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NASA NTRSDate not supplied

Management of Operations under Visual Flight Rules in UTM for Disaster Response Missions

The disaster response domain has experienced an increased focus in recent years due to the rise in number and scale of events, lessons learned from past experience, and emerging technologies that make possible a more coordinated and effective response. As part of this focus, JAXA and NASA have been collaborating on the integration of manned and unmanned aircraft in support of disaster response operations through integrated testing of their respective mission planning and optimization system (Disaster Relief Aircraft Information Sharing Network, or D-NET) and an automated UAS traffic management system (e.g., UTM). In 2018, JAXA and NASA jointly participated in a large-scale disaster drill in Japan where the integration of systems was successfully demonstrated through real-time data exchanges, visualization, and decision making as part of the coordinated airspace management of a manned helicopter in VFR conditions and unmanned small UAS operating in common areas. This work details a flight test consisting of two flights that were conducted December 2019 near the Chofu Aerodrome in Tokyo, which focused on the evaluation of pilots operating under Visual Flight Rules (VFR) communicating through D-NET and sharing intent and position information within UTM. This work contributes to defining the necessary requirements for digital coordination between manned and unmanned operations. UTM requires the use of operation volumes, which are spatial and temporal volumes that encompass UAS flight trajectories and account for technical performance errors and deviations due to disturbances (e.g., wind). A series of flights, representing different missions, used landmark-based operation volumes and conformance of the aircraft to those operation volumes were tracked within UTM. Experienced disaster response helicopter pilots provided insight on the development of the operation plans and their usability during disaster response operations. Results from the flight test supported the suggested benefits of using landmarks for planning and positional awareness and highlighted the need for future research in advanced visualization capabilities to support operations that consider both system constraints and flight deck/airspace management interaction.

disaster response↗

NASA NTRS2006

Conflict-Aware Scheduling Algorithm

conflict-aware scheduling algorithm is being developed to help automate the allocation of NASA s Deep Space Network (DSN) antennas and equipment that are used to communicate with interplanetary scientific spacecraft. The current approach for scheduling DSN ground resources seeks to provide an equitable distribution of tracking services among the multiple scientific missions and is very labor intensive. Due to the large (and increasing) number of mission requests for DSN services, combined with technical and geometric constraints, the DSN is highly oversubscribed. To help automate the process, and reduce the DSN and spaceflight project labor effort required for initiating, maintaining, and negotiating schedules, a new scheduling algorithm is being developed. The scheduling algorithm generates a "conflict-aware" schedule, where all requests are scheduled based on a dynamic priority scheme. The conflict-aware scheduling algorithm allocates all requests for DSN tracking services while identifying and maintaining the conflicts to facilitate collaboration and negotiation between spaceflight missions. These contrast with traditional "conflict-free" scheduling algorithms that assign tracks that are not in conflict and mark the remainder as unscheduled. In the case where full schedule automation is desired (based on mission/event priorities, fairness, allocation rules, geometric constraints, and ground system capabilities/ constraints), a conflict-free schedule can easily be created from the conflict-aware schedule by removing lower priority items that are in conflict.

Wang, Yeou-Fang↗

NASA NTRS1989

Parallel plan execution with self-processing networks

A critical issue for space operations is how to develop and apply advanced automation techniques to reduce the cost and complexity of working in space. In this context, it is important to examine how recent advances in self-processing networks can be applied for planning and scheduling tasks. For this reason, the feasibility of applying self-processing network models to a variety of planning and control problems relevant to spacecraft activities is being explored. Goals are to demonstrate that self-processing methods are applicable to these problems, and that MIRRORS/II, a general purpose software environment for implementing self-processing models, is sufficiently robust to support development of a wide range of application prototypes. Using MIRRORS/II and marker passing modelling techniques, a model of the execution of a Spaceworld plan was implemented. This is a simplified model of the Voyager spacecraft which photographed Jupiter, Saturn, and their satellites. It is shown that plan execution, a task usually solved using traditional artificial intelligence (AI) techniques, can be accomplished using a self-processing network. The fact that self-processing networks were applied to other space-related tasks, in addition to the one discussed here, demonstrates the general applicability of this approach to planning and control problems relevant to spacecraft activities. It is also demonstrated that MIRRORS/II is a powerful environment for the development and evaluation of self-processing systems.

