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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 1,297 records · Page 72
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NASA NTRS1993

Algorithm Aligns Gyrocompass In Twisting And Swaying Vehicle

Algorithm proposed for use with strapdown inertial sensors synthesizes gyrocompass and repeatedly refines alignment of synthetic gyrocompass to maintain accuracy until time of departure. In original application, inertial sensors located in spacecraft twisting and swaying in wind on launching pad, and time of departure is time of launch. Also possible to devise terrestrial version of algorithm for use in aircraft, ground vehicle, or vessel. Algorithm includes local-level-navigator, coarse-alignment, and fine-alignment subalgorithms.

Reddy, Narotham S.↗
NASA NTRS1992

SeaWiFS technical report series. Volume 4: An analysis of GAC sampling algorithms. A case study

The Sea-viewing Wide Field-of-view Sensor (SeaWiFS) instrument will sample at approximately a 1 km resolution at nadir which will be broadcast for reception by realtime ground stations. However, the global data set will be comprised of coarser four kilometer data which will be recorded and broadcast to the SeaWiFS Project for processing. Several algorithms for degrading the one kilometer data to four kilometer data are examined using imagery from the Coastal Zone Color Scanner (CZCS) in an effort to determine which algorithm would best preserve the statistical characteristics of the derived products generated from the one kilometer data. Of the algorithms tested, subsampling based on a fixed pixel within a 4 x 4 pixel array is judged to yield the most consistent results when compared to the one kilometer data products.

Yeh, Eueng-Nan↗
NASA NTRS1992

Possibility expectation and its decision making algorithm

The fuzzy integral has been shown to be an effective tool for the aggregation of evidence in decision making. Of primary importance in the development of a fuzzy integral pattern recognition algorithm is the choice (construction) of the measure which embodies the importance of subsets of sources of evidence. Sugeno fuzzy measures have received the most attention due to the recursive nature of the fabrication of the measure on nested sequences of subsets. Possibility measures exhibit an even simpler generation capability, but usually require that one of the sources of information possess complete credibility. In real applications, such normalization may not be possible, or even desirable. In this report, both the theory and a decision making algorithm for a variation of the fuzzy integral are presented. This integral is based on a possibility measure where it is not required that the measure of the universe be unity. A training algorithm for the possibility densities in a pattern recognition application is also presented with the results demonstrated on the shuttle-earth-space training and testing images.

Keller, James M.↗
NASA NTRS1992

Forward model and CO retrieval algorithm

A progress report on the forward model and CO retrieval algorithm is presented. For the forward model, the fast-transmittance algorithm is discussed including monochromatic calculations, determination of fast-transmittance parameters, and regression errors. Simulations, retrieval technique, and sensitivity of the CO retrieval algorithm are discussed.

Strow, L. L.↗
NASA NTRS1992

Formulation and error analysis for a generalized image point correspondence algorithm

A Generalized Image Point Correspondence (GIPC) algorithm, which enables the determination of 3-D motion parameters of an object in a configuration where both the object and the camera are moving, is discussed. A detailed error analysis of this algorithm has been carried out. Furthermore, the algorithm was tested on both simulated and video-acquired data, and its accuracy was determined.

Shapiro, Linda↗
NASA NTRS1992

NASA airborne radar wind shear detection algorithm and the detection of wet microbursts in the vicinity of Orlando, Florida

The algorithms used in the NASA experimental wind shear radar system for detection, characterization, and determination of windshear hazard are discussed. The performance of the algorithms in the detection of wet microbursts near Orlando is presented. Various suggested algorithms that are currently being evaluated using the flight test results from Denver and Orlando are reviewed.

Britt, Charles L.↗
NASA NTRS1993

Testing of the on-board attitude determination and control algorithms for SAMPEX

Algorithms for on-board attitude determination and control of the Solar, Anomalous, and Magnetospheric Particle Explorer (SAMPEX) have been expanded to include a constant gain Kalman filter for the spacecraft angular momentum, pulse width modulation for the reaction wheel command, an algorithm to avoid pointing the Heavy Ion Large Telescope (HILT) instrument boresight along the spacecraft velocity vector, and the addition of digital sun sensor (DSS) failure detection logic. These improved algorithms were tested in a closed-loop environment for three orbit geometries, one with the sun perpendicular to the orbit plane, and two with the sun near the orbit plane - at Autumnal Equinox and at Winter Solstice. The closed-loop simulator was enhanced and used as a truth model for the control systems' performance evaluation and sensor/actuator contingency analysis. The simulations were performed on a VAX 8830 using a prototype version of the on-board software.

