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This paper describes the development of the K/Ka-band, satellite-tracking mobile-vehicular antenna system for NASA's ACTS Mobile Terminal (AMT) project. ACTS is NASA's Advanced Communications Technology Satellite, which will be launched into its geostationary orbit in 1993.
As the Goddard Space Flight Center's (GSFC) Flight Dynamics Facility (FDF) continues to ensure mission success in support of Human Space Flight (HSF) and Launch Vehicle (LV) missions, it continues to improve on different areas of mission support. The FDF processes numerous different types of trajectory profiles, and, for each trajectory, the FDF provides multiple acquisition data vectors to the Space Network (SN) White Sands Complex (WSC) for further processing and uplinking to the SN's Tracking and Data Relay Satellites (TDRSs), tracking the vehicle and maintaining communications throughout required support. Some trajectories target a specific orbit plane through Right Ascension of the Ascending Node (RAAN), or yaw, steering, which can yield to high variability across the launch window. Because of this, there can be a large number of trajectory profiles to process and generate acquisition data for that ensure TDRS is accurately pointing to the launch vehicle. Processing many trajectory profiles by FDF and WSC increases the complexity and level of effort associated with support. FDF employs a legacy boundary on the range difference between trajectories, which determines the number of discrete trajectory cases required to maintain communication with TDRS over the full launch window. An analysis was performed to determine a new boundary, taking into consideration current support requirements. The results show the boundary can be expanded beyond the currently employed legacy value without an impact on communication. In doing so, the number of trajectory profiles processed can be reduced, reducing the complexity and level of effort required, with no impact to mission safety.
Five electric vehicles were tested at vehicle test tracks using the SAE. The tests provide range data at steady speeds and for several driving cycles. Most tests were conducted with lead-acid traction batteries. The Otis Van and the Copper Electric Town Car were also tested with lead-acid and nickel-zinc batteries. The tests showed a range increase of from 82 to 101 percent depending on vehicle, speed, and test cycle.
Early in its electric vehicle (EV) test program, JPL recognized that EV test procedures were too vague and too loosely defined to permit much meaningful data to be obtained from the testing. Therefore, JPL adopted more stringent test procedures and chose the chassis dynamometer rather than the track as its principal test technique. Through the years, test procedures continued to evolve towards a methodology based on chassis dynamometers which would exhibit good correlation with track testing. Based on comparative dynamometer and track test results on the ETV-1 vehicle, the test methods discussed in this report demonstrate a means by which excellent track-to-dynamometer correlation can be obtained.
Autonomous space rendezvous scenarios require knowledge of the target vehicle state in order to safely dock with the chaser vehicle. Ideally, the target vehicle state information is derived from telemetered data, or with the use of known tracking points on the target vehicle. However, if the target vehicle is non-cooperative and does not have the ability to maintain attitude control, or transmit attitude knowledge, the docking becomes more challenging. This work presents a nonlinear approach for estimating the body rates of a non-cooperative target vehicle, and coupling this estimation to a tracking control scheme. The approach is tested with the robotic servicing mission concept for the Hubble Space Telescope (HST). Such a mission would not only require estimates of the HST attitude and rates, but also precision control to achieve the desired rate and maintain the orientation to successfully dock with HST.
Autonomous space rendezvous scenarios require knowledge of the target vehicle state in order to safely dock with the chaser vehicle. Ideally, the target vehicle state information is derived from telemetered data, or with the use of known tracking points on the target vehicle. However, if the target vehicle is non-cooperative and does not have the ability to maintain attitude control, or transmit attitude knowledge, the docking becomes more challenging. This work presents a nonlinear approach for estimating the body rates of a non-cooperative target vehicle, and coupling this estimation to a tracking control scheme. The approach is tested with the robotic servicing mission concept for the Hubble Space Telescope (HST). Such a mission would not only require estimates of the HST attitude and rates, but also precision control to achieve the desired rate and maintain the orientation to successfully dock with HST.
