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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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
NASA NTRS1977

An asymptotic analysis of a general class of signal detection algorithms

For applications to the problem of radio frequency interference identification, or in the search for extraterrestrial intelligence, it is important to have a basic understanding of signal detection algorithms. A general technique for assessing the asymptotic sensitivity of a broad class of signal detection algorithms is given. In these algorithms, the decision is based on the value of X sub 1 + X sub 2...+ X sub n where the X sub 1's are obtained by sampling and preliminary processing of a physical process.

Mceliece, R. J.↗
DOE OSTI2025

Multiple Hypothesis Tracking for Opportunistic Transmitter Identification

The exploitation of radio frequency (RF) signals from Low Earth Orbit (LEO) communication satellites for the purposes of navigation is an active field of research. In this alternative navigation system, navigation observables are passively extracted from existing RF signals. Because these signals are not designed for navigation purposes and often have proprietary signal structures that are unknown to the receiver, they lack much of the information required for navigation systems or such information is unavailable to the receiver.

42 ENGINEERING↗
NASA NTRS1977

Analysis of a discrete spectrum analyzer for the detection of radio frequency interference

As the radio frequency spectrum becomes increasingly overcrowded, interference with mission-critical DSN operations is rising at an alarming rate. To alleviate this problem the DSN is developing a wideband surveillance system for on-site detection and identification of potential sources of radio frequency interference (RFI), which will complement the existing frequency coordination activities. The RFI monitoring system is based on a wideband, multi-look discrete spectrum analyzer operating on fast Fourier transform principles. An extensive general statistical analysis is presented of such spectrum analyzers and derives threshold detection performance formulas for signals of interest. These results are then applied to the design of the RFI spectrum analyzer under development.

Levitt, B. K.↗
NASA NTRS2004

Polarimetric Scanning Radiometer C and X Band Microwave Observations During SMEX03

Soil Moisture Experiments 2003 (SMEX03) was the second in a series of field campaigns using the NOAA Polarimetric Scanning Radiometer (PSR/CX) designed to validate brightness temperature data and soil moisture retrieval algorithms for the Advanced during SMEX03 were: calibration and validation of AMSR-E brightness temperature observations over different climate/vegetation regions of the US. (Alabama, Georgia, Oklahoma), identification of possible sources of Radio Frequency Interference (RFI), comparison of X-band observations from TRMM Microwave Imager (TMI), AMSR-E and PSR/CX, and exploring the potential of soil moisture retrieval algorithms using C and X band imagery in diverse landscapes. In the current investigation, more than one hundred flightlines of PSR/CX data were extensively processed to produce gridded brightness temperature products for the four study regions. Variations associated with soil moisture were not as large as hoped for due to the lack of significant rainfall in Oklahoma. Observations obtained over Alabama include a wide range of soil moisture and vegetation conditions for C and X band frequencies. These results clearly showed a lack of sensitivity to rainfall/soil moisture under forest canopy cover. Quantitative comparisons made between the PSR/CX, AMSR-E for validated that both the PSR/CX and AMSR-E data were well calibrated. X band comparisons of the PSR/CX high resolution and AMSR-E and TMI low-resolution data indicated a linear scaling for the range of conditions studied in SMEX03. These results will form the basis for further soil moisture investigations.

Jackson, Thomas J.↗
NASA NTRS1979

The state of technology in electromagnetic (RF) sensors (for lightning detection)

A brief overview of the radio-frequency sensors which were applied to the detection, isolation, and/or identification of the transient electromagnetic energy (sferics) radiated from one or more lightning discharges in the atmosphere is presented. Radio frequency (RF) characteristics of lightning discharges, general RF sensor (antenna) characteristics, sensors and systems previously used for sferic detection, electromagnetic pulse sensors are discussed. References containing extensive bibliographies concerning lightning are presented.

Shumpert, T. H.↗
NASA NTRS1972

The light ion trough

Several fundamental characteristics of LIT (light ion trough), including evidence of diurnal variation as well as response to magnetic disturbances, are identified. These identifications were made using the Bennett radio frequency ion mass spectrometer onboard the OGO-6 from 1969 to 1970. It was shown that the LIT, rather than the total ionization trough, appears as a more meaningful indicator of the plasmapause. This makes the LIT a fundamental parameter for studies of the formation and maintenance of the plasmasphere.

