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At least 703 records · Page 39
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Multi-Dimensional Scaling on Groups

Leveraging the intrinsic symmetries in data for clear and efficient analysis is an important theme in signal processing and other data-driven sciences. A basic example of this is the ubiquity of the discrete Fourier transform which arises from translational symmetry (i.e. time-delay/phase-shift). Particularly important in this area is understanding how symmetries inform the algorithms that we apply to our data. In this paper we explore the behavior of the dimensionality reduction algorithm multi-dimensional scaling (MDS) in the presence of symmetry. We show that understanding the properties of the underlying symmetry group allows us to make strong statements about the output of MDS even before applying the algorithm itself. In analogy to Fourier theory, we show that in some cases only a handful of fundamental ``frequencies'' (irreducible representations derived from the corresponding group) contribute information for the MDS Euclidean embedding.

Dimensionality reduction, Representation theory, D↗
NASA NTRS1975

Performance of quasi-optimum digital FM demodulators for fading channels

This paper deals with the problem of digital demodulation of FM signals transmitted over Rayleigh and Rician fading channels. The Rayleigh and Rician fading channels are represented by two quadrature multiplicative nonzero mean white Gaussian processes in addition to an additive zero-mean white Gaussian noise. Quasi-optimum digital baseband demodulation algorithms using various nonlinear estimation techniques are derived. The digital demodulator structures are then simulated on a digital computer for an FM system with first order message spectrum for various values of the parameters for Rayleigh and Rician channels.

Dharamsi, M. T.↗
NASA NTRS1990

Flight test results of failure detection and isolation algorithms for a redundant strapdown inertial measurement unit

Flight test results for two sensor fault-tolerant algorithms developed for a redundant strapdown inertial measurement unit are presented. The inertial measurement unit (IMU) consists of four two-degrees-of-freedom gyros and accelerometers mounted on the faces of a semi-octahedron. Fault tolerance is provided by edge vector test and generalized likelihood test algorithms, each of which can provide dual fail-operational capability for the IMU. To detect the wide range of failure magnitudes in inertial sensors, which provide flight crucial information for flight control and navigation, failure detection and isolation are developed in terms of a multi level structure. Threshold compensation techniques, developed to enhance the sensitivity of the failure detection process to navigation level failures, are presented. Four flight tests were conducted in a commercial transport-type environment to compare and determine the performance of the failure detection and isolation methods. Dual flight processors enabled concurrent tests for the algorithms. Failure signals such as hard-over, null, or bias shift, were added to the sensor outputs as simple or multiple failures during the flights. Both algorithms provided timely detection and isolation of flight control level failures. The generalized likelihood test algorithm provided more timely detection of low-level sensor failures, but it produced one false isolation. Both algorithms demonstrated the capability to provide dual fail-operational performance for the skewed array of inertial sensors.

Morrell, F. R.↗
NASA NTRS1997

Improvements for Image Compression Using Adaptive Principal Component Extraction (APEX)

The issues of image compression and pattern classification have been a primary focus of researchers among a variety of fields including signal and image processing, pattern recognition, data classification, etc. These issues depend on finding an efficient representation of the source data. In this paper we collate our earlier results where we introduced the application of the. Hilbe.rt scan to a principal component algorithm (PCA) with Adaptive Principal Component Extraction (APEX) neural network model. We apply these technique to medical imaging, particularly image representation and compression. We apply the Hilbert scan to the APEX algorithm to improve results

Ziyad, Nigel A.↗
DOE OSTI2024

Denoising Seismic Waveforms Using a Wavelet-Transform-Based Machine-Learning Method

Seismic waveform data recorded at stations can be thought of as a superposition of the signal from a source of interest and noise from other sources. Frequency‐based filtering methods for waveform denoising do not result in desired outcomes when the targeted signal and noise occupy similar frequency bands. Recently, denoising techniques based on deep‐learning convolutional neural networks (CNNs), in which a recorded waveform is decomposed into signal and noise components, have led to improved results. These CNN methods, which use short‐time Fourier transform representations of the time series, provide signal and noise masks for the input waveform. These masks are used to create denoised signal and designaled noise waveforms, respectively. However, advancements in the field of image denoising have shown the benefits of incorporating discrete wavelet transforms (DWTs) into CNN architectures to create multilevel wavelet CNN (MWCNN) models. The MWCNN model preserves the details of the input due to the good time–frequency localization of the DWT. In this report we use a data set of over 382,000 constructed seismograms recorded by the University of Utah Seismograph Stations network to compare the performance of CNN and MWCNN‐based denoising models. Evaluation of both models on constructed test data shows that the MWCNN model outperforms the CNN model in the ability to recover the ground‐truth signal component in terms of both waveform similarity and preservation of amplitude information. Model evaluation of real‐world data shows that both the CNN and MWCNN models outperform standard band‐pass filtering (BPF; average improvement in signal‐to‐noise ratio of 9.6 and 19.7 dB, respectively, with respect to BPF). Evaluation of continuous data suggests the MWCNN denoiser can improve both signal detection capabilities and phase arrival time estimates.