After a general, overall definition of Complex 39L during the previous two years, the 1988-89 projects were chosen to focus on more specific aspects, specifically, guidance systems and propellant systems. Six teams or subtasks were formulated: cascade refrigeration for boil-off recovery of cryogenic storage vessels; lunar ground-based radar system to track space vehicles; microwave altimeter for spacecraft; development of a computational model for the determination of lunar surface and sub-surface temperatures; lunar cryogenic facility for the storage of fuels; and lunar lander fuel inventory tent for the storage of cryogenic vessels. At the present time, a cascade refrigeration system for a cryogenic boil-off recovery system has been designed. This is to serve as a baseline system. The ground-based tracking system uses existing technology to implement a reliable tracking radar for use on the lunar surface. A prototype has been constructed. The microwave altimeter is for use on lunar landers. It makes use of the Doppler effect to measure both altitude and the vertical velocity component of the spacecraft. A prototype has been constructed. A computational model that predicts the spatial and temporal temperature profiles of the lunar subsurface was formulated. Propellant storage vessels have been designed. A support for these vessels which minimizes heat leaks was also designed. Further work on the details of the Fuel Inventory Tent (FIT) was performed. While much design work on the overall Complex 39L remains to be done, significant new work has been performed in the subject areas.
Sonic boom pressure signatures recorded during the launch and reentry phases of the Apollo 15 mission are presented. The measurements were obtained along the vehicle ground track at 87 km and 970 km downrange from the launch site during ascent; and at 500 km, 55.6 km, and 12.9 km from the splashdown point during reentry. Tracings of the measured signatures are included along with values of the overpressure, impulse, time duration, and rise times. Also included are brief descriptions of the launch and recovery test areas in which the measurements were obtained, the sonic boom instrumentation deployment, flight profiles and operating conditions for the launch vehicle and spacecraft, surface weather information at the measuring sites, and high altitude weather information for the general measurement areas.
On-demand mobility - also referred to as on-demand transit (ODT) - is a form of public mobility that is flexible with respect to where and when service is provided, and ODT deployments have increased significantly in recent years. Transit agencies are becoming increasingly interested in ODT, and due to differing definitions and various service design and business model options, it can be difficult to learn about the emerging industry. This work provides an overview of the definitions of ODT, recent trends internationally and in the U.S., ODT's benefits and challenges (particularly compared to fixed-route transit), three primary service design options, system costs and funding considerations, and a metrics framework for evaluating ODT systems to ensure continued successful performance. Identified benefits include increased service areas, short ride and wait times, increased user flexibility, potential to reduce energy consumption and emissions through shared trips and smaller, right-sized vehicles, increased safety and comfort through door-to-door service, and rich data streams including granular spatio-temporal data that can be analyzed to continuously improve the service. Challenges include scaling ODT service up as small increases in ridership require additional supply to keep service quality high, serving peak times including keeping low wait times, the lack of fixed schedule being challenging for commuters, integrating ODT services with nearby transit systems, and equity for riders without smartphones who cannot track the vehicle in a mobile app. Finally, an overview of seven ODT case studies (in Texas, Missouri, New York, and Ontario, Canada) performed by NREL and related analysis of travel time, energy and emissions, costs, and equity are presented. Initial key findings include: ODT can be cost- and energy-effective compared to fixed-route transit, ODT serves more people than other transit options, and ODT system deployments can be followed by rapid growth.
Sonic-boom pressure signatures recorded during the launch and reentry phases of the Apollo 16 mission are presented. Five measurements were obtained along the vehicle ground track: 69 km (37.3 n. mi.) 92 km (49.8 n. mi.), and 130 km (70.3 n. mi.) down range from the launch site during ascent, and at 185 km (100 n. mi.) and approximately 5.5 km (3 n. mi.) from the splash-down point during reentry. Tracings of the measured signatures are included along with values of the overpressure, impulse, time duration, and rise times. Also included are brief descriptions of the launch and recovery test areas in which the measurements were obtained, the sonic-boom instrumentation deployment, flight profiles, and operating conditions for the launch vehicle and spacecraft, surface weather information at the measuring sites, and high-altitude weather information for the general measurement areas. Comparisons of the sonic-boom overpressures from Apollo 15 and 16 along with those from current aircraft are also presented.
The emergence of Advance Air Mobility (AAM) will increase the number and types of aerial vehicles operating in shared airspaces, which will subsequently affect the amount of actionable data that ground control station operators (GCSOs) will be expected to manage. In this environment, GCSOs are particularly susceptible to the visual perceptual phenomenon known as change blindness, in which a stimulus undergoes a change without the change being noticed by its observer. A machine agent designed to detect change blindness and mitigate the effects could improve human agent performance in a data-saturated remote operations environment. The objective of this paper is to describe a proof-of-concept system architecture that integrates real-time eye tracking and vehicle telemetry data to prevent human-agent errors resulting from change blindness while operating aircraft from a remote ground control station (GCS).
