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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 361 records · Page 20
All sourcesNASA NTRSDOE OSTI
NASA NTRS1984

Effects of CW interference on the carrier tracking loop of the deep space network

A radio-frequency interference (RFI) environment can cause serious problems for communications systems, such as the Deep Space Network (DSN). For this reason, it is necessary to determine first the RFI susceptibility characteristics for DSN receiving systgms. The present investigation is concerned with CW RFI's which are close in frequency to the carrier frequency. The carrier tracking loop is highly sensitive, and this type of RFI will degrade the carrier loop performance before saturation effects become noticeable. The investigation has the objective to develop an analytical model which will make it possible to predict the tracking performance of the Block IV receiver when operated in the presence of a CW RFI in the receiver passband. The Block IV receiver represents one of the DSN receivers. Attention is given to the effects of a CW RFI on a phase-locked loop, the effects of a bandpass limiter, numerical results, experimental verification, and aspects of computer simulation.

Sue, M. K.↗
NASA NTRS2004

Amplitude Scintillation due to Atmospheric Turbulence for the Deep Space Network Ka-Band Downlink

Fast amplitude variations due to atmospheric scintillation are the main concerns for the Deep Space Network (DSN) Ka-band downlink under clear weather conditions. A theoretical study of the amplitude scintillation variances for a finite aperture antenna is presented. Amplitude variances for weak scattering scenarios are examined using turbulence theory to describe atmospheric irregularities. We first apply the Kolmogorov turbulent spectrum to a point receiver for three different turbulent profile models, especially for an exponential model varying with altitude. These analytic solutions then are extended to a receiver with a finite aperture antenna for the three profile models. Smoothing effects of antenna aperture are expressed by gain factors. A group of scaling factor relations is derived to show the dependences of amplitude variances on signal wavelength, antenna size, and elevation angle. Finally, we use these analytic solutions to estimate the scintillation intensity for a DSN Goldstone 34-m receiving station. We find that the (rms) amplitude fluctuation is 0.13 dB at 20-deg elevation angle for an exponential model, while the fluctuation is 0.05 dB at 90 deg. These results will aid us in telecommunication system design and signal-fading prediction. They also provide a theoretical basis for further comparison with other measurements at Ka-band.

Ho, C.↗
NASA NTRS2000

Deep Space Network turbo decoder implementation

A new decoder is being developed by the Jet Propulsion Laboratory for NASA's Deep Space Network. This unit will decode the new turbo codes, which have recently been approved by the Consultative Committee for Space Data Systems (CCSDS).

turbo decoder turbo code↗
NASA NTRS2013

Analysis of Near-field of Circular Aperture Antennas with Application to Study of High Intensity Radio Frequency (HIRF) Hazards to Aviation from JPL/NASA Deep Space Network Antennas

This work includes a simplified analysis of the radiated near to mid-field from JPL/NASA Deep Space Network (DSN) reflector antennas and uses an averaging technique over the main beam region and beyond for complying with FAA regulations in specific aviation environments. The work identifies areas that require special attention, including the implications of the very narrow beam of the DSN transmitters. The paper derives the maximum averaged power densities allowed and identifies zones where mitigation measures are required.

Antennas↗
DOE OSTI2021

Identifying Genomic Islands with Deep Neural Networks

Background Horizontal gene transfer is the main source of adaptability for bacteria, through which genes are obtained from different sources including bacteria, archaea, viruses, and eukaryotes. This process promotes the rapid spread of genetic information across lineages, typically in the form of clusters of genes referred to as genomic islands (GIs). Different types of GIs exist, and are often classified by the content of their cargo genes or their means of integration and mobility. While various computational methods have been devised to detect different types of GIs, no single method is capable of detecting all types. Results We propose a method, which we call Shutter Island, that uses a deep learning model (Inception V3, widely used in computer vision) to detect genomic islands. The intrinsic value of deep learning methods lies in their ability to generalize. Via a technique called transfer learning, the model is pre-trained on a large generic dataset and then re-trained on images that we generate to represent genomic fragments. We demonstrate that this image-based approach generalizes better than the existing tools. Conclusions We used a deep neural network and an image-based approach to detect the most out of the correct GI predictions made by other tools, in addition to making novel GI predictions. The fact that the deep neural network was re-trained on only a limited number of GI datasets and then successfully generalized indicates that this approach could be applied to other problems in the field where data is still lacking or hard to curate.

