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At least 217 records · Page 12

Enhancing Autonomous Satellite Communication Systems with Weather-Aware Scheduling and Reconfiguration

NASA currently provides communication support to over 100 satellite missions, and the agency is driving developments in Ka-band communications and network management automation to support additional future missions. At Ka-band frequencies, rain can degrade a communication link by more than 10 dB, which may be mitigated by agile scheduling and data rate control. We present a weather forecasting module for Ka-band communications that is intended to be used in an autonomous network management service that employs machine-to-machine scheduling systems for dynamic user access opportunities. Our forecasting module (NIMBUS) runs on AWS Cloud, consumes the freely and publicly available NOAA MRMS precipitation rate dataset (1km x 1km x 2-min), produces 30-minute Nowcasts using the pySTEPS algorithm, and publishes high level ground station specific link quality predictions. We evaluate two potential NIMBUS outputs, a binary classifier that predicts rain attenuation greater than 3 dB and a rain attenuation estimator, and we backtest these outputs using one year of power measurement data collected from observations of the geostationary ANIK F2 satellite’s Ka-band beacon. We report, with a 30-minute lead time, a binary classifier accuracy of 84% and an estimator RMSE of 1.67 dB. Additionally, we discuss how the NIMBUS module could be incorporated into a user-initiated service framework to enable weather-aware scheduling and reconfiguration. Operating a static link budget with minimal link margin can increase network operation costs by creating additional scheduling tasks due to failed packets, which may require human intervention and/or lead to inefficient asset utilization. The proposed system aims to increase throughput by reducing link margin, while mitigating increases in network operations costs by leveraging autonomous machine-to-machine scheduling, shortened prediction lead times, and advances in precipitation Nowcasting.

satellite communications↗

On-demand Command and Control of ASTERIA with Cloud-based Ground Station Services

ASTERIA (Arcsecond Space Telescope Enabling Research in Astrophysics) was a 6-unit CubeSat technology demonstration mission that deployed from the International Space Station on November 20th, 2017. After successfully completing its 90-day primary mission that demonstrated arcsecond-level line-of-sight pointing and focal plane thermal stability for exoplanet detection, it entered an extended mission performing onboard software demonstrations to mature technology both in space and on the ground. One of the technologies was a completely cloud-based ground system leveraging Amazon Web Services (AWS) Ground Station service.Announced in December 2018 and launched in May 2019, AWS Ground Station is a fully managed ground station service that aims to reduce the overhead associated with developing and maintaining ground system infrastructure throughout the mission lifecycle. AWS Ground Station makes available the suite of features required for any ground system in support of low-Earth orbit (LEO) and medium-Earth Orbit (MEO) satellite operations on-demand and without setting up or maintaining long-term contracts. Charges are incurred on a per-minute basis for antenna usage during scheduled tracks. Support is available for S-band uplink and downlink, along with X-band narrowband and wideband downlink. Missions that use the service may reserve tracks with any licensed AWS Ground Station antennas located across each service region and have direct access to any AWS services in support of mission operations.The cloud-based architecture built around the AWS Ground Station service greatly enhanced ASTERIA mission operations by enabling end-to-end pass automation, on-demand contact scheduling and contingency planning, along with more efficient data downlink through station availability and station-to-station handovers. It incorporated open-source software, particularly NASA's AMMOS Instrument Toolkit (AIT) and Open Mission Control Technologies (OpenMCT), along with the AWS application programming interfaces (API) to the Ground Station, Elastic Compute Cloud (EC2) and Simple Storage Service (S3) services. After showcasing operability in August 2019, the team continued using and improving this novel ground system architecture until the end of mission in December 2019. This paper describes the cloud-based ground system, how it was designed, tested, and evaluated with an in-orbit spacecraft, the operational capabilities that it enabled, along with lessons learned and recommendations for future missions.