Mccullough, Jon D.↗
NASA NTRS1993

Computationally efficient algorithms for real-time attitude estimation

For many practical spacecraft applications, algorithms for determining spacecraft attitude must combine inputs from diverse sensors and provide redundancy in the event of sensor failure. A Kalman filter is suitable for this task, however, it may impose a computational burden which may be avoided by sub optimal methods. A suboptimal estimator is presented which was implemented successfully on the Delta Star spacecraft which performed a 9 month SDI flight experiment in 1989. This design sought to minimize algorithm complexity to accommodate the limitations of an 8K guidance computer. The algorithm used is interpreted in the framework of Kalman filtering and a derivation is given for the computation.

Pringle, Steven R.↗
NASA NTRS1993

Analysis of the Command and Control Segment (CCS) attitude estimation algorithm

This paper categorizes the qualitative behavior of the Command and Control Segment (CCS) differential correction algorithm as applied to attitude estimation using simultaneous spin axis sun angle and Earth cord length measurements. The categories of interest are the domains of convergence, divergence, and their boundaries. Three series of plots are discussed that show the dependence of the estimation algorithm on the vehicle radius, the sun/Earth angle, and the spacecraft attitude. Common qualitative dynamics to all three series are tabulated and discussed. Out-of-limits conditions for the estimation algorithm are identified and discussed.

Stockwell, Catherine↗
NASA NTRS1992

Two neural network algorithms for designing optimal terminal controllers with open final time

Multilayer neural networks, trained by the backpropagation through time algorithm (BPTT), have been used successfully as state-feedback controllers for nonlinear terminal control problems. Current BPTT techniques, however, are not able to deal systematically with open final-time situations such as minimum-time problems. Two approaches which extend BPTT to open final-time problems are presented. In the first, a neural network learns a mapping from initial-state to time-to-go. In the second, the optimal number of steps for each trial run is found using a line-search. Both methods are derived using Lagrange multiplier techniques. This theoretical framework is used to demonstrate that the derived algorithms are direct extensions of forward/backward sweep methods used in N-stage optimal control. The two algorithms are tested on a Zermelo problem and the resulting trajectories compare favorably to optimal control results.

Plumer, Edward S.↗
NASA NTRS1993

Fast parallel algorithms that compute transitive closure of a fuzzy relation

The notion of a transitive closure of a fuzzy relation is very useful for clustering in pattern recognition, for fuzzy databases, etc. The original algorithm proposed by L. Zadeh (1971) requires the computation time O(n(sup 4)), where n is the number of elements in the relation. In 1974, J. C. Dunn proposed a O(n(sup 2)) algorithm. Since we must compute n(n-1)/2 different values s(a, b) (a not equal to b) that represent the fuzzy relation, and we need at least one computational step to compute each of these values, we cannot compute all of them in less than O(n(sup 2)) steps. So, Dunn's algorithm is in this sense optimal. For small n, it is ok. However, for big n (e.g., for big databases), it is still a lot, so it would be desirable to decrease the computation time (this problem was formulated by J. Bezdek). Since this decrease cannot be done on a sequential computer, the only way to do it is to use a computer with several processors working in parallel. We show that on a parallel computer, transitive closure can be computed in time O((log(sub 2)(n))2).

Kreinovich, Vladik YA.↗
NASA NTRS1993

Resource utilization model for the algorithm to architecture mapping model

The analytical model for resource utilization and the variable node time and conditional node model for the enhanced ATAMM model for a real-time data flow architecture are presented in this research. The Algorithm To Architecture Mapping Model, ATAMM, is a Petri net based graph theoretic model developed at Old Dominion University, and is capable of modeling the execution of large-grained algorithms on a real-time data flow architecture. Using the resource utilization model, the resource envelope may be obtained directly from a given graph and, consequently, the maximum number of required resources may be evaluated. The node timing diagram for one iteration period may be obtained using the analytical resource envelope. The variable node time model, which describes the change in resource requirement for the execution of an algorithm under node time variation, is useful to expand the applicability of the ATAMM model to heterogeneous architectures. The model also describes a method of detecting the presence of resource limited mode and its subsequent prevention. Graphs with conditional nodes are shown to be reduced to equivalent graphs with time varying nodes and, subsequently, may be analyzed using the variable node time model to determine resource requirements. Case studies are performed on three graphs for the illustration of applicability of the analytical theories.

