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Developing digital computer program for correcting soft parameters of thermal network by Kalman filtering method
A type of weakly stationary noise called herringbone noise was observed in satellite imagery. The characteristics of this noise are described; a model for its simulation was developed. The model is used to degrade pictorial data for comparison with similar noise degraded Nimbus data. Two filtering methods are defined and evaluated. A user's application demonstration is discussed.
The techniques considered are related to gravity profiling from Doppler residuals, a solution for a surface mass distribution, and a dynamical approach for the estimation of random forces at each data point. The dynamical approach makes use of a new filtering method which uses sequential estimation theory to determine unknown and somewhat correlated forces which randomly perturb the orbit. It is concluded that lunar data reduction methods would be suitable for applications in connection with the GEOS-C/ATS-F mission.
A class of algorithms for the multicyclic control of helicopter vibration and loads is derived and discussed. This class is characterized by a linear, quasi-static, frequency-domain model of the helicopter response to control; identification of the helicopter model by least-squared-error or Kalman filter methods; and a minimum variance or quadratic performance function controller. Previous research on such controllers is reviewed. The derivations and discussions cover the helicopter model; the identification problem, including both off-line and on-line (recursive) algorithms; the control problem, including both open-loop and closed-loop feedback; and the various regulator configurations possible within this class. Conclusions from analysis and numerical simulations of the regulators provide guidance in the design and selection of algorithms for further development, including wind tunnel and flight tests.
A adaptive filtering method, the Windrow-Hoff algorithm, for enhancing multichannel signals against aditive noise was investigated. It removes noise for multichannel images containing correlated signal compoments but uncorrelated noise components. Its potential application is the enhancement of multichannel microwave satellite images as a preprocessing step for the extraction of geophysical parameters.
A study is performed under NASA contract to evaluate data from an AN/FPS-16 radar installed for support of flight programs at Dryden Flight Research Facility of NASA Ames Research Center. The purpose of this study is to provide information necessary for improving post-flight data reduction and knowledge of accuracy of derived radar quantities. Tracking data from six flights are analyzed. Noise and bias errors in raw tracking data are determined for each of the flights. A discussion of an altiude bias error during all of the tracking missions is included. This bias error is defined by utilizing pressure altitude measurements made during survey flights. Four separate filtering methods, representative of the most widely used optimal estimation techniques for enhancement of radar tracking data, are analyzed for suitability in processing both real-time and post-mission data. Additional information regarding the radar and its measurements, including typical noise and bias errors in the range and angle measurements, is also presented. This is in two parts. This is part 1, an analysis of radar data.
A study is performed under NASA contract to evaluate data from an AN/FPS-16 radar installed for support of flight programs at Dryden Flight Research Facility of NASA Ames Research Center. The purpose of this study is to provide information necessary for improving post-flight data reduction and knowledge of accuracy of derived radar quantities. Tracking data from six flights are analyzed. Noise and bias errors in raw tracking data are determined for each of the flights. A discussion of an altitude bias error during all of the tracking missions is included. This bias error is defined by utilizing pressure altitude measurements made during survey flights. Four separate filtering methods, representative of the most widely used optimal estimation techniques for enhancement of radar tracking data, are analyzed for suitability in processing both real-time and post-mission data. Additional information regarding the radar and its measurements, including typical noise and bias errors in the range and angle measurements, is also presented. This report is in two parts. This is part 2, a discussion of the modeling of propagation path errors.
A thermographic inspection technique for crack detection based on a 2D filter convolved with the thermal temperature images is presented. The filter is designed to approximate operating on the temperature images with a Laplacian operator. This operation yields an image which approximates changes in the heat flux in a thin plate. This filtering method results in an enhanced contrast due to the presence of cracks. Measurements have been performed on samples with fabricated electrical discharge machining (EDM) notches (both through-the-thickness and surface notches) and closed fatigue cracks around rivets. It is shown that the technique is effective for the detection of various crack lengths down to the resolution limits of the imager used.