Computer Vision↗
NASA NTRS2006

Changes in the Deep Space Network to Support the Mars Reconnaissance Orbiter

In August of 2005, the Mars Reconnaissance Orbiter (MRO) was launched. Its mission is to orbit Mars, performing remote sensing of the planet. Its mission will either introduce new, or greatly expand upon, deep space telecommunication capabilities. To support the MRO requirements, there have been multiple changes implemented in NASA's Deep Space Network. These changes include the first deep space usage of Quadrature Phase Shift Keying (QPSK), high rate turbo coded links (up to 1.6 Mbps), high rate Reed-Solomon coded links (6 Mbps), and characterization and utilization of Ka-band for the downlink, both for telemetry and for navigational purposes. The challenges of implementing these changes are discussed.

Quadrature Phase Shift Keying (QPSK)↗
NASA NTRS1994

(abstract) Deep Space Network Radiometric Remote Sensing Program

Planetary spacecraft are viewed through a troposphere that absorbs and delays radio signals propagating through it. Tropospheric water, in the form of vapor, cloud liquid,and precipitation , emits radio noise which limits satellite telemetry communication link performance. Even at X-band, rain storms have severely affected several satellite experiments including a planetary encounter. The problem will worsen with DSN implementation of Ka-band becausecommunication link budgets will be dominated by tropospheric conditions. Troposphere-induced propagation delays currently limit VLBI accuracy and are significant sources of error for Doppler tracking. Additionally, the success of radio science programs such as satellite gravity wave experiments and atmospheric occultation experiments depends on minimizing the effect of watervapor-induced prop agation delays. In order to overcome limitations imposed by the troposphere, the Deep Space Network has supported a program of radiometric remote sensing. Currently, water vapor radiometers (WVRs) and microwave temperature profilers (MTPs) support many aspects of the Deep Space Network operations and research and development programs. Their capability to sense atmospheric water, microwave sky brightness, and atmospheric temperature is critical to development of Ka-band telemetry systems, communication link models, VLBI, satellite gravity waveexperiments, and r adio science missions. During 1993, WVRs provided data for propagation mode development, supp orted planetary missions, and demonstrated advanced tracking capability. Collection of atmospheric statistics is necessary to model and predict performance of Ka-band telemetry links, antenna arrays, and radio science experiments. Since the spectrum of weather variations has power at very long time scales, atmospheric measurements have been requested for periods ranging from one year to a decade at each DSN site. The resulting database would provide reliable statistics on daily, monthly, and seasonal variations. Only long-term monitoring will prevent biases from being introduced by an exceptionally wet or dry year. Support for planetary missions included tropospheric calibration for the recent Mars Observer gravity wave experiments and Ka-band link experiment (KaBLE). Additionally, several proposed radio science experiments such as profiling planetary atmospheres using satellite occultations and Ka-band gravitational wave searches require advanced radiometer technology development. Finally, there has been a consistent advanced technology program to advance satellite navigational and tracking capabilities. This year that included an experiment with radiometer based tropospheric calibration for a series of VLBI catalog measurements.

