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All sourcesNASA NTRSDOE OSTI
NASA NTRS2009

LDPC Codes with Minimum Distance Proportional to Block Size

Low-density parity-check (LDPC) codes characterized by minimum Hamming distances proportional to block sizes have been demonstrated. Like the codes mentioned in the immediately preceding article, the present codes are error-correcting codes suitable for use in a variety of wireless data-communication systems that include noisy channels. The previously mentioned codes have low decoding thresholds and reasonably low error floors. However, the minimum Hamming distances of those codes do not grow linearly with code-block sizes. Codes that have this minimum-distance property exhibit very low error floors. Examples of such codes include regular LDPC codes with variable degrees of at least 3. Unfortunately, the decoding thresholds of regular LDPC codes are high. Hence, there is a need for LDPC codes characterized by both low decoding thresholds and, in order to obtain acceptably low error floors, minimum Hamming distances that are proportional to code-block sizes. The present codes were developed to satisfy this need. The minimum Hamming distances of the present codes have been shown, through consideration of ensemble-average weight enumerators, to be proportional to code block sizes. As in the cases of irregular ensembles, the properties of these codes are sensitive to the proportion of degree-2 variable nodes. A code having too few such nodes tends to have an iterative decoding threshold that is far from the capacity threshold. A code having too many such nodes tends not to exhibit a minimum distance that is proportional to block size. Results of computational simulations have shown that the decoding thresholds of codes of the present type are lower than those of regular LDPC codes. Included in the simulations were a few examples from a family of codes characterized by rates ranging from low to high and by thresholds that adhere closely to their respective channel capacity thresholds; the simulation results from these examples showed that the codes in question have low error floors as well as low decoding thresholds. As an example, the illustration shows the protograph (which represents the blueprint for overall construction) of one proposed code family for code rates greater than or equal to 1.2. Any size LDPC code can be obtained by copying the protograph structure N times, then permuting the edges. The illustration also provides Field Programmable Gate Array (FPGA) hardware performance simulations for this code family. In addition, the illustration provides minimum signal-to-noise ratios (Eb/No) in decibels (decoding thresholds) to achieve zero error rates as the code block size goes to infinity for various code rates. In comparison with the codes mentioned in the preceding article, these codes have slightly higher decoding thresholds.

Divsalar, Dariush↗
NASA NTRS2009

Constructing LDPC Codes from Loop-Free Encoding Modules

A method of constructing certain low-density parity-check (LDPC) codes by use of relatively simple loop-free coding modules has been developed. The subclasses of LDPC codes to which the method applies includes accumulate-repeat-accumulate (ARA) codes, accumulate-repeat-check-accumulate codes, and the codes described in Accumulate-Repeat-Accumulate-Accumulate Codes (NPO-41305), NASA Tech Briefs, Vol. 31, No. 9 (September 2007), page 90. All of the affected codes can be characterized as serial/parallel (hybrid) concatenations of such relatively simple modules as accumulators, repetition codes, differentiators, and punctured single-parity check codes. These are error-correcting codes suitable for use in a variety of wireless data-communication systems that include noisy channels. These codes can also be characterized as hybrid turbolike codes that have projected graph or protograph representations (for example see figure); these characteristics make it possible to design high-speed iterative decoders that utilize belief-propagation algorithms. The present method comprises two related submethods for constructing LDPC codes from simple loop-free modules with circulant permutations. The first submethod is an iterative encoding method based on the erasure-decoding algorithm. The computations required by this method are well organized because they involve a parity-check matrix having a block-circulant structure. The second submethod involves the use of block-circulant generator matrices. The encoders of this method are very similar to those of recursive convolutional codes. Some encoders according to this second submethod have been implemented in a small field-programmable gate array that operates at a speed of 100 megasymbols per second. By use of density evolution (a computational- simulation technique for analyzing performances of LDPC codes), it has been shown through some examples that as the block size goes to infinity, low iterative decoding thresholds close to channel capacity limits can be achieved for the codes of the type in question having low maximum variable node degrees. The decoding thresholds in these examples are lower than those of the best-known unstructured irregular LDPC codes constrained to have the same maximum node degrees. Furthermore, the present method enables the construction of codes of any desired rate with thresholds that stay uniformly close to their respective channel capacity thresholds.