Two-dimensional Boussinesq convection is studied numerically using two different methods: a filtered pseudospectral method and a high order accurate Essentially Nonoscillatory (ENO) scheme. The issue whether finite time singularity occurs for initially smooth flows is investigated. The numerical results suggest that the collapse of the bubble cap is unlikely to occur in resolved calculations. The strain rate corresponding to the intensification of the density gradient across the front saturates at the bubble cap. We also found that the cascade of energy to small scales is dominated by the formulation of thin and sharp fronts across which density jumps.
The signal from a stable periodicity can seem to be intermittent when it is partially masked by an unmodelled window function or when the data set is too short to resolve closely spaced periodicities. By taking this into account, short-lived periodicities in solar data can be reinterpreted as evidence for continuously periodic behavior. The periodic sources are located in the solar interior and caused by global oscillation modes. The convective envelope acts as the window for these sources. Recent reports of seven periodicities from 100 to 1000 days are compared with this model. Precise long-term values for the periodicities are predicted and they agree closely with observations. Some elements are suggested that might explain the well-documented 155-day periodicity. Conventional filtering methods to suppress effects of the 11-year cycle are criticized as inadequate.
A potential application of the photorefractive time-integrating correlator is the real-time radar jamming interference rejection system, using the adaptive filter method; a fast photorefractive crystal is needed for adapting a rapidly changing jamming signal. An effort is presently made to demonstrate and characterize a GaAs-based photorefractive time-integrating correlator, since GaAs crystals are 2-3 orders of magnitude faster than most other alternatives.
A real time correlator design based on the principles of Distributed Arithmetic (DA) is described. This design is shown to be more efficient in terms of memory requirement than the direct DA implementation, especially when the number of coefficients is large. Since the proposed architecture implements the sum of product evaluation, it can be easily extended to finite and infinite response filters. Methods to further reduce the memory requirements are also discussed. A brief comparison is made between the proposed method and different DA implementations.
The KB3D algorithm is a pairwise conflict detection and resolution (CD&R) algorithm. It detects and generates trajectory vectoring for an aircraft which has been predicted to be in an airspace minima violation within a given look-ahead time. It has been proven, using mechanized theorem proving techniques, that for a pair of aircraft, KB3D produces at least one vectoring solution and that all solutions produced are correct. Although solutions produced by the algorithm are mathematically correct, they might not be physically executable by an aircraft or might not solve multiple aircraft conflicts. This paper describes a simple solution selection method which assesses all solutions generated by KB3D and determines the solution to be executed. The solution selection method and KB3D are evaluated using a simulation in which N aircraft fly in a free-flight environment and each aircraft in the simulation uses KB3D to maintain separation. Specifically, the solution selection method filters KB3D solutions which are procedurally undesirable or physically not executable and uses a predetermined criteria for selection.
The invention presents The Estimated Spectrum Adaptive Postfilter (ESAP) and the Iterative Prepost Filter (IPF) algorithms. These algorithms model a number of image-adaptive post-filtering and pre-post filtering methods. They are designed to minimize Discrete Cosine Transform (DCT) blocking distortion caused when images are highly compressed with the Joint Photographic Expert Group (JPEG) standard. The ESAP and the IPF techniques of the present invention minimize the mean square error (MSE) to improve the objective and subjective quality of low-bit-rate JPEG gray-scale images while simultaneously enhancing perceptual visual quality with respect to baseline JPEG images.
A simple and fast algorithm for generating two correlated stochastic twodimensional (2D) cloud fields is described. The algorithm is illustrated with two broken cumulus cloud fields: cloud optical depth and cloud top height retrieved from Moderate Resolution Imaging Spectrometer (MODIS). Only two 2D fields are required as an input. The algorithm output is statistical realizations of these two fields with approximately the same correlation and joint distribution functions as the original ones. The major assumption of the algorithm is statistical isotropy of the fields. In contrast to fractals and the Fourier filtering methods frequently used for stochastic cloud modeling, the proposed method is based on spectral models of homogeneous random fields. For keeping the same probability density function as the (first) original field, the method of inverse distribution function is used. When the spatial distribution of the first field has been generated, a realization of the correlated second field is simulated using a conditional distribution matrix. This paper is served as a theoretical justification to the publicly available software that has been recently released by the authors and can be freely downloaded from http://i3rc.gsfc.nasa.gov/Public codes clouds.htm. Though 2D rather than full 3D, stochastic realizations of two correlated cloud fields that mimic statistics of given fields have proved to be very useful to study 3D radiative transfer features of broken cumulus clouds for better understanding of shortwave radiation and interpretation of the remote sensing retrievals.