Stoughton, John W.↗
NASA NTRS1991

Probabilistic structural analysis algorithm development for computational efficiency

The PSAM (Probabilistic Structural Analysis Methods) program is developing a probabilistic structural risk assessment capability for the SSME components. An advanced probabilistic structural analysis software system, NESSUS (Numerical Evaluation of Stochastic Structures Under Stress), is being developed as part of the PSAM effort to accurately simulate stochastic structures operating under severe random loading conditions. One of the challenges in developing the NESSUS system is the development of the probabilistic algorithms that provide both efficiency and accuracy. The main probability algorithms developed and implemented in the NESSUS system are efficient, but approximate in nature. In the last six years, the algorithms have improved very significantly.

Wu, Y.-T.↗
NASA NTRS1992

Complex generalized minimal residual algorithm for iterative solution of quantum-mechanical reactive scattering equations

Complex dense matrices corresponding to the D + H2 and O + HD reactions were solved using a complex generalized minimal residual (GMRes) algorithm described by Saad and Schultz (1986) and Saad (1990). To provide a test case with a different structure, the H + H2 system was also considered. It is shown that the computational effort for solutions with the GMRes algorithm depends on the dimension of the linear system, the total energy of the scattering problem, and the accuracy criterion. In several cases with dimensions in the range 1110-5632, the GMRes algorithm outperformed the LAPACK direct solver, with speedups for the linear equation solution as large as a factor of 23.

Chatfield, David C.↗
NASA NTRS1992

A passive microwave algorithm for tropical oceanic rainfall

This study discusses a rainfall algorithm utilizing six channels of microwave radiance data from the Nimbus-7 Scanning Multifrequency Microwave Radiometer. The algorithm is intended for short-term climate studies over the ocean at low latitudes. To find a set of functional relationships, rain rates are regressed on brightness temperatures for each channel. Next, these functions are integrated over a class of rain-rate distributions to find relations between mean brightness temperatures and mean rain rates. This step accounts for beam filling. Finally, weights are obtained for combining the rain rates from the individual channels. The weights vary with the rain rates, so that the optimum combination of channels is always used. Results are stored in a database grid 1 deg latitude x 1 deg longitude by one month. To test the algorithm, three years (1979-81) of data from the Indian Ocean are processed.

Hinton, Barry B.↗
NASA NTRS1992

A new algorithm for L2 optimal model reduction

In this paper the quadratically optimal model reduction problem for single-input, single-output systems is considered. The reduced order model is determined by minimizing the integral of the magnitude-squared of the transfer function error. It is shown that the numerator coefficients of the optimal approximant satisfy a weighted least squares problem and, on this basis, a two-step iterative algorithm is developed combining a least squares solver with a gradient minimizer. Convergence of the proposed algorithm to stationary values of the quadratic cost function is proved. The formulation is extended to handle the frequency-weighted optimal model reduction problem. Three examples demonstrate the optimization algorithm.

Spanos, J. T.↗
NASA NTRS1993

Newton algorithm for fitting transfer functions to frequency response measurements

In this paper the problem of synthesizing transfer functions from frequency response measurements is considered. Given a complex vector representing the measured frequency response of a physical system, a transfer function of specified order is determined that minimizes the sum of the magnitude-squared of the frequency response errors. This nonlinear least squares minimization problem is solved by an iterative global descent algorithm of the Newton type that converges quadratically near the minimum. The unknown transfer function is expressed as a sum of second-order rational polynomials, a parameterization that facilitates a numerically robust computer implementation. The algorithm is developed for single-input, single-output, causal, stable transfer functions. Two numerical examples demonstrate the effectiveness of the algorithm.

Spanos, J. T.↗
NASA NTRS1991

A fast algorithm for image-based ranging

Image-based ranging has emerged as a critical issue in the low altitude operation of flight vehicles such as rotorcraft and planetary landers. These flight regimes require ranging systems for recovering the geometry of the terrain and obstacles for use with guidance algorithms. The development of a ranging equation combining image irradiance together with various order spatial partial derivatives and the vehicle motion parameters is discussed. The ranging equation is in the form of a polynomial in scene depth. Two-dimensional linear filters are then used to compute the coefficients of this polynomial to result in a fast image-based ranging algorithm. Performance of the algorithm is demonstrated using laboratory images.

Menon, P. K. A.↗