Divsalar, Dariush↗
NASA NTRS2007

Accumulate-Repeat-Accumulate-Accumulate Codes

Accumulate-repeat-accumulate-accumulate (ARAA) codes have been proposed, inspired by the recently proposed accumulate-repeat-accumulate (ARA) codes. These are error-correcting codes suitable for use in a variety of wireless data-communication systems that include noisy channels. ARAA codes can be regarded as serial turbolike codes or as a subclass of low-density parity-check (LDPC) codes, and, like ARA codes they have projected graph or protograph representations; these characteristics make it possible to design high-speed iterative decoders that utilize belief-propagation algorithms. The objective in proposing ARAA codes as a subclass of ARA codes was to enhance the error-floor performance of ARA codes while maintaining simple encoding structures and low maximum variable node degree.

Divsalar, Dariush↗
NASA NTRS2010

Short-Block Protograph-Based LDPC Codes

Short-block low-density parity-check (LDPC) codes of a special type are intended to be especially well suited for potential applications that include transmission of command and control data, cellular telephony, data communications in wireless local area networks, and satellite data communications. [In general, LDPC codes belong to a class of error-correcting codes suitable for use in a variety of wireless data-communication systems that include noisy channels.] The codes of the present special type exhibit low error floors, low bit and frame error rates, and low latency (in comparison with related prior codes). These codes also achieve low maximum rate of undetected errors over all signal-to-noise ratios, without requiring the use of cyclic redundancy checks, which would significantly increase the overhead for short blocks. These codes have protograph representations; this is advantageous in that, for reasons that exceed the scope of this article, the applicability of protograph representations makes it possible to design highspeed iterative decoders that utilize belief- propagation algorithms.

Divsalar, Dariush↗
NASA NTRSDate not supplied

Chasing Shadows in the Night: How NASA's Kepler and TESS Missions Are Revolutionizing Exoplanet Science

The first planet outside our own solar system was discovered almost thirty years ago in an extremely unlikely place, orbiting a pulsar, and the first exoplanet orbiting a Sun-like star was discovered nearly 26 years ago. In the time since, we’ve detected over 5000 planets and over 75% of these have been detected by transit surveys. The Kepler Mission, launched in 2009, has found the lion’s share of these exoplanets, and demonstrated that each star in the night sky has, on average, at least one planet. Kepler’s success spurred NASA and ESA to select several exoplanet-themed missions to move the field of exoplanet science forward from discovery to characterization: How do these planets form and evolve? What is the structure and composition of the atmospheres and interiors of these planets? Can we detect biomarkers in the atmospheres of these planets and learn the answer to the fundamental question, are we alone? NASA selected the Transiting Exoplanet Survey Satellite (TESS) in 2014 to conduct a nearly all-sky survey for transiting planets with the goal of identifying at least 50 small planets with measured masses that can be followed up by large telescopic assets, such as the upcoming James Webb Space Telescope. TESS has discovered 266 exoplanets so far, 100 of which are smaller than earth with measured masses. In this talk I will describe how we detect weak transit signatures in noisy but beautiful transit survey data sets and present some of the most compelling discoveries made so far by Kepler and TESS.