Dautrechy, C. Lynne↗

NASA NTRS1989

Parallel plan execution with self-processing networks

D'Autrechy, C. Lynne↗

NASA NTRSDate not supplied

An Augmented Ground Station Architecture for Spacecraft-Initiated Communication Service Requests

Spacecraft performing science and exploration missions have increasingly complex and event-driven objectives, making communication needs difficult to predict in advance. Additional flexibility is required in space communication provider networks to effectively meet time-varying demand. We envision a framework for automated resource allocation in which requests for communications service are initiated by spacecraft based on current mission needs. We propose an augmented ground station configuration featuring a wide field-of-view antenna to receive transmissions from spacecraft requesting high-rate communications. A software suite to automate the service fulfillment process, including interfacing with external scheduling systems such as NASA’s Near Space Network, is described. Experimental results characterizing the physical-layer link between the wide field-of-view antenna and a software-defined radio testbed on the International Space Station are presented. We also discuss long-duration software testing on a ground-based testbed. Taken together, these proof-of-concept results demonstrate the feasibility of the concept to improve the responsiveness of space communications.

user-initiated service↗

NASA NTRS1997

Knowledge-Based Aircraft Automation: Managers Guide on the use of Artificial Intelligence for Aircraft Automation and Verification and Validation Approach for a Neural-Based Flight Controller

The ultimate goal of this report was to integrate the powerful tools of artificial intelligence into the traditional process of software development. To maintain the US aerospace competitive advantage, traditional aerospace and software engineers need to more easily incorporate the technology of artificial intelligence into the advanced aerospace systems being designed today. The future goal was to transition artificial intelligence from an emerging technology to a standard technology that is considered early in the life cycle process to develop state-of-the-art aircraft automation systems. This report addressed the future goal in two ways. First, it provided a matrix that identified typical aircraft automation applications conducive to various artificial intelligence methods. The purpose of this matrix was to provide top-level guidance to managers contemplating the possible use of artificial intelligence in the development of aircraft automation. Second, the report provided a methodology to formally evaluate neural networks as part of the traditional process of software development. The matrix was developed by organizing the discipline of artificial intelligence into the following six methods: logical, object representation-based, distributed, uncertainty management, temporal and neurocomputing. Next, a study of existing aircraft automation applications that have been conducive to artificial intelligence implementation resulted in the following five categories: pilot-vehicle interface, system status and diagnosis, situation assessment, automatic flight planning, and aircraft flight control. The resulting matrix provided management guidance to understand artificial intelligence as it applied to aircraft automation. The approach taken to develop a methodology to formally evaluate neural networks as part of the software engineering life cycle was to start with the existing software quality assurance standards and to change these standards to include neural network development. The changes were to include evaluation tools that can be applied to neural networks at each phase of the software engineering life cycle. The result was a formal evaluation approach to increase the product quality of systems that use neural networks for their implementation.

Broderick, Ron↗

NASA NTRS2009

Neural Network Target Identification System for False Alarm Reduction

A multi-stage automated target recognition (ATR) system has been designed to perform computer vision tasks with adequate proficiency in mimicking human vision. The system is able to detect, identify, and track targets of interest. Potential regions of interest (ROIs) are first identified by the detection stage using an Optimum Trade-off Maximum Average Correlation Height (OT-MACH) filter combined with a wavelet transform. False positives are then eliminated by the verification stage using feature extraction methods in conjunction with neural networks. Feature extraction transforms the ROIs using filtering and binning algorithms to create feature vectors. A feed forward back propagation neural network (NN) is then trained to classify each feature vector and remove false positives. This paper discusses the test of the system performance and parameter optimizations process which adapts the system to various targets and datasets. The test results show that the system was successful in substantially reducing the false positive rate when tested on a sonar image dataset.