Fesq, Lorraine↗

On-demand Command and Control of ASTERIA with Cloud-based Ground Station Services

ASTERIA (Arcsecond Space Telescope Enabling Research in Astrophysics) was a 6-unit CubeSat technology demonstration mission that deployed from the International Space Station on November 20th, 2017. After successfully completing its 90-day primary mission that demonstrated arcsecond-level line-of-sight pointing and focal plane thermal stability for exoplanet detection, it entered an extended mission performing onboard software demonstrations to mature technology both in space and on the ground. One of the technologies was a completely cloud-based ground system leveraging Amazon Web Services (AWS) Ground Station service. Announced in December 2018 and launched in May 2019, AWS Ground Station is a fully managed ground station service that aims to reduce the overhead associated with developing and maintaining ground system infrastructure throughout the mission lifecycle. AWS Ground Station makes available the suite of features required for any ground system in support of low-Earth orbit (LEO) and medium-Earth Orbit (MEO) satellite operations on-demand and without setting up or maintaining long-term contracts. Charges are incurred on a per-minute basis for antenna usage during scheduled tracks. Support is available for S-band uplink and downlink, along with X-band narrowband and wideband downlink. Missions that use the service may reserve tracks with any licensed AWS Ground Station antennas located across each service region and have direct access to any AWS services in support of mission operations. The cloud-based architecture built around the AWS Ground Station service greatly enhanced ASTERIA mission operations by enabling end-to-end pass automation, on-demand contact scheduling and contingency planning, along with more efficient data downlink through station availability and station-tostation handovers. It incorporated open-source software, particularly NASA's AMMOS Instrument Toolkit (AIT) and Open Mission Control Technologies (OpenMCT), along with the AWS application programming interfaces (API) to the Ground Station, Elastic Compute Cloud (EC2) and Simple Storage Service (S3) services. After showcasing operability in August 2019, the team continued using and improving this novel ground system architecture until the end of mission in December 2019. This paper describes the cloud-based ground system, how it was designed, tested, and evaluated with an inorbit spacecraft, the operational capabilities that it enabled, along with lessons learned and recommendations for future missions.

Fesq, Lorraine↗

Analysis of Issues for Project Scheduling by Multiple, Dispersed Schedulers (distributed Scheduling) and Requirements for Manual Protocols and Computer-based Support

Although computerized operations have significant gains realized in many areas, one area, scheduling, has enjoyed few benefits from automation. The traditional methods of industrial engineering and operations research have not proven robust enough to handle the complexities associated with the scheduling of realistic problems. To address this need, NASA has developed the computer-aided scheduling system (COMPASS), a sophisticated, interactive scheduling tool that is in wide-spread use within NASA and the contractor community. Therefore, COMPASS provides no explicit support for the large class of problems in which several people, perhaps at various locations, build separate schedules that share a common pool of resources. This research examines the issue of distributing scheduling, as applied to application domains characterized by the partial ordering of tasks, limited resources, and time restrictions. The focus of this research is on identifying issues related to distributed scheduling, locating applicable problem domains within NASA, and suggesting areas for ongoing research. The issues that this research identifies are goals, rescheduling requirements, database support, the need for communication and coordination among individual schedulers, the potential for expert system support for scheduling, and the possibility of integrating artificially intelligent schedulers into a network of human schedulers.

Richards, Stephen F.↗

How do Air Traffic Controllers Use Automation and Tools Differently During High Demand Situations?

In a human-in-the-loop simulation, two air traffic controllers managed identical airspace while burdened with higher than average workload, and while using advanced tools and automation designed to assist with scheduling aircraft on multiple arrival flows to a single meter fix. This paper compares the strategies employed by each controller, and investigates how the controllers' strategies change while managing their airspace under more normal workload conditions and a higher workload condition. Each controller engaged in different methods of maneuvering aircraft to arrive on schedule, and adapted their strategies to cope with the increased workload in different ways. Based on the conclusions three suggestions are made: that quickly providing air traffic controllers with recommendations and information to assist with maneuvering and scheduling aircraft when burdened with increased workload will improve the air traffic controller's effectiveness, that the tools should adapt to the strategy currently employed by a controller, and that training should emphasize which traffic management strategies are most effective given specific airspace demands.