Taylor, H. A., Jr.↗
NASA NTRS2011

Shuttle Communications and Tracking, Avionics, and Electromagnetic Compatibility

By definition, electromagnetic compatibility (EMC) is the capability of components, sub-systems, and systems, to operate in their intended electromagnetic environment, within an established margin of safety, and at design levels of performance. Practice of the discipline itself incorporates knowledge of various aspects of applied physics, materials science, and engineering across the board, and includes control and mitigation of undesirable electromagnetic interaction between intentional and unintentional emitters and receivers of radio frequency energy, both within and external to the vehicle; identification and control of the hazards of non-ionizing electromagnetic radiation to personnel, ordnance, and fuels and propellants; and vehicle and system protection from the direct and indirect effects of lightning and various other forms of electrostatic discharge (ESD) threats, such as triboelectrification and plasma charging. EMC is extremely complex and far-reaching, affecting in some degree every aspect of the vehicle s design and operation. The most successful efforts incorporate EMC design features and techniques throughout design and fabrication of the vehicle s structure and components, as well as appropriate operational considerations with regard to electromagnetic threats in the operational environment, from the beginning of the design effort to the end of the life cycle of the manufactured product. This approach yields the highest design performance with the lowest cost and schedule impact.

deSilva, K.↗
DOE OSTI2024

YOLO for Radio Frequency Signal Classification

Radio frequency signal classification plays a pivotal role in various applications, including spectrum management, wireless security, and cognitive radio. Extant signal classification methods require significant data throughput and are not multilabel. We propose a novel approach to radio frequency signal classification by leveraging the You Only Look Once (YOLO) object detection method. YOLO is a state-of-the-art deep learning model renowned for its real-time object detection capabilities in computer vision applications. We adapt YOLO for signal classification to enable the automatic and efficient identification of various signal types within a power spectral density image. Index Terms—radio-frequency analysis, object detection, neural networks, machine learning, deep learning.

42 ENGINEERING↗
DOE OSTI2022

Deep Learning Based Superconducting Radio-Frequency Cavity Fault Classification at Jefferson Laboratory

This work investigates the efficacy of deep learning (DL) for classifying C100 superconducting radio-frequency (SRF) cavity faults in the Continuous Electron Beam Accelerator Facility (CEBAF) at Jefferson Lab. CEBAF is a large, high-power continuous wave recirculating linac that utilizes 418 SRF cavities to accelerate electrons up to 12 GeV. Recent upgrades to CEBAF include installation of 11 new cryomodules (88 cavities) equipped with a low-level RF system that records RF time-series data from each cavity at the onset of an RF failure. Typically, subject matter experts (SME) analyze this data to determine the fault type and identify the cavity of origin. This information is subsequently utilized to identify failure trends and to implement corrective measures on the offending cavity. Manual inspection of large-scale, time-series data, generated by frequent system failures is tedious and time consuming, and thereby motivates the use of machine learning (ML) to automate the task. This study extends work on a previously developed system based on traditional ML methods (Tennant and Carpenter and Powers and Shabalina Solopova and Vidyaratne and Iftekharuddin, Phys. Rev. Accel. Beams, 2020, 23, 114601), and investigates the effectiveness of deep learning approaches. The transition to a DL model is driven by the goal of developing a system with sufficiently fast inference that it could be used to predict a fault event and take actionable information before the onset (on the order of a few hundred milliseconds). Because features are learned, rather than explicitly computed, DL offers a potential advantage over traditional ML. Specifically, two seminal DL architecture types are explored: deep recurrent neural networks (RNN) and deep convolutional neural networks (CNN). We provide a detailed analysis on the performance of individual models using an RF waveform dataset built from past operational runs of CEBAF. In particular, the performance of RNN models incorporating long short-term memory (LSTM) are analyzed along with the CNN performance. Furthermore, comparing these DL models with a state-of-the-art fault ML model shows that DL architectures obtain similar performance for cavity identification, do not perform quite as well for fault classification, but provide an advantage in inference speed.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1982

Tidbinbilla two-element interferometer

A phase-stable two-element interferometer has been formed by linking the 64- and 34-m antennas of the Deep Space Network at Tidbinbilla, Australia. Utilizing the existing first-stage maser receivers at 2.3 GHz to yield a system temperature of approximately 20 K, the system has a 5 sigma detection sensitivity of 50 mJy in 1 s, with a rms confusion of approximately 6 mJy. The 195-m north-south baseline permits positional measurements to approximately 2 arcsec of sources stronger than approximately 100 mJy over the declination range -80 to +30 deg. Such measurements are ideally suited for the optical identification of weak radio sources. It is planned to extend the frequency of operation of the instrument to 8.4 GHz in the near future.

