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At least 757 records · Page 42

On state estimation for an orbiting single tether system

The effects of instrumentation accuracy and configuration on estimation error are studied for the small expendable-tether deployment system (SEDS) using a continuous-discrete extended Kalman filter (CDEKF) state estimator. A twelfth order model that incorporates the rigid body modes of the tether as well as the satellite attitude dynamics is developed. Simulation results using the model and the estimator indicate that the originally planned instrumentation package could not estimate the state vector adequately. Recommendations are made and results presented that reduce the estimation error by adding instruments and increasing selected measurement accuracies.

Greene, Michael E.↗

Colored noise effects on batch attitude accuracy estimates

The effects of colored noise on the accuracy of batch least squares parameter estimates with applications to attitude determination cases are investigated. The standard approaches used for estimating the accuracy of a computed attitude commonly assume uncorrelated (white) measurement noise, while in actual flight experience measurement noise often contains significant time correlations and thus is colored. For example, horizon scanner measurements from low Earth orbit were observed to show correlations over many minutes in response to large scale atmospheric phenomena. A general approach to the analysis of the effects of colored noise is investigated, and interpretation of the resulting equations provides insight into the effects of any particular noise color and the worst case noise coloring for any particular parameter estimate. It is shown that for certain cases, the effects of relatively short term correlations can be accommodated by a simple correction factor. The errors in the predicted accuracy assuming white noise and the reduced accuracy due to the suboptimal nature of estimators that do not take into account the noise color characteristics are discussed. The appearance of a variety of sample noise color characteristics are demonstrated through simulation, and their effects are discussed for sample estimation cases. Based on the analysis, options for dealing with the effects of colored noise are discussed.

Bilanow, Stephen↗

Vision-based range estimation using helicopter flight data

Pilot aiding during low-altitude flight depends on the ability to detect and locate obstacles near the helicopter's intended flightpath. Computer-vision-based methods provide one general approach for obstacle detection and range estimation. Several algorithms have been developed for this purpose, but have not been tested with actual flight data. This paper presents results obtained using helicopter flight data with a feature-based range estimation algorithm. A method for recursively estimating range using a Kalman filter with a monocular sequence of images and knowledge of the camera's motion is described. The helicopter flight experiment and four resulting datasets are discussed. Finally the performance of the range estimation algorithm is explored in detail based on comparison of the range estimates with true range measurements collected during the flight experiment.

Smith, Philip N.↗

Application of magnitude estimation scaling to the assessment of subjective loudness response to simulated sonic booms

A laboratory study was conducted for the following reasons: (1) to investigate the application of magnitude estimation scaling for evaluating the subjective loudness of sonic booms; and (2) to compare the relative merits of magnitude estimation and numerical category scaling for sonic boom loudness evaluation. The study was conducted in the NASA LeRC's sonic boom simulator and used a total of 80 test subjects (48 for magnitude estimation and 32 for numerical category scaling). Results demonstrated that magnitude estimation was a practical and effective method for quantifying subjective loudness of sonic booms. When using magnitude estimation, the subjects made valid and consistent ratio judgments of sonic boom loudness irrespective of the frequency of presentation of the standard stimulus. Presentation of the standard as every fourth stimulus was preferred by the subjects and is recommended as the standard presentation frequency to be used in future tests.

S McDaniel↗

Reusable Reentry Satellite (RRS) system design study: System cost estimates document

The Reusable Reentry Satellite (RRS) program was initiated to provide life science investigators relatively inexpensive, frequent access to space for extended periods of time with eventual satellite recovery on earth. The RRS will provide an on-orbit laboratory for research on biological and material processes, be launched from a number of expendable launch vehicles, and operate in Low-Altitude Earth Orbit (LEO) as a free-flying unmanned laboratory. SAIC's design will provide independent atmospheric reentry and soft landing in the continental U.S., orbit for a maximum of 60 days, and will sustain three flights per year for 10 years. The Reusable Reentry Vehicle (RRV) will be 3-axis stabilized with artificial gravity up to 1.5g's, be rugged and easily maintainable, and have a modular design to accommodate a satellite bus and separate modular payloads (e.g., rodent module, general biological module, ESA microgravity botany facility, general botany module). The purpose of this System Cost Estimate Document is to provide a Life Cycle Cost Estimate (LCCE) for a NASA RRS Program using SAIC's RRS design. The estimate includes development, procurement, and 10 years of operations and support (O&S) costs for NASA's RRS program. The estimate does not include costs for other agencies which may track or interface with the RRS program (e.g., Air Force tracking agencies or individual RRS experimenters involved with special payload modules (PM's)). The life cycle cost estimate extends over the 10 year operation and support period FY99-2008.

