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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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NASA NTRS1985

Massively parallel processor

A brief description is given of the Massively Parallel Processor (MPP). Major applications of the MPP are in the area of image processing (where the operands are often very small integers) from very high spatial resolution passive image sensors, signal processing of radar data, and numerical modeling simulations of climate. The system can be programmed in assembly language or a high level language. Information on background, status, architecture, programming, hardware reliability, applications, and the MPP's development as a national resource for parallel algorithm research are presented in outline form.

Source record↗

NASA NTRS1992

Time-frequency representation of a highly nonstationary signal via the modified Wigner distribution

A new signal analysis technique called the modified Wigner distribution (MWD) is presented. The new signal processing tool has been very successful in determining time frequency representations of highly non-stationary multicomponent signals in both simulations and trials involving actual Space Shuttle Main Engine (SSME) high frequency data. The MWD departs from the classic Wigner distribution (WD) in that it effectively eliminates the cross coupling among positive frequency components in a multiple component signal. This attribute of the MWD, which prevents the generation of 'phantom' spectral peaks, will undoubtedly increase the utility of the WD for real world signal analysis applications which more often than not involve multicomponent signals.

Zoladz, T. F.↗

NASA NTRS1993

Massively parallel neurocomputing for aerospace applications

An innovative hybrid, analog-digital charge-domain technology, for the massively parallel VLSI implementation of certain large scale matrix-vector operations, has recently been introduced. It employs arrays of Charge Coupled/Charge Injection Device cells holding an analog matrix of charge, which process digital vectors in parallel by means of binary, non-destructive charge transfer operations. The impact of this technology on massively parallel processing is discussed. Fundamentally new classes of algorithms, specifically designed for this emerging technology, as applied to signal processing, are derived.

Fijany, Amir↗

NASA NTRS1995

Emergency vehicle alert system (EVAS)

The Emergency Vehicle Alert System (EVAS) program is sponsored by the NASA/MSFC Technology Utilization (TU) office. The program was conceived to support the needs of hearing impaired drivers. The objective of the program is to develop a low-cost, small device which can be located in a personal vehicle and warn the driver, via a visual means, of the approach of an emergency vehicle. Many different technologies might be developed for this purpose and each has its own advantages and drawbacks. The requirements for an acoustic detection system, appear to be pretty stringent and may not allow the development of a reliable, low-cost device in the near future. The problems include variations in the sirens between various types of emergency vehicles, distortions due to wind and surrounding objects, competing background noise, sophisticated signal processing requirements, and omni-directional coverage requirements. Another approach is to use a Radio Frequency (RF) signal between the Emergency Vehicle (EV) and the Personal Vehicle (PV). This approach requires a transmitter on each EV and a receiver in each PV, however it is virtually assured that a system can be developed which works. With this approach, the real technology issue is how to make a system work as inexpensively as possible. This report gives a brief summary of the EVAS program from its inception and concentrates on describing the activities that occurred during Phase 4. References 1-3 describe activities under Phases 1-3. In the fourth phase of the program, the major effort to be expended was in development of the microcontroller system for the PV, refinement of some system elements and packaging for demonstration purposes. An EVAS system was developed and demonstrated which used standard spread spectrum modems with minor modifications.

Reed, Bill↗

NASA NTRS1996

Cardiac Monitor

Under contract to Johnson Space Center, the University of Minnesota developed the concept of impedance cardiography as an alternative to thermodilution to access astronaut heart function in flight. NASA then contracted Space Labs, Inc. to construct miniature space units based on this technology. Several companies then launched their own impedance cardiography, including Renaissance Technologies, which manufactures the IQ System. The IQ System is 5 to 17 times cheaper than thermodilution, and features the signal processing technology called TFD (Time Frequency Distribution). TFD provides three- dimensional distribution of the blood circulation force signals, allowing visualization of changes in power, frequency and time.