Batty, M. J.↗
NASA NTRS1973

Observations of noise bands associated with the upper hybrid resonance by the Imp 6 radio astronomy experiment.

The intense noise bands occurring near the upper hybrid resonance frequency have been observed with the Imp 6 GSFC radio astronomy experiment in the plasmasphere. The identification of the upper hybrid resonance provides an accurate measure of the local electron density and allows the observed noise data to be fit to the scale of characteristic frequencies in the plasma. The data are consistent with earlier theoretical interpretations in which noise is generated between the upper hybrid and plasma frequencies and propagates to region 4 of the CMA diagram, where it is reflected at the L = 0 plasma cutoff.

Mosier, S. R.↗
DOE OSTI2020

Percolation and nanosecond fluctuators in V 2 O 3 films within the metal–insulator transition

Vanadium sesquioxide (V 2 O 3 ) exhibits a metal–insulator transition (MIT) at 160 K between a low temperature, monoclinic, antiferromagnetic Mott insulator and a high temperature, rhombohedral, paramagnetic, metallic phase. In thin films, a percolative transition takes place over a finite temperature range of phase coexistence. We study the fluctuating dynamics of this percolative MIT by measuring voltage noise spectra at both low frequencies (up to 100 kHz) and radio frequencies (between 10 MHz and 1 GHz). Noise intensity quadratic in bias is observed in the MIT region, as expected for resistive fluctuations probed nonperturbatively by the current. The low frequency noise resembles flicker-type 1/f β noise, often taking on the form of Lorentzian noise dominated by a small number of fluctuators as the volume fraction of the insulating phase dominates. Radio frequency noise intensity also quadratic in the bias current allows the identification of resistance fluctuations with lifetimes below 1 ns, approaching timescales seen in non-equilibrium pump–probe studies of the transition. We find quantitative consistency with a model for fluctuations in the percolative fraction. The thermodynamics of the MIT suggests that dominant fluctuations are ones that alter small volumes affecting the connectivity of domain boundaries. This noise serves as a sensitive and nonperturbative probe for the dynamics of switching phenomena in this system.

36 MATERIALS SCIENCE↗
NASA NTRS2008

DSN Scheduling Engine

The DSN (Deep Space Network) Scheduling Engine targets all space missions that use DSN services. It allows clients to issue scheduling, conflict identification, conflict resolution, and status requests in XML over a Java Message Service interface. The scheduling requests may include new requirements that represent a set of tracks to be scheduled under some constraints. This program uses a heuristic local search to schedule a variety of schedule requirements, and is being infused into the Service Scheduling Assembly, a mixed-initiative scheduling application. The engine resolves conflicting schedules of resource allocation according to a range of existing and possible requirement specifications, including optional antennas; start of track and track duration ranges; periodic tracks; locks on track start, duration, and allocated antenna; MSPA (multiple spacecraft per aperture); arraying/VLBI (very long baseline interferometry)/delta DOR (differential one-way ranging); continuous tracks; segmented tracks; gap-to-track ratio; and override or block-out of requirements. The scheduling models now include conflict identification for SOA(start of activity), BOT (beginning of track), RFI (radio frequency interference), and equipment constraints. This software will search through all possible allocations while providing a best-effort solution at any time. The engine reschedules to accommodate individual emergency tracks in 0.2 second, and emergency antenna downtime in 0.2 second. The software handles doubling of one mission's track requests over one week (to 42 total) in 2.7 seconds. Further tests will be performed in the context of actual schedules.