Source record↗

Space Station Furnace Facility. Volume 3: Program cost estimate

The approach used to estimate costs for the Space Station Furnace Facility (SSFF) is based on a computer program developed internally at Teledyne Brown Engineering (TBE). The program produces time-phased estimates of cost elements for each hardware component, based on experience with similar components. Engineering estimates of the degree of similarity or difference between the current project and the historical data is then used to adjust the computer-produced cost estimate and to fit it to the current project Work Breakdown Structure (WBS). The SSFF Concept as presented at the Requirements Definition Review (RDR) was used as the base configuration for the cost estimate. This program incorporates data on costs of previous projects and the allocation of those costs to the components of one of three, time-phased, generic WBS's. Input consists of a list of similar components for which cost data exist, number of interfaces with their type and complexity, identification of the extent to which previous designs are applicable, and programmatic data concerning schedules and miscellaneous data (travel, off-site assignments). Output is program cost in labor hours and material dollars, for each component, broken down by generic WBS task and program schedule phase.

Source record↗

Lunar gravitational field estimation and the effects of mismodeling upon lunar satellite orbit prediction

Lunar spherical harmonic gravity coefficients are estimated from simulated observations of a near-circular low altitude polar orbiter disturbed by lunar mascons. Lunar gravity sensing missions using earth-based nearside observations with and without satellite-based far-side observations are simulated and least squares maximum likelihood estimates are developed for spherical harmonic expansion fit models. Simulations and parameter estimations are performed by a modified version of the Smithsonian Astrophysical Observatory's Planetary Ephemeris Program. Two different lunar spacecraft mission phases are simulated to evaluate the estimated fit models. Results for predicting state covariances one orbit ahead are presented along with the state errors resulting from the mismodeled gravity field. The position errors from planning a lunar landing maneuver with a mismodeled gravity field are also presented. These simulations clearly demonstrate the need to include observations of satellite motion over the far side in estimating the lunar gravity field. The simulations also illustrate that the eighth degree and order expansions used in the simulated fits were unable to adequately model lunar mascons.

Davis, John H.↗

Cost-estimating relationships for space programs

Cost-estimating relationships (CERs) are defined and discussed as they relate to the estimation of theoretical costs for space programs. The paper primarily addresses CERs based on analogous relationships between physical and performance parameters to estimate future costs. Analytical estimation principles are reviewed examining the sources of errors in cost models, and the use of CERs is shown to be affected by organizational culture. Two paradigms for cost estimation are set forth: (1) the Rand paradigm for single-culture single-system methods; and (2) the Price paradigms that incorporate a set of cultural variables. For space programs that are potentially subject to even small cultural changes, the Price paradigms are argued to be more effective. The derivation and use of accurate CERs is important for developing effective cost models to analyze the potential of a given space program.

Mandell, Humboldt C., Jr.↗

On the estimation of snow depth from microwave radiometric measurements

Multiple-channel microwave radiometric measurements made over Alaska at aircraft (near 90 and 183 GHz) and satellite (at 37 and 85 GHz) altitudes are used to study the effect of atmospheric absorption on the estimation of snow depth. The estimation is based on the radiative transfer calculations using an early theoretical model of Mie scattering of single-size particles. It is shown that the radiometric correction for the effect of atmospheric absorption is important even at 37 GHz for a reliable estimation of snow depth. Under a dry atmosphere and based on single-frequency radiometric measurements, the underestimation of snow depth could amount to 50 percent at 85 GHz and 20-30 percent at 37 GHz if the effect of atmospheric absorption is not taken into account. The snow depths estimated from the 90-GHz aircraft and 85-GHz satellite measurements are found to be in reasonable agreement. However, there is a discrepancy in the snow depths estimated from the 37-GHz (at both vertical and horizontal polarizations) and 85-GHz satellite measurements.

Wang, James R.↗

Vision-based range estimation using helicopter flight data

Pilot aiding during low-altitude flight depends on the ability to detect and locate obstacles near the helicopter's intended flightpath. Computer-vision-based methods provide one general approach for obstacle detection and range estimation. Several algorithms have been developed for this purpose, but have not been tested with actual flight data. This paper presents results obtained using helicopter flight data with a feature-based range estimation algorithm. A method for recursively estimating range using a Kalman filter with a monocular sequence of images and knowledge of the camera's motion is described. The helicopter flight experiment and one of four resulting datasets is briefly discussed. Finally the performance of the range estimation algorithm is explored based on comparison of the range estimates with true range measurements collected during the flight experiment.