Source record↗

NASA NTRS2022

Mars 2020 Entry, Descent, and Landing as Observed by Radio Science Techniques at UHF and X-band Frequencies

On February 18, 2021, NASA’s Mars 2020 Rover “Perseverance” conducted the Entry, Descent, and Landing (EDL) sequence to land safely on the surface of Mars at Jezero Crater. Due to the criticality of the EDL sequence, redundant telecommunications strategies were utilized to observe the event. The rover transmitted an X-band (8.4 GHz) signal encoded with Multiple Frequency Shift Keying tones direct-to-Earth and a UHF (401.5 MHz) signal with 8 kbps encoded telemetry to orbiters, which relayed the signal back to Earth at X-band. NASA’s Deep Space Network complexes at Goldstone, California and Madrid, Spain received the direct-to-Earth X-band signal. Two of the largest steerable radio telescopes in the world, the 100-meter Green Bank Telescope in West Virginia and the Effelsberg 100-meter Radio Telescope in Germany also received the UHF carrier signal on Earth. During the EDL event, full spectrum recordings of the UHF and X-band signals were captured at these observatories using open-loop receivers. Real-time and post-processing signal analysis to determine power level, received frequency, and Doppler shift allowed determination of the spacecraft’s health and safety state during critical sequences, including event detection such as atmospheric entry, plasma blackouts, and parachute deployment. Simultaneous observations of the UHF and X-band radio links allow for redundancy in the event of a fault and greatly improve confidence in Doppler event detection.

Gladden, Roy↗

NASA NTRS1989

Systolic VLSI array for implementing the Kalman filter algorithm

A method and apparatus for processing signals representative of a complex matrix/vector equation. More particularly, signals representing an orderly sequence of the combined matrix and vector equation, known as a Kalman filter algorithm, are processed in real time in accordance with the principles of this invention. The Kalman filter algorithm is rearranged into a Faddeeva algorithm, which is a matrix-only algorithm that is modified to represent both the matrix and vector portions of the Kalman filter algorithm. The modified Faddeeva algorithm is embodied into electrical signals which are applied as inputs to a systolic array processor. The processor performs triangulation and nullification on the input signals, and delivers an output signal which is a real-time solution to the input signals.

Jaw J Chang↗

NASA NTRS1972

A Theory for the Function of the Spermaceti Organ of the Sperm Whale (Physeter Catodon L.)

The function of the spermaceti organ of the sperm whale is studied using a model of its acoustic system. Suggested functions of the system include: (1) action as an acoustic resonating and sound focussing chamber to form and process burst-pulsed clicks; (2) use of nasal passages in forehead for repeated recycling of air for phonation during dives and to provide mirrors for sound reflection and signal processing; and (3) use of the entire system to allow sound signal production especially useful for long range echolocofion in the deep sea.

Norris, K. S.↗

NASA NTRS2015

Data Processing And Machine Learning Methods For Multi-Modal Operator State Classification Systems

This document is intended as an introduction to a set of common signal processing learning methods that may be used in the software portion of a functional crew state monitoring system. This includes overviews of both the theory of the methods involved, as well as examples of implementation. Practical considerations are discussed for implementing modular, flexible, and scalable processing and classification software for a multi-modal, multi-channel monitoring system. Example source code is also given for all of the discussed processing and classification methods.

Machine learning↗

NASA NTRS1965

Audio problems in space.

Audio signal processing techniques in future space exploration, discussing channel capacity, speech processing, bandwidth narrowing, etc

SPACE EXPLORATION↗

NASA NTRS1978

Photoacoustic spectroscopy of condensed matter

Photoacoustic spectroscopy is a new analytical tool that provides a simple nondestructive technique for obtaining information about the electronic absorption spectrum of samples such as powders, semisolids, gels, and liquids. It can also be applied to samples which cannot be examined by conventional optical methods. Numerous applications of this technique in the field of inorganic and organic semiconductors, biology, and catalysis have been described. Among the advantages of photoacoustic spectroscopy, the signal is almost insensitive to light scattering by the sample and information can be obtained about nonradiative deactivation processes. Signal saturation, which can modify the intensity of individual absorption bands in special cases, is a drawback of the method.

