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NASA NTRS1975

Robustly optimal rate one-half binary convolutional codes

Three optimality criteria for convolutional codes are considered in this correspondence: namely, free distance, minimum distance, and distance profile. Here we report the results of computer searches for rate one-half binary convolutional codes that are 'robustly optimal' in the sense of being optimal for one criterion and optimal or near-optimal for the other two criteria. Comparisons with previously known codes are made. The results of a computer simulation are reported to show the importance of the distance profile to computational performance with sequential decoding.

Johannesson, R.↗
NASA NTRS1975

On optimal soft-decision demodulation

Wozencraft and Kennedy have suggested that the appropriate demodulator criterion of goodness is the cut-off rate of the discrete memoryless channel created by the modulation system; the criterion of goodness adopted in this note is the symmetric cut-off rate which differs from the former criterion only in that the signals are assumed equally likely. Massey's necessary condition for optimal demodulation of binary signals is generalized to M-ary signals. It is shown that the optimal demodulator decision regions in likelihood space are bounded by hyperplanes. An iterative method is formulated for finding these optimal decision regions from an initial good quess. For additive white Gaussian noise, the corresponding optimal decision regions in signal space are bounded by hypersurfaces with hyperplane asymptotes; these asymptotes themselves bound the decision regions of a demodulator which, in several examples, is shown to be virtually optimal. In many cases, the necessary condition for demodulator optimality is also sufficient, but a counter example to its general sufficiency is given.

Lee, L. N.↗
NASA NTRS2014

First All-Sky Search for Continuous Gravitational Waves from Unknown Sources in Binary Systems

We present the first results of an all-sky search for continuous gravitational waves from unknown spinning neutron stars in binary systems using LIGO and Virgo data. Using a specially developed analysis program, the TwoSpect algorithm, the search was carried out on data from the sixth LIGO science run and the second and third Virgo science runs. The search covers a range of frequencies from 20 Hz to 520 Hz, a range of orbital periods from 2 to ∼2,254 h and a frequency- and period-dependent range of frequency modulation depths from 0.277 to 100 mHz. This corresponds to a range of projected semimajor axes of the orbit from ∼0.6 × 10(exp −3) ls to ∼6,500 ls assuming the orbit of the binary is circular. While no plausible candidate gravitational wave events survive the pipeline, upper limits are set on the analyzed data. The most sensitive 95% confidence upper limit obtained on gravitational wave strain is 2.3 × 10(exp −24) at 217 Hz, assuming the source waves are circularly polarized. Although this search has been optimized for circular binary orbits, the upper limits obtained remain valid for orbital eccentricities as large as 0.9. In addition, upper limits are placed on continuous gravitational wave emission from the low-mass x-ray binary Scorpius X-1 between 20 Hz and 57.25 Hz.

systems↗
NASA NTRS1994

Maximum-likelihood soft-decision decoding of block codes using the A* algorithm

The A* algorithm finds the path in a finite depth binary tree that optimizes a function. Here, it is applied to maximum-likelihood soft-decision decoding of block codes where the function optimized over the codewords is the likelihood function of the received sequence given each codeword. The algorithm considers codewords one bit at a time, making use of the most reliable received symbols first and pursuing only the partially expanded codewords that might be maximally likely. A version of the A* algorithm for maximum-likelihood decoding of block codes has been implemented for block codes up to 64 bits in length. The efficiency of this algorithm makes simulations of codes up to length 64 feasible. This article details the implementation currently in use, compares the decoding complexity with that of exhaustive search and Viterbi decoding algorithms, and presents performance curves obtained with this implementation of the A* algorithm for several codes.

Ekroot, L.↗
NASA NTRS1999

Efficient IR Transmission Diffraction Grating for Circularly Polarized Light

Numerical methods, using rigorous coupled wave theory, are used to design rectangular relief diffraction gratings for an infrared application which requires comparable first order efficiencies in the TE and TM polarization states. The depth, period, and fill factor of the grating are varied to identify optimal two level binary lamellar grating profiles which predict efficiencies for individual TM and TE polarizations above 75 percent, while keeping the difference between the two efficiencies within 10 percent. The application at hand is a rotating, transmissive diffractive scanner for space-based coherent lidar. The operating wavelength is 2.0 microns. A collimated, circularly polarized beam is incident on the diffractive scanner at the Bragg angle; 30 and 45 degree beam deflection angles being studied. Fused silica is the substrate material of choice. Selected designs are fabricated on 3 inch fused silica substrates using lithographic methods. The performance of the test pieces is measured and compared to theoretical predictions.