Smith, Phillip N.↗

Vision-based range estimation using helicopter flight data

Pilot aiding during low-altitude flight depends on the ability to detect and locate obstacles near the helicopter's intended flightpath. Computer-vision-based methods provide one general approach for obstacle detection and range estimation. Several algorithms have been developed for this purpose, but have not been tested with actual flight data. This paper presents results obtained using helicopter flight data with a feature-based range estimation algorithm. A method for recursively estimating range using a Kalman filter with a monocular sequence of images and knowledge of the camera's motion is described. The helicopter flight experiment and four resulting datasets are discussed. Finally the performance of the range estimation algorithm is explored in detail based on comparison of the range estimates with true range measurements collected during the flight experiment.

Smith, Phillip N.↗

Flight-path estimation in passive low-altitude flight by visual cues

A series of experiments was conducted, in which subjects had to estimate the flight path while passively being flown in straight or in curved motion over several types of nominally flat, textured terrain. Three computer-generated terrain types were investigated: (1) a random 'pole' field, (2) a flat field consisting of random rectangular patches, and (3) a field of random parallelepipeds. Experimental parameters were the velocity-to-height (V/h) ratio, the viewing distance, and the terrain type. Furthermore, the effect of obscuring parts of the visual field was investigated. Assumptions were made about the basic visual-field information by analyzing the pattern of line-of-sight (LOS) rate vectors in the visual field. The experimental results support these assumptions and show that, for both a straight as well as a curved flight path, the estimation accuracy and estimation times improve with the V/h ratio. Error scores for the curved flight path are found to be about 3 deg in visual angle higher than for the straight flight path, and the sensitivity to the V/h ratio is found to be considerably larger. For the straight motion, the flight path could be estimated successfully from local areas in the far field. Curved flight-path estimates have to rely on the entire LOS rate pattern.

Grunwald, Arthur J.↗

The North Atlantic circulation in the early 1980s - An estimate from inversion of a finite-difference model

A finite-difference model of the North Atlantic is constructed for the purpose of making an estimate of the circulation through an inverse calculation. The data base is eclectic, and includes hydrography, oxygen, nutrients, current meter and float records, atmospheric momentum, heat and water vapor transfers, as well as estimates of certain integral fluxes. Owing to the available hydrographic database, the model resolution is restricted to 1 deg at best, and is much coarser in many aspects. This limited resolution is a major obstacle to accurate estimates of climatological fluxes. In its final form, there are about 9000 constraints in 29,000 formal unknowns plus 9000 noise unknowns. The system is solved as a tapered least-squares system by a sparse conjugate gradient algorithm. With the exception of a few float velocities, all constraints are found to be consistent within error estimates. The model produces estimates of large-scale fluxes and flux divergences for all conventional properties including heat and nutrients as well as carbon dioxide and alkalinity. Meridional fluxes of carbon are found to be indistinguishable from zero, whereas the North Atlantic tends to export nutrients to the south, but carry heat to the north. Traditional oceanographic depictions of the circulation through combination of nonsynoptic data into steady models may have reached their useful limit in the present calculation, as the conflicts between the data and physical requirements become quantitatively apparent.

Martel, Francoise↗

The limit of frequency estimation

In phase and frequency measurements, the measured phase and frequency are not the true phase and frequency but the ones which are disturbed by noises, due to the effects of the noise processes. The effects of three noise processes, i.e., White PM, White FM, and Random Walk FM, on the estimations of phase and frequency is discussed. It is indicated that the properties of these two estimations are very different. In phase estimation, the error can be reduced by properly selecting suitable smoothing length NT and smaple interval T. But in frequency estimation, the error cannot be reduced arbitrarily by means of improving estimator or measurement equipment. The precision of frequency is limited by the intrinsic noises in the clock.