58 GEOSCIENCES↗
DOE OSTI2019

Facile Background Discrimination in Femtosecond Stimulated Raman Spectroscopy Using a Dual-Frequency Raman Pump Technique

Femtosecond stimulated Raman spectroscopy (FSRS) is a useful technique for uncovering chemical reaction dynamics by acquiring high-resolution Raman spectra with ultrafast time resolution. However, in FSRS, it can be challenging to discern Raman features from signals arising from transient absorption and other four-wave mixing pathways. To overcome this difficulty, we combine the principles of shifted excitation Raman difference spectroscopy with a simple fixed frequency comb to perform dual-frequency Raman pump FSRS. Through the addition of only two mirrors and a slit to the standard FSRS setup, this method provides Raman spectra at two different excitation wavelengths that can be processed by an automated algorithm to reconstruct the Raman spectrum. In this study, we demonstrate the utility of dual-frequency Raman pump FSRS to easily identify Raman signatures by visual inspection for excited-state and ground-state spectra, both on- and off-resonance. We show that previously assigned short-lived vibrations of photoexcited β-carotene are actually not vibrational in nature. We also use crystalline betaine-30 as a challenging test case for this method, as the FSRS spectra contain a number of narrow transient vibronic and non-SRS features. By reliably reducing interference from background signals, the interpretation is substantially more quantitative and enables the future study of new systems, particularly those with small Raman cross-sections or solid-state samples with narrow vibronic features.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2015

ERRATUM: “Automated Transient Identification in the Dark Energy Survey” (2015, AJ, 150, 82)

Here, we describe an algorithm for identifying point-source transients and moving objects on reference-subtracted optical images containing artifacts of processing and instrumentation. The algorithm makes use of the supervised machine learning technique known as Random Forest. We present results from its use in the Dark Energy Survey Supernova program (DES-SN), where it was trained using a sample of 898,963 signal and background events generated by the transient detection pipeline. After reprocessing the data collected during the first DES-SN observing season (2013 September through 2014 February) using the algorithm, the number of transient candidates eligible for human scanning decreased by a factor of 13.4, while only 1.0% of the artificial Type Ia supernovae (SNe) injected into search images to monitor survey efficiency were lost, most of which were very faint events. Here we characterize the algorithm's performance in detail, and we discuss how it can inform pipeline design decisions for future time-domain imaging surveys, such as the Large Synoptic Survey Telescope and the Zwicky Transient Facility. An implementation of the algorithm and the training data used in this paper are available at at http://portal.nersc.gov/project/dessn/autoscan.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS2002

The New IERS Special Bureau for Loading (SBL)

Currently, the establishment of the International Earth Rotation Service (IERS) Special Bureau for Loading (SBL) is in progress as part of the IERS Global Geophysical Fluids Center (GGFC). The main purpose of the SBL is to provide reliable, consistent model predictions of loading signals that have been thoroughly tested and validated. The products will describe at least the surface deformation, gravity signal and geo-center variations due to the various surface loading processes in reference frames relevant for direct comparison with existing geodetic observing techniques. To achieve these goals, major scientific advances are required with respect to the Earth model, the theory and algorithms used to model deformations of the Earth as well as improvements in the observational data related to surface loading.

vanDam, Tonie↗
NASA NTRS2011

A Background Noise Reduction Technique Using Adaptive Noise Cancellation for Microphone Arrays

Background noise in wind tunnel environments poses a challenge to acoustic measurements due to possible low or negative Signal to Noise Ratios (SNRs) present in the testing environment. This paper overviews the application of time domain Adaptive Noise Cancellation (ANC) to microphone array signals with an intended application of background noise reduction in wind tunnels. An experiment was conducted to simulate background noise from a wind tunnel circuit measured by an out-of-flow microphone array in the tunnel test section. A reference microphone was used to acquire a background noise signal which interfered with the desired primary noise source signal at the array. The technique s efficacy was investigated using frequency spectra from the array microphones, array beamforming of the point source region, and subsequent deconvolution using the Deconvolution Approach for the Mapping of Acoustic Sources (DAMAS) algorithm. Comparisons were made with the conventional techniques for improving SNR of spectral and Cross-Spectral Matrix subtraction. The method was seen to recover the primary signal level in SNRs as low as -29 dB and outperform the conventional methods. A second processing approach using the center array microphone as the noise reference was investigated for more general applicability of the ANC technique. It outperformed the conventional methods at the -29 dB SNR but yielded less accurate results when coherence over the array dropped. This approach could possibly improve conventional testing methodology but must be investigated further under more realistic testing conditions.