Cole, Helen↗
NASA NTRS2013

Classification of Dust Days by Satellite Remotely Sensed Aerosol Products

Considerable progress in satellite remote sensing (SRS) of dust particles has been seen in the last decade. From an environmental health perspective, such an event detection, after linking it to ground particulate matter (PM) concentrations, can proxy acute exposure to respirable particles of certain properties (i.e. size, composition, and toxicity). Being affected considerably by atmospheric dust, previous studies in the Eastern Mediterranean, and in Israel in particular, have focused on mechanistic and synoptic prediction, classification, and characterization of dust events. In particular, a scheme for identifying dust days (DD) in Israel based on ground PM10 (particulate matter of size smaller than 10 nm) measurements has been suggested, which has been validated by compositional analysis. This scheme requires information regarding ground PM10 levels, which is naturally limited in places with sparse ground-monitoring coverage. In such cases, SRS may be an efficient and cost-effective alternative to ground measurements. This work demonstrates a new model for identifying DD and non-DD (NDD) over Israel based on an integration of aerosol products from different satellite platforms (Moderate Resolution Imaging Spectroradiometer (MODIS) and Ozone Monitoring Instrument (OMI)). Analysis of ground-monitoring data from 2007 to 2008 in southern Israel revealed 67 DD, with more than 88 percent occurring during winter and spring. A Classification and Regression Tree (CART) model that was applied to a database containing ground monitoring (the dependent variable) and SRS aerosol product (the independent variables) records revealed an optimal set of binary variables for the identification of DD. These variables are combinations of the following primary variables: the calendar month, ground-level relative humidity (RH), the aerosol optical depth (AOD) from MODIS, and the aerosol absorbing index (AAI) from OMI. A logistic regression that uses these variables, coded as binary variables, demonstrated 93.2 percent correct classifications of DD and NDD. Evaluation of the combined CART-logistic regression scheme in an adjacent geographical region (Gush Dan) demonstrated good results. Using SRS aerosol products for DD and NDD, identification may enable us to distinguish between health, ecological, and environmental effects that result from exposure to these distinct particle populations.

satellite remote sensing↗
NASA NTRS2011

Constraining the Braneworld with Gravitational Wave Observations

Some braneworld models may have observable consequences that, if detected, would validate a requisite element of string theory. In the infinite Randall-Sundrum model (RS2), the AdS radius of curvature, L, of the extra dimension supports a single bound state of the massless graviton on the brane, thereby reproducing Newtonian gravity in the weak-field limit. However, using the AdS/CFT correspondence, it has been suggested that one possible consequence of RS2 is an enormous increase in Hawking radiation emitted by black holes. We utilize this possibility to derive two novel methods for constraining L via gravitational wave measurements. We show that the EMRI event rate detected by LISA can constrain L at the approximately 1 micron level for optimal cases, while the observation of a single galactic black hole binary with LISA results in an optimal constraint of L less than or equal to 5 microns.

McWilliams, Sean T.↗
NASA NTRS1993

Data fusion with artificial neural networks (ANN) for classification of earth surface from microwave satellite measurements