Guo, Wei↗

Technology Benefit Estimator (T/BEST): User's Manual

The Technology Benefit Estimator (T/BEST) system is a formal method to assess advanced technologies and quantify the benefit contributions for prioritization. T/BEST may be used to provide guidelines to identify and prioritize high payoff research areas, help manage research and limited resources, show the link between advanced concepts and the bottom line, i.e., accrued benefit and value, and to communicate credibly the benefits of research. The T/BEST software computer program is specifically designed to estimating benefits, and benefit sensitivities, of introducing new technologies into existing propulsion systems. Key engine cycle, structural, fluid, mission and cost analysis modules are used to provide a framework for interfacing with advanced technologies. An open-ended, modular approach is used to allow for modification and addition of both key and advanced technology modules. T/BEST has a hierarchical framework that yields varying levels of benefit estimation accuracy that are dependent on the degree of input detail available. This hierarchical feature permits rapid estimation of technology benefits even when the technology is at the conceptual stage. As knowledge of the technology details increases the accuracy of the benefit analysis increases. Included in T/BEST's framework are correlations developed from a statistical data base that is relied upon if there is insufficient information given in a particular area, e.g., fuel capacity or aircraft landing weight. Statistical predictions are not required if these data are specified in the mission requirements. The engine cycle, structural fluid, cost, noise, and emissions analyses interact with the default or user material and component libraries to yield estimates of specific global benefits: range, speed, thrust, capacity, component life, noise, emissions, specific fuel consumption, component and engine weights, pre-certification test, mission performance engine cost, direct operating cost, life cycle cost, manufacturing cost, development cost, risk, and development time. Currently, T/BEST operates on stand-alone or networked workstations, and uses a UNIX shell or script to control the operation of interfaced FORTRAN based analyses. T/BEST's interface structure works equally well with non-FORTRAN or mixed software analysis. This interface structure is designed to maintain the integrity of the expert's analyses by interfacing with expert's existing input and output files. Parameter input and output data (e.g., number of blades, hub diameters, etc.) are passed via T/BEST's neutral file, while copious data (e.g., finite element models, profiles, etc.) are passed via file pointers that point to the expert's analyses output files. In order to make the communications between the T/BEST's neutral file and attached analyses codes simple, only two software commands, PUT and GET, are required. This simplicity permits easy access to all input and output variables contained within the neutral file. Both public domain and proprietary analyses codes may be attached with a minimal amount of effort, while maintaining full data and analysis integrity, and security. T/BESt's sotware framework, status, beginner-to-expert operation, interface architecture, analysis module addition, and key analysis modules are discussed. Representative examples of T/BEST benefit analyses are shown.

Generazio, Edward R.↗

On-line, adaptive state estimator for active noise control

Dynamic characteristics of airframe structures are expected to vary as aircraft flight conditions change. Accurate knowledge of the changing dynamic characteristics is crucial to enhancing the performance of the active noise control system using feedback control. This research investigates the development of an adaptive, on-line state estimator using a neural network concept to conduct active noise control. In this research, an algorithm has been developed that can be used to estimate displacement and velocity responses at any locations on the structure from a limited number of acceleration measurements and input force information. The algorithm employs band-pass filters to extract from the measurement signal the frequency contents corresponding to a desired mode. The filtered signal is then used to train a neural network which consists of a linear neuron with three weights. The structure of the neural network is designed as simple as possible to increase the sampling frequency as much as possible. The weights obtained through neural network training are then used to construct the transfer function of a mode in z-domain and to identify modal properties of each mode. By using the identified transfer function and interpolating the mode shape obtained at sensor locations, the displacement and velocity responses are estimated with reasonable accuracy at any locations on the structure. The accuracy of the response estimates depends on the number of modes incorporated in the estimates and the number of sensors employed to conduct mode shape interpolation. Computer simulation demonstrates that the algorithm is capable of adapting to the varying dynamic characteristics of structural properties. Experimental implementation of the algorithm on a DSP (digital signal processing) board for a plate structure is underway. The algorithm is expected to reach the sampling frequency range of about 10 kHz to 20 kHz which needs to be maintained for a typical active noise control application.

Lim, Tae W.↗

Estimation of spectral emissivity in the thermal infrared

A number of algorithms are available in the literature that attempt to remove most of the effects of temperature from thermal multispectral data where the final goal is to extract emissivity differences. Early approaches include adjacent spectral band ratioing, broad band radiance normalization and the use of one band where emissivities are generally high (e.g., 11 to 12 micrometers) to determine the temperature. More recent work has produced two techniques that use data averaging to extract temperature to leave a quantity related to emissivity changes. These two techniques have been investigated and compared and appear to provide reasonable results. The analysis presented in this paper develops a thermal IR multispectral temperature/emissivity estimation procedure based on formal estimation theory, Gaussian statistics, and a stochastic radiance signal model including the effects of both temperature and emissivity. The importance of this work is that this is an optimal estimation procedure which will provide minimum variance estimates of temperature and emissivity changes directly. Section 2 discusses optimal linear spectral emissivity estimation and Section 3 is a summary.

Kryskowski, David↗

An automated method of tuning an attitude estimator

Attitude determination is a major element of the operation and maintenance of a spacecraft. There are several existing methods of determining the attitude of a spacecraft. One of the most commonly used methods utilizes the Kalman filter to estimate the attitude of the spacecraft. Given an accurate model of a system and adequate observations, a Kalman filter can produce accurate estimates of the attitude. If the system model, filter parameters, or observations are inaccurate, the attitude estimates may be degraded. Therefore, it is advantageous to develop a method of automatically tuning the Kalman filter to produce the accurate estimates. In this paper, a three-axis attitude determination Kalman filter, which uses only magnetometer measurements, is developed and tested using real data. The appropriate filter parameters are found via the Process Noise Covariance Estimator (PNCE). The PNCE provides an optimal criterion for determining the best filter parameters.

Mason, Paul A. C.↗