The subject of magnetohydrodynamic simulations in the 1980's, magnetic turbulence has reemerged as a favored explanation for the production of fast magnetic reconnection. Recent three-dimensional simulations reveal the formation of secondary islands that serve to shorten the current sheet and increase the accelerating electric field, while both simulations and observations witness electron holes whose collapse energizes electrons. However, little work has been done to investigate the presence of turbulent magnetic and electric field spectra in association with in situ reconnection observations in space. In this study we address this deficiency by analyzing the wavelength spectra of two reconnection events established by multiple spacecraft observations in previous publications. We apply a k-filtering analysis to determine the wave vectors. To optimize the quality of the k-filtering analysis and minimize aliasing, we select multi-spacecraft observations having optimal spacecraft tetrahedral geometry and dimensions that resolve wavelengths within the ion diffusion region. We have chosen one dayside and one nightside reconnection event each observed by the Cluster spacecraft. Spatial correlation between the reconnecting current sheet and a turbulent magnetic spectrum supports an association between turbulence and reconnection in space. The k-filtering method, a wavelet time-frequency spectrum, and a polarization analysis serve to identify wave modes associated with the turbulence. A calculation of the reconnection electric field based on the normal component of the reconnecting magnetic field provides an estimate of the reconnection rate.
The goal of this paper is to generalize the well-balanced approach for non-equilibrium flow studied by Wang et al. [26] to a class of low dissipative high order shock-capturing filter schemes and to explore more advantages of well-balanced schemes in reacting flows. The class of filter schemes developed by Yee et al. [30], Sjoegreen & Yee [24] and Yee & Sjoegreen [35] consist of two steps, a full time step of spatially high order non-dissipative base scheme and an adaptive nonlinear filter containing shock-capturing dissipation. A good property of the filter scheme is that the base scheme and the filter are stand alone modules in designing. Therefore, the idea of designing a well-balanced filter scheme is straightforward, i.e., choosing a well-balanced base scheme with a well-balanced filter (both with high order). A typical class of these schemes shown in this paper is the high order central difference schemes/predictor-corrector (PC) schemes with a high order well-balanced WENO filter. The new filter scheme with the well-balanced property will gather the features of both filter methods and well-balanced properties: it can preserve certain steady state solutions exactly; it is able to capture small perturbations, e.g., turbulence fluctuations; it adaptively controls numerical dissipation. Thus it shows high accuracy, efficiency and stability in shock/turbulence interactions. Numerical examples containing 1D and 2D smooth problems, 1D stationary contact discontinuity problem and 1D turbulence/shock interactions are included to verify the improved accuracy, in addition to the well-balanced behavior.
Australia represents a challenging region in which to study hydrological variations as recovered by the GRACE (Gravity Recovery And Climate Experiment) mission data. Much of Australia is characterized by relatively small hydrological signals, with large precipitation gradients between the North and the South. These signals are better recovered using innovative GRACE processing techniques such as high-resolution mascon solutions, which may help overcome the deficiencies in the standard GRACE data processing and filtering methods. We will show the power of using regional and global mas con solutions to recover hydrological variations from 2003 to 2011, as well as the oceanic mass variations in the surrounding regions. We will compare the GRACE signals with state of the art hydrology and ocean general circulation models, precipitation, soil moisture and groundwater data sets. We especially emphasize the gravity signatures observed during the decadal drought in the Murray-Darling river basin and the early 2011 floods in North-Western Australia.