ATR↗

NASA NTRS2005

Automated Synthesis of Long Communication Delays for Testing

Planetary-Ohio Network Emulator (p- ONE) is a computer program for local laboratory testing of high bandwidth data-communication systems subject to long delays in propagation over interplanetary distances. p-ONE is installed on a personal computer connected to two bidirectional Ethernet interfaces, denoted A and B, that represent local-area networks at opposite ends of a long propagation path. Traffic that is to be passed between A and B is encapsulated in IP (Internet Protocol) packets (e.g., User Data Protocol, UDP). Intercepting this traffic between A and B in both directions, p-ONE time-tags each packet and stores it in memory or on the hard disk of the computer for a user-specified interval that equals the propagation delay to be synthesized. At the expiration of its storage time, each such packet is sent to its destination (that is, if it was received from A, it is sent to B, or vice versa). The accuracy of the p-ONE software is very high, with zero packet loss through the system and negligible latency. Optionally, p-ONE can be configured to delay all network traffic to and from all network addresses on each Ethernet interface or to selectively delay traffic between specific addresses or traffic of specific types. p-ONE works well with Linux and is also designed to be compatible with other operating systems.

Seibert, Marc↗

NASA NTRS1983

Packet telemetry and packet telecommand - The new generation of spacecraft data handling techniques

Because of rising costs and reduced reliability of spacecraft and ground network hardware and software customization, standardization Packet Telemetry and Packet Telecommand concepts are emerging as viable alternatives. Autonomous packets of data, within each concept, which are created within ground and space application processes through the use of formatting techniques, are switched end-to-end through the space data network to their destination application processes through the use of standard transfer protocols. This process may result in facilitating a high degree of automation and interoperability because of completely mission-independent-designed intermediate data networks. The adoption of an international guideline for future space telemetry formatting of the Packet Telemetry concept, and the advancement of the NASA-ESA Working Group's Packet Telecommand concept to a level of maturity parallel to the of Packet Telemetry are the goals of the Consultative Committee for Space Data Systems. Both the Packet Telemetry and Packet Telecommand concepts are reviewed.

Hooke, A. J.↗

NASA NTRS1984

Data management

The following tasks were prioritized: software acquisition management plan; space station flight data system architectural study; space station user data system interface; automation of software development process; automation of software testing; distributed data base management; ADA (automated data acquisition) evaluation and transition and planning; network operating system software; fault tolerant computer validation methodology for onboard data management system; systems integration; artificial intelligence/expert systems; space station data network concept; space station standard interface protocols; space station data networks systems; integrated software development facility; and language trade studies.

Love, G.↗

NASA NTRS1985

Improving management decision processes through centralized communication linkages

Information flow is a critical element to intelligent and timely decision-making. At NASA's Johnson Space Center the flow of information is being automated through the use of a centralized backbone network. The theoretical basis of this network, its implications to the horizontal and vertical flow of information, and the technical challenges involved in its implementation are the focus of this paper. The importance of the use of common tools among programs and some future concerns related to file transfer, graphics transfer, and merging of voice and data are also discussed.

Simanton, D. F.↗

NASA NTRS1987

First Annual Workshop on Space Operations Automation and Robotics (SOAR 87)

Several topics relative to automation and robotics technology are discussed. Automation of checkout, ground support, and logistics; automated software development; man-machine interfaces; neural networks; systems engineering and distributed/parallel processing architectures; and artificial intelligence/expert systems are among the topics covered.

Griffin, Sandy↗

NASA NTRS1992

Use of Convex supercomputers for flight simulation at NASA Langley

The use of the Convex Computer Corporation supercomputers for flight simulation is discussed focusing on a real-time input/output system for supporting the flight simulation. The flight simulation computing system is based on two single processor control data corporation CYBER 175 computers, coupled through extended memory. The Advanced Real-Time Simulation System for digital data distribution and signal conversion is a state-of-the-art, high-speed fiber-optic-based, ring network system which is based on the computer automated measurement and control technology.

Cleveland, Jeff I., II↗

NASA NTRS2005

Hydrogen Sensors Boost Hybrids; Today's Models Losing Gas?