TESS↗
NASA NTRS1989

Radio frequency interference at Jodrell Bank Observatory within the protected 21 cm band

Radio frequency interference (RFI) will provide one of the most difficult challenges to systematic Searches for Extraterrestrial Intelligence (SETI) at microwave frequencies. The SETI-specific equipment is being optimized for the detection of signals generated by a technology rather than those generated by natural processes in the universe. If this equipment performs as expected, then it will inevitably detect many signals originating from terrestrial technology. If these terrestrial signals are too numerous and/or strong, the equipment will effectively be blinded to the (presumably) weaker extraterrestrial signals being sought. It is very difficult to assess how much of a problem RFI will actually represent to future observations, without employing the equipment and beginning the search. In 1983 a very high resolution spectrometer was placed at the Nuffield Radio Astronomy Laboratories at Jodrell Bank, England. This equipment permitted an investigation of the interference environment at Jodrell Bank, at that epoch, and at frequencies within the 21 cm band. This band was chosen because it has long been "protected" by international agreement; no transmitters should have been operating at those frequencies. The data collected at Jodrell Bank were expected to serve as a "best case" interference scenario and provide the minimum design requirements for SETI equipment that must function in the real and noisy environment. This paper describes the data collection and analysis along with some preliminary conclusions concerning the nature of the interference environment at Jodrell Bank.

NASA Discipline Number 52-60↗
NASA NTRS2006

Practical Aspects of the Equation-Error Method for Aircraft Parameter Estimation

Various practical aspects of the equation-error approach to aircraft parameter estimation were examined. The analysis was based on simulated flight data from an F-16 nonlinear simulation, with realistic noise sequences added to the computed aircraft responses. This approach exposes issues related to the parameter estimation techniques and results, because the true parameter values are known for simulation data. The issues studied include differentiating noisy time series, maximum likelihood parameter estimation, biases in equation-error parameter estimates, accurate computation of estimated parameter error bounds, comparisons of equation-error parameter estimates with output-error parameter estimates, analyzing data from multiple maneuvers, data collinearity, and frequency-domain methods.

Morelli, Eugene a.↗
DOE OSTI2021

Geometrical-Based Generative Adversarial Network to Enhance Digital Rock Image Quality

X-ray microcomputed tomography (micro-CT) is a common tool for the study of porous media structures and properties. High-quality micro-CT data are required to accurately capture pore structures. Acquiring high-quality micro-CT data, however, is not always possible, owing to application limitations and experimental constraints. Therefore, we propose a geometrical-based generative adversarial network (GAN) to rapidly restore noisy micro-CT images to their clean counterparts. The training data and related ground-truth (GT) data are scanned for 7 min and 9.5 h, respectively. To evaluate the performance of the geometrical-based GAN, a 6003 voxel image that has never been used for training is reconstructed and compared with the corresponding GT image. Histogram matching and linear normalization are implemented to adjust the histogram of the reconstructed image to that of the GT image. A watershed-based segmentation method is then applied to delineate pore and solid phases. Lastly, we measure the Minkowski functionals and petrophysical properties, including absolute permeability, pore size distribution, drainage capillary pressure-saturation curve, and imbibition relative permeability, to estimate the physical accuracy of the denoised image. The results show that the proposed geometrical-based GAN can accurately restore noisy micro-CT data. By reducing the scanning time from 9.5 h to 7 min, the expenditure of collecting micro-CT can be decreased significantly. This is particularly important for applications where time-lapse images of a dynamic process are required, high-throughput imaging is necessary for real-time data analysis, or where the quantification of large sample volumes is required.

58 GEOSCIENCES↗
NASA NTRS1989

Advanced orbiting systems - A standard architecture for space data communications

The standard data handling service architecture developed by the Consultative Committee for Space Data Systems is discussed. Special attention is given to the communications protocols that are recommended for the networked transfer of space mission data, with emphasis on the unique requirements of transmitting many different data types through the weak-signal noisy space channels at high rates (up to many hundreds of megabits per second). A user service model of a typical space mission data flow configuration, known as the 'pipe diagram', is described in detail.