Spalt, Taylor B.↗
NASA NTRS2010

Improving Global Mass Flux Solutions from Gravity Recovery and Climate Experiment (GRACE) Through Forward Modeling and Continuous Time Correlation

We describe Earth's mass flux from April 2003 through November 2008 by deriving a time series of mas cons on a global 2deg x 2deg equal-area grid at 10 day intervals. We estimate the mass flux directly from K band range rate (KBRR) data provided by the Gravity Recovery and Climate Experiment (GRACE) mission. Using regularized least squares, we take into account the underlying process dynamics through continuous space and time-correlated constraints. In addition, we place the mascon approach in the context of other filtering techniques, showing its equivalence to anisotropic, nonsymmetric filtering, least squares collocation, and Kalman smoothing. We produce mascon time series from KBRR data that have and have not been corrected (forward modeled) for hydrological processes and fmd that the former produce superior results in oceanic areas by minimizing signal leakage from strong sources on land. By exploiting the structure of the spatiotemporal constraints, we are able to use a much more efficient (in storage and computation) inversion algorithm based upon the conjugate gradient method. This allows us to apply continuous rather than piecewise continuous time-correlated constraints, which we show via global maps and comparisons with ocean-bottom pressure gauges, to produce time series with reduced random variance and full systematic signal. Finally, we present a preferred global model, a hybrid whose oceanic portions are derived using forward modeling of hydrology but whose land portions are not, and thus represent a pure GRACE-derived signal.

Sabaka, T. J.↗
NASA NTRS2019

Multi-Band Atmospheric Correction Algorithm for Ocean Color Retrievals

NASA's current Atmospheric Correction (AC) algorithm for ocean color utilizes two bands and their ratio in the Near Infrared (NIR) to estimate aerosol reflectance and aerosol type. The algorithm then extrapolates the spectral dependence of aerosol reflectance to the visible wavelengths based on modeled spectral dependence of the identified aerosol type. Future advanced ocean color sensors, such as the Ocean Color Instrument (OCI) that will be carried on the Plankton, Aerosol, Cloud, and ocean Ecosystem (PACE) satellite, will be capable of measuring the hyperspectral radiance from 340 to 890 nm at 5-nm spectral resolution and at 7 discrete Short-wave Infrared (SWIR) channels: 940, 1038,1250, 1378, 1615, 2130, and 2260 nm. To optimally employ this unprecedented instrument capability, we propose an improved AC algorithm that utilizes all atmospheric-window channels in the NIR to SWIR spectral range to reduce the uncertainty in the AC process. A theoretical uncertainty analysis of this, namely Multi-Band AC (MBAC), indicates that the algorithm can reduce the uncertainty in remote sensing reflectance (Rrs) retrievals of the ocean caused by sensor random noise. Furthermore, in optically complex waters, where the NIR signal is affected by contributions from highly-reflective turbid waters, the MBAC algorithm can be adaptively weighted to the strongly-absorbing SWIR channels to enable improved ocean color retrievals in coastal waters. We provide here a description of the algorithm and demonstrate the improved performance in ocean color retrievals, relative to the current NASA standard AC algorithm, through comparison with field measurements and assessment of propagated uncertainties in applying the MBAC algorithm to MODIS and simulated PACE OCI data.

PACE↗
NASA NTRS1983

The Development of a Digital Processing System for Accurate Range Determinations

The development of an accurate close range (from 0.0 meters to 30.0 meters) radar system for Teleoperator Maneuvering Systems (TMS) is discussed. The system under investigation is a digital processor that converts incoming signals from the radar system into their related frequency spectra. Identification will be attempted by correlating spectral characteristics with accurate range determinataions. The system will utilize an analog to digital converter for sampling and converting the signal from the radar system into 16-bit digital words (two bytes) for RAM storage, data manipulations, and computations. To remove unwanted frequency components the data will be retrieved from RAM and digitally filtered using large scale integration (LSI) circuits. Filtering will be performed by a biquadratic routine within the chip which carries out the required filter algorithm. For conversion to a frequency spectrum the filtered data will be processed by a Fast Fourier Transform chip. Analysis and identification of spectral characteristics for accurate range determinations will be made by microcomputer computations.

