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NASA NTRS1991

Distributed parameter estimation for NASA Mini-Mast truss using Timoshenko beam model

A more accurate Timoshenko beam model is used to characterize the bending behavior of the truss. A maximum likelihood estimator for the Timoshenko beam model has been formulated. A closed-form solution of the Timoshenko beam equation, for a uniform cantilevered beam with two concentrated masses, is derived so that the procedure for the estimation of modal characteristics is much improved. The updated model to the NASA Mini-Mast test data is demonstrated.

Shen, Ji-Yao↗

NASA NTRS1992

Determination of mean rainfall from the Special Sensor Microwave/Imager (SSM/I) using a mixed lognormal distribution

Global estimates of monthly, seasonal, and annual oceanic rainfall are computed for a period of one year using data from the Special Sensor Microwave/Imager (SSM/I). Instantaneous rainfall estimates are derived from brightness temperature values obtained from the satellite data using the Hughes D-matrix algorithm. The instantaneous rainfall estimates are stored in 1 deg square bins over the global oceans for each month. A mixed probability distribution combining a lognormal distribution describing the positive rainfall values and a spike at zero describing the observations indicating no rainfall is used to compute mean values. The resulting data for the period of interest are fitted to a lognormal distribution by using a maximum-likelihood. Mean values are computed for the mixed distribution and qualitative comparisons with published historical results as well as quantitative comparisons with corresponding in situ raingage data are performed.

Berg, Wesley↗

NASA NTRS1992

The density evolution of IRAS galaxies

A maximum likelihood test for density evolution is applied to a full-sky redshift survey of 5297 galaxies selected from the IRAS data base and flux-limited at 1.2 Jy. No evidence for evolution is found. Attention is given to important systematic errors which decrease the certainty with which evolution can be measured, namely, limited knowledge of the cosmological model, the unknown intrinsic spectral energy distribution of IRAS galaxies from 16 to 140 microns, the effect of density fluctuations, a Malmquist-like bias arising from flux errors in the IRAS Point Source Catalog, and possible incompleteness of the sample at high redshifts and low Galactic latitudes. It is shown that the Malmquist bias could result in a significant overestimation of the evolution rate, especially if the catalog has a flux limit near the completion limit of the Point Source Catalog.

Fisher, Karl B.↗

NASA NTRS1992

Bayesian classification of polarimetric SAR images using adaptive a priori probabilities

The problem of classifying earth terrain by observed polarimetric scattering properties is tackled with an iterative Bayesian scheme using a priori probabilities adaptively. The first classification is based on the use of fixed and not necessarily equal a priori probabilities, and successive iterations change the a priori probabilities adaptively. The approach is applied to an SAR image in which a single water body covers 10 percent of the image area. The classification accuracy for ocean, urban, vegetated, and total area increase, and the percentage of reclassified pixels decreases greatly as the iteration number increases. The iterative scheme is found to improve the a posteriori classification accuracy of maximum likelihood classifiers by iteratively using the local homogeneity in polarimetric SAR images. A few iterations can improve the classification accuracy significantly without sacrificing key high-frequency detail or edges in the image.

Van Zyl, J. J.↗

NASA NTRS1991

Improved geometric calibration of the SIR-C data

Errors in the determination of the platform state vector (position and velocity) limit the accuracy with which individual pixels in a SAR (synthetic aperture radar) image can be located. A method of updating the state vector based on the SAR data is described. The algorithm combines reference targets at known locations with the estimates available from the mission control center, utilizing a maximum likelihood estimator. The targets can be located at calibration sites or be easily recognizable targets of opportunity. The accuracy of the update depends on the number of targets, their geometry, and the accuracy of their position determination. The algorithm is tested using Seasat SAR data. High-accuracy state vectors were perturbed by Gaussian distributed errors with standard deviations and cross-correlations based on worst-case expectations for SIR-C (Shuttle Imaging Radar). Tests using ground targets located in topographic maps (1:24,000) showed that state vector position errors on the order of 300-400 m and velocity accuracies of 2-3 m/s are readily achievable.

Madsen, S. N.↗

NASA NTRS1991

A finite mixtures algorithm for finding classes in images

The authors describe an algorithm for estimating the proportions of classes in a SAR (synthetic aperture radar) image without any user interaction. The method assumes that the image is a mixture of a known number of different pixel types. A maximum likelihood estimate of the parameters of the resulting mixture distribution is then used to find the proportions for the various classes. The technique was successfully applied to aircraft SAR images of sea ice. Computer simulations were used to determine the relative errors of the technique. The technique performs well even with extremely noisy images.