Hooke, Adrian J.↗
NASA NTRS2022

MLtool: Universal Supervised Machine Learning Tool to Model Tabulated Data

Machine Learning (ML) is a subfield of Artificial Intelligence that gives computers the ability to learn from past data without being explicitly programmed. The predictive capabilities of ML models have already been used to facilitate several scientific breakthroughs. However, the practical application of ML is often limited due to the gaps in technical knowledge of its users. The common issue faced by many scientific researchers is the inability to choose the appropriate ML pipelines that are needed to treat real-world data, which is often sparse and noisy. To solve this problem, we have developed an automated Machine Learning tool (MLtool) that includes a set of ML algorithms and approaches to aid scientific researchers. The current version of MLtool is implemented as an object-oriented Python code that is easily extensible. It includes 44 different regression algorithms used to model data. MLtool helps users select the best model for their data, based on the scoring metrics used. Besides regression algorithms, MLtool also includes a suite of pre- and post-processing techniques such as missing value imputation, categorical variable encoding, input feature normalization, uncertainty quantification, exploratory data analysis (EDA), etc. MLtool was tested on several publicly available multi-dimensional data sets and was found capable of making accurate predictions.

Machine learning↗
NASA NTRS2022

MLtool Python Code

Machine Learning (ML) is a subfield of Artificial Intelligence that gives computers the ability to learn from past data without being explicitly programmed. The predictive capabilities of ML models have already been used to facilitate several scientific breakthroughs. However, the practical application of ML is often limited due to the gaps in technical knowledge of its users. The common issue faced by many scientific researchers is the inability to choose the appropriate ML pipelines that are needed to treat real-world data, which is often sparse and noisy. To solve this problem, we have developed an automated Machine Learning tool (MLtool) that includes a set of ML algorithms and approaches to aid scientific researchers. The current version of MLtool is implemented as an object-oriented Python code that is easily extensible. It includes 44 different regression algorithms used to model data. MLtool helps users select the best model for their data, based on the scoring metrics used. Besides regression algorithms, MLtool also includes a suite of pre- and post-processing techniques such as missing value imputation, categorical variable encoding, input feature normalization, uncertainty quantification, exploratory data analysis (EDA), etc. MLtool was tested on several publicly available multi-dimensional data sets and was found capable of making accurate predictions.

Machine Learning↗
NASA NTRS1979

Performance of unbalanced QPSK in the presence of noisy reference and crosstalk

The problem of transmitting two telemetry data streams having different rates and different powers using unbalanced quadriphase shift keying (UQPSK) signaling is considered. It is noted that the presence of a noisy carrier phase reference causes a degradation in detection performance in coherent communications systems and that imperfect carrier synchronization not only attenuates the main demodulated signal voltage in UQPSK but also produces interchannel interference (crosstalk) which degrades the performance still further. Exact analytical expressions for symbol error probability of UQPSK in the presence of noise phase reference are derived.

Divsalar, D.↗
NASA NTRS1978

A subjective field study of helicopter blade-slap noise

The effects of impulsiveness on the noisiness of helicopters are examined by varying the main rotor speed while maintaining a constant airspeed. This resulted in other characteristics of the noise being held relatively constant. Other controlled variables included altitude, side line distance, descent operations, and level flyovers. A description is provided of the concept, experimental design and procedures along with results based on partial analyses of acoustic and subjective response data. No significant improvement in the noisiness predictive ability of EPNL was provided by either proposed or an A-weighted crest factor correction for impulsiveness.

Powell, C. A.↗
NASA NTRS1995

Effect Of Transition Density On Performance Of A DTTL

One estimates minimum transition density needed to limit symbol-error rate. Theoretical calculations and accompanying computer simulations provide numerical basis for specification of minimum data-transition density needed for adequate performance of radio receiver processing noisy signal containing non-return-to-zero (NRZ) stream of data symbols (bits). By use of digital-data-transition-tracking loop (DTTL), receiver strives to synchronize operation with data symbols. Performance of receiver in terms of ability to keep symbol-error rate (SER) in output of receiver below specified level depends on symbol signal-to-noise ratio (SSNR) of incoming signal and on degree of synchronization. Ability of DTTL to maintain synchronization depends partly on SSNR and partly on data-transition density.

