 820 grams making it well suited for installation on small UASs. The onboard, SAA capability, known as ICAROUS, (Independent Configurable Architecture for Reliable Operations of Unmanned Systems), developed by NASA to support sUAS operations, will provide autonomous guidance using the traffic radar tracks from the onboard radar. The RAAVIN set of studies will be conducted in three phases. The first phase included outdoor, ground-based radar evaluations performed at the Virginia Tech’s Kentland Farm testing range in Blacksburg, VA. The test was designed to measure how well the radar could detect and track a small UAS flying in the radar’s field of view. The radar was used to monitor 5 test flights consisting of outbound, inbound and crossing routes at different ranges and altitudes. The UAS flown during the ground test was the Inspire 2, a quad copter weighing less than 4250 grams (10 pounds) at maximum payload. The radar was set up to scan and track targets over its full azimuthal field of view from 0 to 40 degrees in elevation. The radar was configured to eliminate tracks generated from any targets located beyond 2000 meters from the radar and moving at velocities under 1.45 meters per second. For subsequent phases of the study the radar will be integrated with a sUAS platform to evaluate its performance in flight for SAA applications ranging from sUAS to manned GA aircraft detections and tracking. Preliminary data analysis from the first outdoor ground tests showed the radar performed well at tracking the vehicle as it flew outbound and repeatedly maintained a track out to 1000 meters (maximum 1387 meters) until the vehicle slowed to a stop to reverse direction to fly inbound. As the Inspire flew inbound tracks from beyond 800 meters, a reacquisition time delay was consistently observed between when the Inspire exceeds a speed of 1.45 meters per second and when the radar indicated an inbound target was present and maintained its track. The time delay varied between 6 seconds to over 37 seconds for the inbound flights examined, and typically resulted in about a 200 meter closure distance before the Inspire track was maintained. The radar performed well at both acquiring and tracking the vehicle as it flew crossing routes out past 400 meters across the azimuthal field of view. The radar and ICAROUS software will be integrated and flown on a BFD-1400-SE8-E UAS during the next phase of the RAAVIN project. The main goal at the conclusion of this effort is to determine if this radar technology can reliably support minimum requirements for SAA applications of sUAS. In particular, the study will measure the range of vehicle detections, lateral and vertical angular errors, false and missed/late detections, and estimated distance at closest point of approach after an avoidance maneuver is executed. This last metric is directly impacted by sensor performance and indicates its suitability for the task.

Szatkowski, George N.↗

NASA NTRS2013

Spectrum for UAS Control and Non-Payload Communications

There is an increasing need to fly UAS in the NAS to perform missions of vital importance to National Security and Defense, Emergency Management, and Science as well as commercial applications (e.g. cargo transport). To enable integration of UAS into the National Airspace System, several critical technical barriers must be eliminated, including: Separation Assurance/Sense and Avoid - the uncertainty surrounding the ability to interoperate in ATC environments and maintain safe separation from other aircraft in the absence of an on-board pilot. Human Systems Integration - lack of standards and guidelines with respect to UAS display information as well as lack of Ground Control Station (GCS) design requirements to operate in the NAS. Certification - lack of airworthiness requirements and safety-related data specific to the full range of UAS, or for their avionics systems or other components. Communications - lack of standard, certifiable data links and aviation safety spectrum to operate such links for civil UAS control communications.

Kerczewski, Robert J.↗