The emergence of Advance Air Mobility (AAM) will increase the number and types of aerial vehicles operating in shared airspaces, which will subsequently affect the amount of actionable data that ground control station operators (GCSOs) will be expected to manage. In this environment, GCSOs are particularly susceptible to the visual perceptual phenomenon known as change blindness, in which a stimulus undergoes a change without the change being noticed by its observer. A machine agent designed to detect change blindness and mitigate the effects could improve human agent performance in a data-saturated remote operations environment. The objective of this paper is to describe a proof-of-concept system architecture that integrates real-time eye tracking and vehicle telemetry data to prevent human-agent errors resulting from change blindness while operating aircraft from a remote ground control station (GCS).
The Raven ISS Hosted Payload will feature several pose measurement sensors on a pan/tilt gimbal which will be used to autonomously track resupply vehicles as they approach and depart the International Space Station. This paper discusses the derivation of a Relative Navigation Filter (RNF) to fuse measurements from the different pose measurement sensors to produce relative position and attitude estimates. The RNF relies on relative translation and orientation kinematics and careful pose sensor modeling to eliminate dependence on orbital position information and associated orbital dynamics models. The filter state is augmented with sensor biases to provide a mechanism for the filter to estimate and mitigate the offset between the measurements from different pose sensors.
The Raven ISS Hosted Payload will feature several pose measurement sensors on a pan/tilt gimbal which will be used to autonomously track resupply vehicles as they approach and depart the International Space Station. This paper discusses the derivation of a Relative Navigation Filter (RNF) to fuse measurements from the different pose measurement sensors to produce relative position and attitude estimates. The RNF relies on relative translation and orientation kinematics and careful pose sensor modeling to eliminate dependence on orbital position information and associated orbital dynamics models. The filter state is augmented with sensor biases to provide a mechanism for the filter to estimate and mitigate the offset between the measurements from different pose sensors
Here we demonstrate a contextually aware multimodal roadside radiation measurement detection testbed for traffic monitoring applications in nuclear nonproliferation. Many variables in traffic such as vehicle or cargo size, mass, speed, shape, and distance of closest approach can have significant impacts on the radiation measured from a vehicle-transported radiation source. These factors can lead to uncertainties in the analysis of the radiation source, especially for lower-strength radiation sources of interest. Our testbed, known as the Multimodal Measurement System (MMS) uses non-radiation sensors including magnetometers, geophones, radiofrequency receivers, cameras, and LiDAR to extract contextual information about vehicles passing by the system. These contextual data can then be fused with data from radiation measurements to increase the system’s sensitivity and accuracy in nuclear threat detection applications. This work describes the instrumentation of the MMS and its data acquisition pipeline. Furthermore, we describe the pre-analysis performed on the raw multimodal data streams for data fusion, and the high-level machine learning analyses for detection and characterization. The variety of sensors within the MMS provides a valuable testbed that can be used to identify the combinations of contextual sensors that provide the greatest improvements to radiation source detection and characterization within the restrictions for various proliferation detection applications. The MMS is also modular so that additional combinations of sensors can be explored in the future.
Automatic phase-control circuit, used on space vehicles, for tracking narrowband signals coherently in high-noise environment
This paper presents representative results of sonic-boom overpressure data recorded during the launch and reentry of the Apollo 15 and 16 space vehicle systems. Comparisons are made between measured overpressures and those predicted using available theory. The measurements were obtained along the vehicle ground track at 68, 87, 92, 129, and 970 km downrange from the launch site during ascent, and at 9, 13, 55, 185, and 500 km from the splash-down point during reentry. Also included are tracings of the sonic-boom signatures along with a brief description of the launch and recovery test areas in which the measurements were obtained, the sonic-boom instrumentation deployment, flight profiles and operating conditions, and high-altitude weather information for the general measurement areas.
The joint German and NASA project Helios is reviewed with special attention paid to the advanced technology required to accomplish the mission, i.e., thermal (second surface mirrors), telecommunications (despun high gain antenna) and power (high temperature solar cells). Engineering and system results are presented for the Mar. 15, 1975 perihelion passage of Helios A to within 0.31 AU of the sun. Also discussed are mission design, the experiment performance, spacecraft configurations, the launch vehicle, and tracking and data acquisition. Tables are included describing the history of German-U.S. cooperation, prelaunch milestones and significant mission events, experiments performance during primary mission and mission dependent requirements, development problems and solutions.