Nguyen, Tien M.↗
DOE OSTI2023

A case study of denoising microseismic data in the Farnsworth, TX CO 2 EOR site

As geologic carbon sequestration projects begin to be funded with a higher degree of frequency, microseismic monitoring will become more necessary to establish caprock integrity and induced seismicity risk. The Farnsworth, TX site, which hosts enhanced oil recovery operations, provides an ideal laboratory to test essential components of microseismic monitoring such as surface station placement, denoising, and different autopicker methods. We find that despite careful optimization, the surface station placement at the Farnsworth site was insufficient given the high level of background noise from the industrial operations at the oil field. Thus, we use only borehole geophone data in our processing. Two denoising techniques were examined: the DeepDenoiser and the continuous wavelet transform. The continuous wavelet transform was shown to be a valuable tool in converting between raw waveforms to processed denoised waveforms for microseismic monitoring. In the case of the noisy waveforms, only ten detections are found, compared with 90 in the denoised data for a two-hour window. The DeepDenoiser suffered from the fact that the training data was regional earthquake data. In addition, the PhaseNet machine-learning autopicker was applied to both the noisy and the denoised data, and this algorithm detected thousands of more arrivals in the data denoised with the continuous wavelet transform technique.

58 GEOSCIENCES↗
NASA NTRS2012

Parametric 3D Atmospheric Reconstruction in Highly Variable Terrain with Recycled Monte Carlo Paths and an Adapted Bayesian Inference Engine

We describe a method for accelerating a 3D Monte Carlo forward radiative transfer model to the point where it can be used in a new kind of Bayesian retrieval framework. The remote sensing challenge is to detect and quantify a chemical effluent of a known absorbing gas produced by an industrial facility in a deep valley. The available data is a single low resolution noisy image of the scene in the near IR at an absorbing wavelength for the gas of interest. The detected sunlight has been multiply reflected by the variable terrain and/or scattered by an aerosol that is assumed partially known and partially unknown. We thus introduce a new class of remote sensing algorithms best described as "multi-pixel" techniques that call necessarily for a 3D radaitive transfer model (but demonstrated here in 2D); they can be added to conventional ones that exploit typically multi- or hyper-spectral data, sometimes with multi-angle capability, with or without information about polarization. The novel Bayesian inference methodology uses adaptively, with efficiency in mind, the fact that a Monte Carlo forward model has a known and controllable uncertainty depending on the number of sun-to-detector paths used.

Monte Carlo↗
NASA NTRS1980

Microprocessor realizations of range and range-rate filters in radar systems

This paper describes the implementation of digital radar range-rate filters on a microprocessor-based system. A range-rate filter processes a digitized noisy range signal to recover smoothed range data and its derivative, range rate. Two filter designs are implemented. Considerations aiding their efficient operation on an 8-bit microprocessor are discussed. The filters are subjected to a noisy range input signal of known variance, and the associated output signals are statistically analysed to determine noise-rejection characteristics. These results are compared to analytical predictions.

Fleischer, D.↗
DOE OSTI2024

Multitiered computational methodology for extracting three-dimensional rotational diffusion coefficients from x-ray photon correlation spectroscopy data without structural information

X-ray photon correlation spectroscopy (XPCS) is a powerful technique for analyzing particle systems by investigating their dynamics in suspensions across a broad range of temporal and spatial scales. This is done by illuminating samples with coherent x-ray beams and calculating the correlation function of the obtained x-ray scattering images. XPCS is uniquely suited for studying Brownian dynamics, consisting of translational and rotational diffusion. While traditional XPCS image analysis techniques can extract translational diffusion components, they are unable to estimate rotational diffusion coefficients. Here, we introduce a methodology that combines the angular-temporal cross-correlation analysis and a algorithmic framework called Multi-Tiered Estimation for Correlation Spectroscopy in 3D for estimating three-dimensional rotational diffusion coefficients from XPCS images of three-dimensional particle systems. We demonstrate our methodology for extracting rotational diffusion coefficients from XPCS data by applying it to simulated noisy x-ray images of systems of crossing nanotubes and proteins that evolve under translational and rotational Brownian motion for different diffusion rates. Furthermore, our results show that our approach determines rotational diffusion coefficients within a few percent error.

97 MATHEMATICS AND COMPUTING↗