Somoano, R. B.↗

NASA NTRS1979

A decision-directed network for dual-polarization crosstalk cancellation

Frequency reuse in the specific form of dual-polarized microwave communication systems has grown in importance in recent years as a practical means of radio spectrum conservation. Ideally the capacity of a given frequency allocation can be doubled through dual-polarization. However, hardware imperfections and propagation effects, particularly rain depolarization, prevent the achievement of this doubling without severe system performance degradation. A decision-directed cross-polarization correction network is presented whose operation depends on only simple base-band signal processing. No pilot tones or frequency offsets are required. The loop can work with any two-dimensional signal set for digital data transmission. The loop has been experimentally verified and provides a means of doubling the data capacity with little performance degradation.

Weber, W. J., III↗

NASA NTRS1988

Controlling basins of attraction in a neural network-based telemetry monitor

The size of the basins of attraction around fixed points in recurrent neural nets (NNs) can be modified by a training process. Controlling these attractive regions by presenting training data with various amount of noise added to the prototype signal vectors is discussed. Application of this technique to signal processing results in a classification system whose sensitivity can be controlled. This new technique is applied to the classification of temporal sequences in telemetry data.

Bell, Benjamin↗

NASA NTRS1993

Attenuation of empennage buffet response through active control of damping using piezoelectric material

Dynamic response and damping data obtained from buffet studies conducted in a low-speed wind tunnel by using a simple, rigid model attached to spring supports are presented. The two parallel leaf spring supports provided a means for the model to respond in a vertical translation mode, thus simulating response in an elastic first bending mode. Wake-induced buffeting flow was created by placing an airfoil upstream of the model of that the wake of the airfoil impinged on the model. Model response was sensed by a strain gage mounted on one of the springs. The output signal from the strain gage was fed back through a control law implemented on a desktop computer. The processed signals were used to 'actuate' a piezoelectric bending actuator bonded to the other spring in such a way as to add damping as the model responded. The results of this 'proof-of-concept' study show that the piezoelectric actuator was effective in attenuating the wake-induced buffet response over the range of parameters investigated.

Heeg, Jennifer↗

NASA NTRS1997

The Algorithm for MODIS Wavelength On-Orbit Calibration using the SRCA

The Spectro-Radiometric Calibration Assembly (SRCA) provides on-orbit spectral calibration of the MODerate resolution Imaging Spectroradiometer (MODIS) reflected solar bands and this paper describes how it is accomplished. The SRCA has two adjacent exit slits: 1) Main slit and 2) Calibration slit. The output from the main slit is measured by a reference silicon photo-diode (SIPD) and then passes through the MODIS. The output from the calibration slit passes through a piece of didymium transmission glass and then it is measured by a calibration SIPD. The centroids of the sharp spectral peaks of a didyrnium glass are utilized as wavelength standards. After normalization using the reference SIPD signal to eliminate the effects of the illuminating source spectra, the calibration SIPD establishes the relationship between the peaks of the didymium spectra and the grating angle; this is accomplished through the grating equation. In the grating equation the monochromator parameters, beta (half angle between the incident and diffractive beams) and theta(sub ff) (offset angle of the grating motor) are determined by matching, in a least square sense, the known centroid wavelengths of the didymium peaks and the calculated centroid grating angles from the calibration SIPD signals for the peaks. A displacement between the calibration SIPD and the reference SIPD complicates the signal processing. The response of the MODIS bands to the SRCA output is also normalized by the reference SIPD signal to eliminate the effect of the source spectrum. That response differs from what is measured by MODIS using the Spectral Measurements Assembly (SpMA), a laboratory double-monochromator, due to the wider slit width of the SRCA. The SRCA slit function, calculated using measurements by the SPMA and the SRCA at the same MODIS temperature, will be used to recover the MODIS spectral response using the SRCA data measured on-orbit.