microwave propagation Ka-band weather variations r↗
NASA NTRS1994

Deep Space Network Radiometric Remote Sensing Program

Planetary spacecraft are viewed through a troposphere that absorbs and delays radio signals propagating through it. Tropospheric water, in the form of vapor, cloud liquid, and precipitation, emits radio noise which limits satellite telemetry communication link performance. Even at X-band, rain storms have severely affected several satellite experiments including a planetary encounter. The problem will worsen with DSN implementation of Ka-band because communication link budgets will be dominated by tropospheric conditions. Troposphere-induced propagation delays currently limit VLBI accuracy and are significant sources of error for Doppler tracking. Additionally, the success of radio science programs such as satellite gravity wave experiments and atmospheric occultation experiments depends on minimizing the effect of water vapor-induced propagation delays. In order to overcome limitations imposed by the troposphere, the Deep Space Network has supported a program of radiometric remote sensing. Currently, water vapor radiometers (WVRs) and microwave temperature profilers (MTPs) support many aspects of the Deep Space Network operations and research and development programs. Their capability to sense atmospheric water, microwave sky brightness, and atmospheric temperature is critical to development of Ka-band telemetry systems, communication link models, VLBI, satellite gravity wave experiments, and radio science missions. During 1993, WVRs provided data for propagation model development, supported planetary missions, and demonstrated advanced tracking capability. Collection of atmospheric statistics is necessary to model and predict performance of Ka-band telemetry links, antenna arrays, and radio science experiments. Since the spectrum of weather variations has power at very long time scales, atmospheric measurements have been requested for periods ranging from one year to a decade at each DSN site. The resulting database would provide reliable statistics on daily, monthly, and seasonal variations. Only long-term monitoring will prevent biases from being introduced by an exceptionally wet or dry year. Support for planetary missions included tropospheric calibration for the recent Mars Observer gravity wave experiments and Ka-band link experiment (KaBLE). Additionally, several proposed radio science experiments such as profiling planetary atmospheres using satellite occultations and Ka-band gravitational wave searches require advanced radiometer technology development. Finally, there has been a consistent advanced technology program to advance satellite navigational and tracking capabilities. This year that included an experiment with radiometer based tropospheric calibration for a series of VLBI catalog measurements.

tropospheric calibration atmospheric water radio s↗
NASA NTRS1992

Deep Space Network Antennas

Explore the source record for details and available documents.

antenna deep space network dsn telemetry planetary↗
DOE OSTI2020

Physics-Informed Deep Neural Networks for Learning Parameters and Constitutive Relationships in Subsurface Flow Problems

In this paper, we present a physics informed deep neural network (DNN) method for estimating parameters and unknown physics (constitutive relationships) in partial differential equation (PDE) models. We use PDEs in addition to measurements to train DNNs to approximate unknown parameters and constitutive relationships as well as states. The proposed approach increases the accuracy of DNN approximations of partially known functions when a limited number of measurements is available and allows for training DNNs when no direct measurements of the functions of interest are available. We employ physics informed DNNs to estimate the unknown space-dependent diffusion coefficient in a linear diffusion equation and an unknown constitutive relationship in a non-linear diffusion equation. For the parameter estimation problem, we assume that partial measurements of the coefficient and states are available and demonstrate that under these conditions, the proposed method is more accurate than state-of-the-art methods. For the non-linear diffusion PDE model with a fully unknown constitutive relationship (i.e., no measurements of constitutive relationship are available), the physics informed DNN method can accurately estimate the non-linear constitutive relationship based on state measurements only. Finally, we demonstrate that the proposed method remains accurate in the presence of measurement noise.

42 ENGINEERING↗
NASA NTRS1980

The Deep Space Network capabilities for radio interferometry

The very long baseline interferometry capability as well as the planned capability of the deep space network (DSN) are described. Major emphasis is placed on the following: VLBI development; operational VLBI for DSN calibration; and VLBI for spacecraft navigation.

Fanselow, J. L.↗
NASA NTRS1987

Proposed upgrade of the Deep Space Network research and development station

Continued exploration of the solar system will require continued evolution of capabilities to support deep space communication and navigation. That evolution will rely, as it has in the past, on the development, demonstration, and field testing of communication and navigation technologies. The existing Deep Space Network (DSN) research and development station, DSS 13, at the Venus site, Goldstone, California was instrumental in those prior developments. However, the present antenna is no longer able to provide the necessary support for technology. The 26 meter antenna has good performance at S-band, fair performance at X-band, but is unusable at the anticipated Ka-band. It is not suitable for conversion to beam waveguides, and is not usable as a test bed for demonstrating high efficiency because of structural pliancy. Additionally, its size and age are increasingly a liability in demonstrations. A 34 meter beam waveguide version of the existing DSN high efficiency (HEF) antennas was proposed for FY-88 Construction of Facilities budget. The antenna is to be built at the Venus site, adjacent to the old antenna, and serve as the DSN research and development antenna through the end of the century.