Pujol, A., Jr.↗
DOE OSTI2024

A Practical Solver for Scalar Data Topological Simplification

This paper presents a practical approach for the optimization of topological simplification, a central pre-processing step for the analysis and visualization of scalar data. Given an input scalar field f and a set of “signal” persistence pairs to maintain, our approaches produces an output field g that is close to f and which optimizes (i) the cancellation of “non-signal” pairs, while (ii) preserving the “signal” pairs. In contrast to pre-existing simplification algorithms, our approach is not restricted to persistence pairs involving extrema and can thus address a larger class of topological features, in particular saddle pairs in three-dimensional scalar data. Our approach leverages recent generic persistence optimization frameworks and extends them with tailored accelerations specific to the problem of topological simplification. Extensive experiments report substantial accelerations over these frameworks, thereby making topological simplification optimization practical for real-life datasets. Our approach enables a direct visualization and analysis of the topologically simplified data, e.g., via isosurfaces of simplified topology (fewer components and handles). We apply our approach to the extraction of prominent filament structures in three-dimensional data. Specifically, we show that our pre-simplification of the data leads to practical improvements over standard topological techniques for removing filament loops. Here, we also show how our approach can be used to repair genus defects in surface processing. Finally, we provide a C++ implementation for reproducibility purposes.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Model-based approach to investigate equipment-induced error in pressure-waveform derived hemodynamic measurements

Advanced hemodynamic monitoring systems have provided less invasive methods for estimating pressure-derived measurements such as pressure-derived cardiac output (CO) measurements. These devices apply algorithms to arterial pressure waveforms recorded via pressure recording components that transmit the pressure signal to a pressure monitor. While standards have been developed for pressure monitoring equipment, it is unclear how the equipment-induced error can affect secondary measurements from pressure waveforms. We propose an approach for modelling different components of a pressure monitoring system and use this model-based approach to investigate the effect of different pressure recording configurations on pressure-derived hemodynamic measurements. The proposed model-based approach is a three-step process. (1) Modelling the response of pressure recording components using bench tests; (2) verifying the identified models through nonparametric equivalence tests; and (3) assessing the effects of pressure recording components on pressure-derived measurements. To delineate the application of this approach, we performed a series of model-based analyses to quantify the combined effect of a wide range of tubing configurations with various damping ratios and natural frequencies and monitors with different bandwidths on pressure waveforms and CO measurements by six pulse contour algorithms. Model-based results show the error in pressure-derived CO measurements because of tubing configurations with different natural frequencies and damping ratios. Tubing configurations with low natural frequencies (<23 Hz) altered characteristics of pressure waveforms in a way that affected the CO measurement, some by as much as 20%. Our method can serve as a tool to quantify the performance of pressure recording systems with different dynamic properties. In conclusion, this approach can be applied to investigate the effects of physiologic signal recording configurations on various pressure-derived hemodynamic measurements.

42 ENGINEERING↗
DOE OSTI2019

High Momentum Transfer Nucleon Elastic Electromagnetic Form Factor Measurements Using Super BigBite Spectrometer at Jefferson Lab