Montgomery, Harry↗

NASA NTRS2003

Investigations of Relatively Easy To Construct Antennas With Efficiency in Receiving Schumann Resonances: Preparations for a Miniaturized Reconfigurable ELF Receiver

Relatively little is known about the cavity between the Earth and the ionosphere, which opens opportunities for technological advances and unique ideas. One effective means to study this cavity is with extremely low frequency (ELF) antennas. Possible applications of these antennas are global weather prediction, earthquake prediction, planetary exploration, communication, wireless transmission of power, or even a free energy source. The superconducting quantum interference device SQUID) and the coil antenna are the two most acceptable receivers discovered for picking up ELF magnetic fields. Both antennas have the potential for size reduction, allowing them to be portable enough for access to space and even for personal ware. With improvements of these antennas and signal processing, insightful analysis of Schumann resonance (SR) can give the science community a band of radio frequency (RF) signals for improving life here on Earth and exploring beyond.

Farmer, Brian W.↗

NASA NTRS2005

A Review of Diagnostic Techniques for ISHM Applications

System diagnosis is an integral part of any Integrated System Health Management application. Diagnostic applications make use of system information from the design phase, such as safety and mission assurance analysis, failure modes and effects analysis, hazards analysis, functional models, fault propagation models, and testability analysis. In modern process control and equipment monitoring systems, topological and analytic , models of the nominal system, derived from design documents, are also employed for fault isolation and identification. Depending on the complexity of the monitored signals from the physical system, diagnostic applications may involve straightforward trending and feature extraction techniques to retrieve the parameters of importance from the sensor streams. They also may involve very complex analysis routines, such as signal processing, learning or classification methods to derive the parameters of importance to diagnosis. The process that is used to diagnose anomalous conditions from monitored system signals varies widely across the different approaches to system diagnosis. Rule-based expert systems, case-based reasoning systems, model-based reasoning systems, learning systems, and probabilistic reasoning systems are examples of the many diverse approaches ta diagnostic reasoning. Many engineering disciplines have specific approaches to modeling, monitoring and diagnosing anomalous conditions. Therefore, there is no "one-size-fits-all" approach to building diagnostic and health monitoring capabilities for a system. For instance, the conventional approaches to diagnosing failures in rotorcraft applications are very different from those used in communications systems. Further, online and offline automated diagnostic applications are integrated into an operations framework with flight crews, flight controllers and maintenance teams. While the emphasis of this paper is automation of health management functions, striking the correct balance between automated and human-performed tasks is a vital concern.

Patterson-Hine, Ann↗

DOE OSTI2025

Improving the Transportability of a Deep Learning Denoising Model Using Transfer Learning Techniques

The adoption of machine learning techniques in the seismology community has led to great performance improvements in several areas, including signal processing. Specifically, the development of deep learning–based seismic waveform denoising models has the potential to yield improvements in signal detection capabilities for networks operating in particularly noisy environments. Recent advancements in the design of these deep learning denoising models have included the incorporation of continuous and discrete wavelet transform functions into the network architecture to improve the learning capabilities and efficiency of said models. These wavelet transform–based seismic denoising models have shown improved denoising capabilities in regions where there is good agreement between the data features present in the training and evaluation datasets. However, questions remain about the overall transportability of these models to other monitoring regions. Here, in this study, we will determine the baseline transportability of a newly developed multilevel wavelet‐transform convolutional neural network (MWCNN) seismic denoising model. We accomplish this by taking a version of the MWCNN denoising model trained on data collected from the Utah region and evaluating its denoising performance on datasets collected from the neighboring Nevada region, which differ with regard to monitoring sensor types and event histories. We find that there is a notable variability in denoising performance related to the degree of similarity between the initial and new target datasets. The most notable difference in denoising performance is the ability of the denoising model to preserve accurate amplitude information associated with the signal energy present in the waveform data. Finally, we evaluate the ability of transfer learning techniques to improve the transportability of the MWCNN denoising model. We find that although there is still a performance gap present in the denoising results of the MWCNN model, transfer learning did yield improved results.

Quinones, Louis [Sandia National Laboratories (SNL↗