A data fusion system with artificial neural networks (ANN) is used for fast and accurate classification of five earth surface conditions and surface changes, based on seven SSMI multichannel microwave satellite measurements. The measurements include brightness temperatures at 19, 22, 37, and 85 GHz at both H and V polarizations (only V at 22 GHz). The seven channel measurements are processed through a convolution computation such that all measurements are located at same grid. Five surface classes including non-scattering surface, precipitation over land, over ocean, snow, and desert are identified from ground-truth observations. The system processes sensory data in three consecutive phases: (1) pre-processing to extract feature vectors and enhance separability among detected classes; (2) preliminary classification of Earth surface patterns using two separate and parallely acting classifiers: back-propagation neural network and binary decision tree classifiers; and (3) data fusion of results from preliminary classifiers to obtain the optimal performance in overall classification. Both the binary decision tree classifier and the fusion processing centers are implemented by neural network architectures. The fusion system configuration is a hierarchical neural network architecture, in which each functional neural net will handle different processing phases in a pipelined fashion. There is a total of around 13,500 samples for this analysis, of which 4 percent are used as the training set and 96 percent as the testing set. After training, this classification system is able to bring up the detection accuracy to 94 percent compared with 88 percent for back-propagation artificial neural networks and 80 percent for binary decision tree classifiers. The neural network data fusion classification is currently under progress to be integrated in an image processing system at NOAA and to be implemented in a prototype of a massively parallel and dynamically reconfigurable Modular Neural Ring (MNR).

Lure, Y. M. Fleming↗
NASA NTRS1983

Evaluation of fuel additives for reduction of material imcompatibilities in methanol-gasoline blends

Screening tests determined the efficacy of six commercially available additives as modifiers of methanol's corrosivity toward metals and its weakening of tensile properties of nonmetals in automotive fuel systems. From the screening phase, three additives which seemed to protect some of the metals were tested in higher concentrations and binary combinations in search of optimal application conditions. Results indicate that two of the additives have protective properties and combining them increases the protection of the metals corroded by methanol-gasoline blends. Half of the metals in the tests were not corroded. Testing at recommended concentrations and then at higher concentrations and in combinations shows that the additives would have no protective or harmful effects on the nonmetals. Two additives emerged as candidates for application to the protection of metals in automotive methanol-gasoline fuel systems. The additives tested were assigned letter codes to protect their proprietary nature.

Rodriguez, C. F.↗
NASA NTRS2012

Orion Script Generator

NASA Engineering's Orion Script Generator (OSG) is a program designed to run on Exploration Flight Test One Software. The script generator creates a SuperScript file that, when run, accepts the filename for a listing of Compact Unique Identifiers (CUIs). These CUIs will correspond to different variables on the Orion spacecraft, such as the temperature of a component X, the active or inactive status of another component Y, and so on. OSG will use a linked database to retrieve the value for each CUI, such as "100 05," "True," and so on. Finally, OSG writes SuperScript code to display each of these variables before outputting the ssi file that allows recipients to view a graphical representation of Orion Flight Test One's status through these variables. This project's main challenge was creating flexible software that accepts and transfers many types of data, from Boolean (true or false) values to "Unsigned Long Long'' values (any number from 0 to 18,446,744,073,709,551,615). We also needed to allow bit manipulation for each variable, requiring us to program functions that could convert any of the multiple types of data into binary code. Throughout the project, we explored different methods to optimize the speed of working with the CUI database and long binary numbers. For example, the program handled extended binary numbers much more efficiently when we stored them as collections of Boolean values (true or false representing 1 or 0) instead of as collections of character strings or numbers. We also strove to make OSG as user-friendly and accommodating of different needs as possible its default behavior is to display a current CUI's maximum value and minimum value with three to five intermediate values in between, all in descending order. Fortunately, users can also add other input on the same lines as each CUI name to request different high values, low values, display options (ascending, sine, and so on), and interval sizes for generating intermediate values. Developing input validation took up quite a bit of time, but OSG's flexibility in the end was worth it.

Dooling, Robert J.↗
NASA NTRS1979

Some optimal partial-unit-memory codes

A class of time-invariant binary convolutional codes is defined, called partial-unit-memory codes. These codes are optimal in the sense of having maximum free distance for given values of R, k (the number of encoder inputs), and mu (the number of encoder memory cells). Optimal codes are given for rates R = 1/4, 1/3, 1/2, and 2/3, with mu not greater than 4 and k not greater than mu + 3, whenever such a code is better than previously known codes. An infinite class of optimal partial-unit-memory codes is also constructed based on equidistant block codes.

Lauer, G. S.↗