The nucleons - protons and neutrons - are the basic building blocks of atomic nuclei. We now know that the nucleon consists of fundamental particles called quarks and gluons. The quarks interact with each other by exchanging gluons via the strong interaction. Understanding the quark-gluon structure of the nucleon, especially the confinement of quarks within the nucleon in its ground state, remains one of the main unsolved puzzles of particle physics. The nucleon electromagnetic form factors are directly related to the internal structure of the nucleon. A new generation of high precision experiments, GEp-V, GEn-II, GEn-RP, and GMn, measuring the ground state nucleon space-like electro-magnetic form factor at high momentum transfer is underway at Jefferson Lab experimental Hall-A as part of the Super Bigbite Spectrometer (SBS) program. This series of experiments will provide a new level of understanding of the nucleon structure. These experiments are highly demanding due to the extremely fast drop off of the elastic cross section with the increasing four-momentum transfer squared(Q2). This thesis provides an overview of the SBS physics program and reports on the extensive R&D program carried out to achieve the high rate running conditions essential for carrying out the SBS experiments. SBS will provide an intermediate solid angle of approximately 35 msr, which is significantly larger than the solid angle of other dipole based spectrometers at Jefferson lab. Of course, there are much larger acceptance spectrometers at Jefferson Lab, CLAS12 for example. What is special about SBS is that it provides a sizable acceptance while operating at the highest possible luminosity at Jefferson Lab. With this combination of medium acceptance and the highest available luminosity, SBS provides an unparalleled opportunity to explore the nucleon in its ground state with unprecedented resolution. The relatively large acceptance of SBS is achieved by using a large gap dipole magnet and placing it close to the target. An unavoidable consequence of this is that the SBS GEM trackers and other detectors have a clear line-of-sight view of the target and a portion of the beam-line. As a result, the background hit rate in the SBS front GEM trackers is expected to be up to 500 kHz/cm2, over the entire active area of 6000 cm2. To the best of our knowledge, this extremely high rate over such a large area is unprecedented in any particle tracking system used anywhere in the world before. Correctly reconstructing the particle tracks of interest in this very high background environment is achieved by using especially adapted high rate techniques at every step of the tracking process: optimizing the GEM module and tracker design at the hardware level, using high bandwidth electronics and real time Field Programmable Gate Array (FPGA) based background suppression techniques at the Data Acquisition (DAQ) level, and developing highly specialized tracking algorithms to pick out the signal hits from among the vast amount of background hits. In order to ensure a smooth start and running of the SBS experiments, it is extremely crucial that these techniques are developed, implemented, and tested under realistic conditions well before the actual start of the SBS experimental program. A detailed Geant4 simulation of the experiment was combined with a digitization package to generate the detector level pseudodata similar to what is expected in the actual experiments. The digitization procedures were calibrated against actual GEM data from cosmic-ray runs, X-ray tests, beam test runs in experimental Hall-A, and the PRad experiment in Hall B. Then, optimized tracking algorithms were developed and implemented in an analysis program used to analyze these pseudo-data and to extract expected high-level parameters. These extracted quantities were then compared with the input parameters from the simulation to verify and determine the performance characteristics for the SBS tracker. From this work, a final tracking efficiency of 69% at 25% occupancy was achieved, with the required reconstruction accuracy, for the GMn experiment, the first experiment in the SBS program, with background level at 100 kHz/cm2. These demonstrated parameters are adequate for the successful running of not only the GMn experiment but as well as for GEn-RP and GEn-II experiments, the second and third experiments in the program. This work builds the solid ground to further improve the tracking performance for these experiments and achieve similar conditions for the running of the GEp-V experiment, the most demanding experiment in the SBS program, with an expected background level at 500 kHz/cm2.

Di, Danning↗
DOE OSTI2016

The orbit and transit prospects for β pictoris b constrained with one milliarcsecond astrometry

A principal scientific goal of the Gemini Planet Imager (GPI) is obtaining milliarcsecond astrometry to constrain exoplanet orbits. However, astrometry of directly imaged exoplanets is subject to biases, systematic errors, and speckle noise. Here, we describe an analytical procedure to forward model the signal of an exoplanet that accounts for both the observing strategy (angular and spectral differential imaging) and the data reduction method (Karhunen–Loève Image Projection algorithm). We use this forward model to measure the position of an exoplanet in a Bayesian framework employing Gaussian processes and Markov-chain Monte Carlo to account for correlated noise. In the case of GPI data on β Pic b, this technique, which we call Bayesian KLIP-FM Astrometry (BKA), outperforms previous techniques and yields 1σ errors at or below the one milliarcsecond level. We validate BKA by fitting a Keplerian orbit to 12 GPI observations along with previous astrometry from other instruments. The statistical properties of the residuals confirm that BKA is accurate and correctly estimates astrometric errors. Our constraints on the orbit of β Pic b firmly rule out the possibility of a transit of the planet at 10-σ significance. However, we confirm that the Hill sphere of β Pic b will transit, giving us a rare chance to probe the circumplanetary environment of a young, evolving exoplanet. As a result, we provide an ephemeris for photometric monitoring of the Hill sphere transit event, which will begin at the start of April in 2017 and finish at the end of January in 2018.

79 ASTRONOMY AND ASTROPHYSICS↗
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 NTRS1993

Compensating For Computational Delay In Flight Simulation

Computer-generated imagery processed with corrective phase shifts at lower frequencies. Algorithm developed from transfer functions predicting lower-frequency components of response of aircraft short time into future. Effects of delay at lower frequencies counteracted by introducing compensatory phase shifts, opposite those caused by delay, into signals driving computer-generated imagery.

Mcfarland, Richard E.↗