Advanced chemical sensors are used in aeronautic and space applications to provide safety monitoring, emission monitoring, and fire detection. In order to fully do their jobs, these sensors must be able to operate in a range of environments. NASA has developed sensor technologies addressing these needs with the intent of improving safety, optimizing combustion efficiencies, and controlling emissions. On the ground, the chemical sensors were developed by NASA engineers to detect potential hydrogen leaks during Space Shuttle launch operations. The Space Shuttle uses a combination of hydrogen and oxygen as fuel for its main engines. Liquid hydrogen is pumped to the external tank from a storage tank located several hundred feet away. Any hydrogen leak could potentially result in a hydrogen fire, which is invisible to the naked eye. It is important to detect the presence of a hydrogen fire in order to prevent a major accident. In the air, the same hydrogen-leak dangers are present. Stress and temperature changes can cause tiny cracks or holes to form in the tubes that line the Space Shuttle s main engine nozzle. Such defects could allow the hydrogen that is pumped through the nozzle during firing to escape. Responding to the challenges associated with pinpointing hydrogen leaks, NASA endeavored to improve propellant leak-detection capabilities during assembly, pre-launch operations, and flight. The objective was to reduce the operational cost of assembling and maintaining hydrogen delivery systems with automated detection systems. In particular, efforts have been focused on developing an automated hydrogen leak-detection system using multiple, networked hydrogen sensors that are operable in harsh conditions.

Source record↗

NASA NTRS2007

Eye Safe, Visible Wavelength Lidar Systems: Design and Operational Advances, Results and Potential

In the early nineties the first of the eye safe visible wavelength lidar systems known now as Micro Pulse Lidar (MPL) became operational. The important advance of the design was a system that, unlike most existing lidar, operated at eye safe energy densities and could thus operate unattended for full time monitoring. Since that time there have been many dozens of these systems produced and applied for full time profiling of atmospheric cloud and aerosol structure. There is currently an observational network of MPL sites to support global climate research. In thc course of application of these instruments there have been significant improvements in the, design and performance of the systems. In the last half decade particularly there has been significant application and technical development of MPL systems. In this paper we review progress. The current MPL systems in use are all single wavelength systems designed for cloud and aerosol applications. For the cloud and aerosol applications, both lidar depolarization and multi wavelength measurements have significant applications. These can be accomplished with the MPL, approach. The main current challenge for the lidar network activity are in the area of the reliability, repeatability and efficiency of data processing. The network makes use of internet data downloads and automated processing. The heights of all cloud and aerosol layers are needed. The recent emphasis has been in operationally deriving aerosol extinction cross section. Future emphasis will include adding cirrus optical parameters. For operational effectiveness, improvements to simplify routine data signal calibration are being researched. Overall the MPL systems have proven very effective. A large data base of results from globally distributed sites can be easily accessed through the internet. Applications have included atmospheric model development. Validation of current global satellite observations of aerosol and clouds, including now orbital lidar observations, was a primary goal for NASA. Although sampling issues require careful consideration, results have proven useful.

Spinhirne, James↗

NASA NTRS1997

Resource Scheduling for a Network of Communications Antennas

This paper describes tha Demand Access Network Scheduler (DANS) system for automatically scheduling and rescheduling resources for a network of communication antennas. DANS accepts a baseline schedule and supports rescheduling of antenna and subsystem resources to satisfy tracking goals in the event of changing track requests, equipment outages, and inclement weather.

Deep↗

NASA NTRS2002

Verification and Validation of Neural Networks for Aerospace Systems

The Dryden Flight Research Center V&V working group and NASA Ames Research Center Automated Software Engineering (ASE) group collaborated to prepare this report. The purpose is to describe V&V processes and methods for certification of neural networks for aerospace applications, particularly adaptive flight control systems like Intelligent Flight Control Systems (IFCS) that use neural networks. This report is divided into the following two sections: Overview of Adaptive Systems and V&V Processes/Methods.

Mackall, Dale↗

NASA NTRS2002

Verification and Validation of Neural Networks for Aerospace Systems

The Dryden Flight Research Center V&V working group and NASA Ames Research Center Automated Software Engineering (ASE) group collaborated to prepare this report. The purpose is to describe V&V processes and methods for certification of neural networks for aerospace applications, particularly adaptive flight control systems like Intelligent Flight Control Systems (IFCS) that use neural networks. This report is divided into the following two sections: 1) Overview of Adaptive Systems; and 2) V&V Processes/Methods.

Mackall, Dale↗