ATC↗

Performance of an Automated System for Control of Traffic in Terminal Airspace

This paper examines the performance of a system that performs automated conflict resolution and arrival scheduling for aircraft in the terminal airspace around major airports. Such a system has the potential to perform separation assurance and arrival sequencing tasks that are currently handled manually by human controllers. The performance of the system is tested against several simulated traffic scenarios that are characterized by the rate at which air traffic is metered into the terminal airspace. For each traffic scenario, the levels of performance that are examined include: number of conflicts predicted to occur, types of resolution maneuver used to resolve predicted conflicts, and the amount of delay for all flights. The simulation results indicate that the percentage of arrivals that required a maneuver that changes the flight's horizontal route ranged between 11% and 15% in all traffic scenarios. That finding has certain implications if this automated system were to be implemented simply as a decision support tool. It is also found that arrival delay due to purely wake vortex separation requirements on final approach constituted only between 29% and 35% of total arrival delay, while the remaining major portion of it is mainly due to delay back propagation effects.

air traffic control↗

An automated system for global atmospheric sampling using B-747 airliners

The global air sampling program utilizes commercial aircrafts in scheduled service to measure atmospheric constituents. A fully automated system designed for the 747 aircraft is described. Airline operational constraints and data and control subsystems are treated. The overall program management, system monitoring, and data retrieval from four aircraft in global service is described.

Lew, K. Q.↗

PERT TIME III

System utilizing time oriented network structure is automated aid for monitoring and scheduling various activities within particular project. Program provides management with means to evaluate accurately status of project and helps control time, cost, and manpower.

Source record↗

Investigation of air transportation technology at Massachusetts Institute of Technology, 1980

Several technological aspects governing air transportation at major airports were investigated. Three major areas were emphasized: (1) development of automated decision making for dynamic scheduling of runway operations at a major airport; (2) flight evaluation of the performance of low cost Loran C receivers; and (3) design of microcomputer based electronic flight displays for general aviation aircraft.

Simpson, R. W.↗

Project Planning and Reporting

Project Planning Analysis and Reporting System (PPARS) is automated aid in monitoring and scheduling of activities within project. PPARS system consists of PPARS Batch Program, five preprocessor programs, and two post-processor programs. PPARS Batch program is full CPM (Critical Path Method) scheduling program with resource capabilities. Can process networks with up to 10,000 activities.

Source record↗

Launching AI in NASA ground systems

This paper will discuss recent operational successes in implementing expert systems to support the complex functions of NASA mission control systems at the Goddard Space Flight Center, including fault detection and diagnosis for real time and engineering analysis functions in the Cosmic Background Explorer and Gamma Ray Observatory missions and automation of resource planning and scheduling functions for various missions. It will also discuss ongoing developments and prototypes that will lead to increasingly sophisticated applications of artificial intelligence. These include the use of neural networks to perform telemetry monitoring functions, the implementation of generic expert system shells that can be customized to telemetry handling functions specific to NASA control centers, the applications of AI in training and user support, the long-term potential of implementing systems based around distributed, cooperative problem solving, and the use of AI to control and assist system development activities.

Perkins, Dorothy C.↗

The development of a Flight Test Engineer's Workstation for the Automated Flight Test Management System

The Automated Flight Test Management System (ATMS) is being developed as part of the NASA Aircraft Automation Program. This program focuses on the application of interdisciplinary state-of-the-art technology in artificial intelligence, control theory, and systems methodology to problems of operating and flight testing high-performance aircraft. The development of a Flight Test Engineer's Workstation (FTEWS) is presented, with a detailed description of the system, technical details, and future planned developments. The goal of the FTEWS is to provide flight test engineers and project officers with an automated computer environment for planning, scheduling, and performing flight test programs. The FTEWS system is an outgrowth of the development of ATMS and is an implementation of a component of ATMS on SUN workstations.

Tartt, David M.↗

The Challenges of Field Testing the Traffic Management Advisor (TMA) in an Operational Air Traffic Control Facility

The Traffic Management Advisor (TMA), the sequence and schedule tool of the Center/TRACON Automation System (CTAS), was evaluated at the Fort Worth Center (ZFW) in the summer of 1996. This paper describes the challenges encountered during the various phases of the TMA field evaluation, which included system (hardware and software) installation, personnel training, and data collection. Operational procedures were developed and applied to the evaluation process that would ensure air safety. The five weeks of field evaluation imposed minimal impact on the hosting facility and provided valuable engineering and human factors data. The collection of data was very much an opportunistic affair, due to dynamic traffic conditions. One measure of the success of the TMA evaluation is that, rather than remove TMA after the evaluation until it could be fully implemented, the prototype TMA is in continual use at ZFW as the fully operational version is readied for implementation.