Clement, Bradley↗
DOE OSTI2025

Coincident learning for beam-based rf station fault identification using phase information at the SLAC linac coherent light source

Anomalies in radio-frequency (rf) stations can result in unplanned downtime and performance degradation in linear accelerators such as SLAC’s Linac Coherent Light Source (LCLS). Detecting these anomalies is challenging due to the complexity of accelerator systems, high data volume, and scarcity of labeled fault data. Prior work identified faults using beam-based detection, combining rf amplitude and beam position monitor data. Due to the simplicity of the rf amplitude data, classical methods are sufficient to identify faults, but the recall is constrained by the low-frequency and asynchronous characteristics of the data. In this work, we leverage high-frequency, time-synchronous rf phase data to enhance anomaly detection in the LCLS accelerator. Due to the complexity of phase data, classical methods fail, and we instead train deep neural networks within the Coincident Anomaly Detection (CoAD) framework. We find that applying CoAD to phase data detects nearly 3 times as many anomalies as when applied to amplitude data, while achieving broader coverage across rf stations. Furthermore, the rich structure of phase data enables us to cluster anomalies into distinct physical categories. Through the integration of auxiliary system status bits, we link clusters to specific fault signatures, providing additional granularity for uncovering the root cause of faults. We also investigate interpretability via Shapley values, confirming that the learned models focus on the most informative regions of the data and providing insight for cases where the model makes mistakes. This work demonstrates that phase-based anomaly detection for rf stations improves both diagnostic coverage and root cause analysis in accelerator systems and that deep neural networks are essential for effective analysis.

Accelerator Physics (physics.acc-ph)↗
NASA NTRS1987

Intelligent signal analysis and recognition

Progress in the research and development of self-organizing database system that can support the identification and characterization of signals in an RF environment is described. As the radio frequency spectrum becomes more crowded, there are a number of situations that require a characterization of the RF environment. This database system is designed to be practical in applications where communications and other instruments encounter a time varying and complex RF environment. The primary application of this system is the guidance and control of NASA's SETI Microwave Observing Project. Other possible applications include selection of telemety bands for communication with spacecraft, and the scheduling of antenna for radio astronomy are two examples where characterization of the RF environment is required. In these applications, the RF environment is constantly changing, and even experienced operators cannot quickly identify the multitude of signals that can be encountered. Some of these signals are repetitive, others appear to occur sporadically.

Levinson, Robert↗
NASA NTRS1995

Precise laboratory measurements of methanol rotational transition frequencies in the 5 to 13 GHz region

Rotational transitions for CH3OH were measured in the 5-13 GHz range with a precision and accuracy of a few kilohertz or less using a Flygare-Balle type pulsed-beam Fourier transform microwave spectrometer. The accurate center frequencies measured should be useful in determining accurate Doppler shifts and making positive molecule identification in radio astronomy.

Breckenridge, S. M.↗
NASA NTRS1998

Extraterrestrial organic matter: a review

We review the nature of the widespread organic material present in the Milky Way Galaxy and in the Solar System. Attention is given to the links between these environments and between primitive Solar System objects and the early Earth, indicating the preservation of organic material as an interstellar cloud collapsed to form the Solar System and as the Earth accreted such material from asteroids, comets and interplanetary dust particles. In the interstellar medium of the Milky Way Galaxy more than 100 molecular species, the bulk of them organic, have been securely identified, primarily through spectroscopy at the highest radio frequencies. There is considerable evidence for significantly heavier organic molecules, particularly polycyclic aromatics, although precise identification of individual species has not yet been obtained. The so-called diffuse interstellar bands are probably important in this context. The low temperature kinetics in interstellar clouds leads to very large isotopic fractionation, particularly for hydrogen, and this signature is present in organic components preserved in carbonaceous chondritic meteorites. Outer belt asteroids are the probable parent bodies of the carbonaceous chondrites, which may contain as much as 5% organic material, including a rich variety of amino acids, purines, pyrimidines, and other species of potential prebiotic interest. Richer in volatiles and hence less thermally processed are the comets, whose organic matter is abundant and poorly characterized. Cometary volatiles, observed after sublimation into the coma, include many species also present in the interstellar medium. There is evidence that most of the Earth's volatiles may have been supplied by a 'late' bombardment of comets and carbonaceous meteorites, scattered into the inner Solar System following the formation of the giant planets. How much in the way of intact organic molecules of potential prebiotic interest survived delivery to the Earth has become an increasingly debated topic over the last several years. The principal source for such intact organics was probably accretion of interplanetary dust particles of cometary origin.

NASA Discipline Exobiology↗