Smith, Joel G.↗
NASA NTRS1992

An OSI Architecture for the Deep Space Network

The flexibility and robustness of a monitor and control system are a direct result of the underlying inter-processor communications architecture. A new architecture for monitor & control at the Deep Space Network Communications Complexes has been developed based on the Open System Interconnection (OSI) standards. The suitability of OSI standards for DSN M&C has been proven in the laboratory. The laboratory success has resulted in choosing an OSI-based architecture for DSS-13 M&C. DSS-13 is the DSN experimental station and is not part of the "operational" DSN; it's role is to provide an environment to test new communications concepts can be tested and conduct unique science experiments. Therefore, DSS-13 must be robust enough to support operational activities, while also being flexible enough to enable experimentation. This paper describes the M&C architecture developed for DSS-13 and the results from system and operational testing.

OSI↗
NASA NTRS1979

The deep space network

Progress is reported in flight project support, tracking and data acquisition research and technology, network engineering, hardware and software implementation, and operations. The functions and facilities of the Deep Space Network are emphasized.

Source record↗
NASA NTRS1982

NASA Deep Space Network performance analysis

As part of the Control Center Operations, the Performance Analysis Group has responsibility for validating all committed Deep Space Network support to the various user projects. The group provides the Network with the analysis support necessary to assure that actual Network performance meets or exceeds committed levels throughout the mission. Validation is carried out as the signals are received in real time by monitoring the data streams and comparing the data quality against predicted values and established performance standards and tolerance limits. An important function is to generate the predictions used to point the antennas, acquire the radio frequency, and validate the monitored Network performance. Another function is anomaly investigation. An integral part of validation is the support task of generating and maintaining performance standards and tolerance limits for each flight project. The Performance Analysis Group is broadly divided into two subgroups: real-time personnel and nonreal-time personnel.

Bartok, C. D.↗
NASA NTRS2002

Media Calibration in the Deep Space Network: A Status Report

A new media calibration system (MCS) has been implemented at the Goldstone complex of the DSN (Deep Space Network). It is intended to calibrate the delay of radio signals imposed by the neutral atmosphere. The system provides periodic measurements of both the static dry and fluctuating wet components of this delay. In particular, the system will calibrate the fluctuations in line of sight path delay due to atmospheric water vapor that we believe will dominate the error budget for several radio science and radio astronomy experiments. We have compared two of these media calibration systems with a connected element interferometer on a 21 km baseline. In this report we describe a total of 30 observations in which a radio source was tracked for an hour or more and the delay residuals then calibrated using the MCS. The accuracy of the comparison appears to be limited by systematic errors in the interferometer, which are under investigation. However, our results do indicate that the MCS can meet or exceed the two-way Allan standard deviation specification of 1.5 x 10( exp -15) on time scales of 2,000 - 10,000 sec, as required by the Cassini GWE (Gravitational Wave Experiment) for two way Doppler tracking.

Naudet, Charles J.↗
NASA NTRS2009

A Deep Space Network Portable Radio Science Receiver

The Radio Science Receiver (RSR) is an open-loop receiver installed in NASA s Deep Space Network (DSN), which digitally filters and records intermediate-frequency (IF) analog signals. The RSR is an important tool for the Cassini Project, which uses it to measure perturbations of the radio-frequency wave as it travels between the spacecraft and the ground stations, allowing highly detailed study of the composition of the rings, atmosphere, and surface of Saturn and its satellites.

Jongeling, Andre P.↗