Hoang, Ty↗

SeaWiFS Postlaunch Technical Report Series: The Fifth Sea-WiFS Intercalibration Round-Robin Experiment (SIRREX-5), July 1996 - Volume 7

This report documents the fifth Sea-viewing Wide Field-of-view Sensor (SeaWiFS) Intercalibration Round-Robin Experiment (SIRREX-5), which was held at the National Institute of Standards and Technology (NIST) on 23-30 July 1996. The agenda for SIRREX-5 was established based on recommendations made during SIRREX-4. For the first time in a SIRREX activity, instrument intercomparisons were performed at field sites, which were near NIST. The goals of SIRREX-5 were to continue the emphasis on training and the implementation of standard measurement practices, investigate the calibration methods and measurement chains in use by the oceanographic community, provide opportunities for discussion, and intercompare selected instruments. As at SIRREX-4, the day was divided between morning lectures and afternoon laboratory exercises. A set of core laboratory sessions were performed: 1) in-water radiant flux measurements; 2) in-air radiant flux measurements; 3) spectral radiance responsivity measurements using the plaque method; 4) device calibration or stability monitoring with portable field sources; and 5) various ancillary exercises designed to illustrate radiometric concepts. Before, during, and after SIRREX-5, NIST calibrated the SIRREX-5 participating radiometers for radiance and irradiance responsivity. The Facility for Automated Spectroradiometric Calibrations (FASCAL) was scheduled for spectral irradiance calibrations for standard lamps during SIRREX-5. Three lamps from the SeaWiFS community were submitted and two were calibrated.

Hooker, Stanford B.↗

Automating the Processing of Earth Observation Data

NASA s vision for Earth science is to build a "sensor web": an adaptive array of heterogeneous satellites and other sensors that will track important events, such as storms, and provide real-time information about the state of the Earth to a wide variety of customers. Achieving this vision will require automation not only in the scheduling of the observations but also in the processing of the resulting data. To address this need, we are developing a planner-based agent to automatically generate and execute data-flow programs to produce the requested data products.

Golden, Keith↗

Automated Data Processing as an AI Planning Problem

NASA s vision for Earth Science is to build a "sensor web"; an adaptive array of heterogeneous satellites and other sensors that will track important events, such as storms, and provide real-time information about the state of the Earth to a wide variety of customers. Achieving his vision will require automation not only in the scheduling of the observations but also in the processing af tee resulting data. Ta address this need, we have developed a planner-based agent to automatically generate and execute data-flow programs to produce the requested data products. Data processing domains are substantially different from other planning domains that have been explored, and this has led us to substantially different choices in terms of representation and algorithms. We discuss some of these differences and discuss the approach we have adopted.

Golden, Keith↗

Activity Planning for the Mars Exploration Rovers

Operating the Mars Exploration Rovers is a challenging, time-pressured task. Each day, the operations team must generate a new plan describing the rover activities for the next day. These plans must abide by resource limitations, safety rules, and temporal constraints. The objective is to achieve as much science as possible, choosing from a set of observation requests that oversubscribe rover resources. In order to accomplish this objective, given the short amount of planning time available, the MAPGEN (Mixed-initiative Activity Plan GENerator) system was made a mission-critical part of the ground operations system. MAPGEN is a mixed-initiative system that employs automated constraint-based planning, scheduling, and temporal reasoning to assist operations staff in generating the daily activity plans. This paper describes the adaptation of constraint-based planning and temporal reasoning to a mixed-initiative setting and the key technical solutions developed for the mission deployment of MAPGEN.

Bresina, John L.↗

Mixed-Initiative Planning in MAPGEN: Capabilities and Shortcomings

MAPGEN (Mixed-initiative Activity Plan GENerator) is a mixed-initiative system that employs automated constraint-based planning, scheduling, and temporal reasoning to assist the Mars Exploration Rover mission operations staff in generating the daily activity plans. This paper describes the mixed-initiative capabilities of MAPGEN, identifies shortcomings with the deployed system, and discusses ongoing work to address some of these shortcomings.

Bresina, John L.↗