Samadani, Ramin↗

NASA NTRS1992

Real-time combining of residual carrier array signals using ML weight estimates

A real-time digital signal combining system for use with array feeds is proposed. The combining system attempts to compensate for signal-to-noise ratio (SNR) loss resulting from antenna deformations induced by gravitational and atmospheric effects. The combining weights are obtained directly from the observed residual carrier samples in each channel using a 'sliding-window' implementation of a maximum-likelihood (ML) parameter estimator. It is shown that with averaging times of about 0.1 s, combining loss for a seven-element array can be limited to about 0.1 dB in a realistic operational environment. This result suggests that the real-time combining system proposed here is capable of recovering virtually all of the signal power captured by the array feed, even in the presence of severe wind gusts and similar disturbances.

Vilnrotter, Victor A.↗

NASA NTRS1992

Top-of-atmosphere radiative fluxes - Validation of ERBE scanner inversion algorithm using Nimbus-7 ERB data

The ERBE algorithm is applied to the Nimbus-7 earth radiation budget (ERB) scanner data for June 1979 to analyze the performance of an inversion method in deriving top-of-atmosphere albedos and longwave radiative fluxes. The performance is assessed by comparing ERBE algorithm results with appropriate results derived using the sorting-by-angular-bins (SAB) method, the ERB MATRIX algorithm, and the 'new-cloud ERB' (NCLE) algorithm. Comparisons are made for top-of-atmosphere albedos, longwave fluxes, viewing zenith-angle dependence of derived albedos and longwave fluxes, and cloud fractional coverage. Using the SAB method as a reference, the rms accuracy of monthly average ERBE-derived results are estimated to be 0.0165 (5.6 W/sq m) for albedos (shortwave fluxes) and 3.0 W/sq m for longwave fluxes. The ERBE-derived results were found to depend systematically on the viewing zenith angle, varying from near nadir to near the limb by about 10 percent for albedos and by 6-7 percent for longwave fluxes. Analyses indicated that the ERBE angular models are the most likely source of the systematic angular dependences. Comparison of the ERBE-derived cloud fractions, based on a maximum-likelihood estimation method, with results from the NCLE showed agreement within about 10 percent.

Suttles, John T.↗

NASA NTRS1993

Constructing An Image From Nonuniform-Scan Data

Algorithm performs maximum-likelihood construction of image of scene scanned nonuniformly by linear array of photodetectors, responses of which unequal. Developed to postprocess data acquired by scanning telescope aboard Infrared Astronomical Satellite (IRAS), also adaptable to generation of high-resolution imagery from data acquired in other nonuniform-scanning applications. Achievable resolution not limited by finite size of detectors, and increases with density of scans. With sufficiently dense scans, one obtains resolution beyond diffraction limit of imaging optics.

Aumann, Hartmut H.↗

NASA NTRS1993

An analytic modeling and system identification study of rotor/fuselage dynamics at hover

A combination of analytic modeling and system identification methods have been used to develop an improved dynamic model describing the response of articulated rotor helicopters to control inputs. A high-order linearized model of coupled rotor/body dynamics including flap and lag degrees of freedom and inflow dynamics with literal coefficients is compared to flight test data from single rotor helicopters in the near hover trim condition. The identification problem was formulated using the maximum likelihood function in the time domain. The dynamic model with literal coefficients was used to generate the model states, and the model was parametrized in terms of physical constants of the aircraft rather than the stability derivatives resulting in a significant reduction in the number of quantities to be identified. The likelihood function was optimized using the genetic algorithm approach. This method proved highly effective in producing an estimated model from flight test data which included coupled fuselage/rotor dynamics. Using this approach it has been shown that blade flexibility is a significant contributing factor to the discrepancies between theory and experiment shown in previous studies. Addition of flexible modes, properly incorporating the constraint due to the lag dampers, results in excellent agreement between flight test and theory, especially in the high frequency range.

Hong, Steven W.↗

NASA NTRS1992

ERS-1 scatterometer calibration and validation activities at ECMWF. B: From radar backscatter characteristics to wind vector solutions

Calibration and validation activities for the ERS-1 scatterometer were carried out at ECMWF (European Center for Medium range Weather Forecast) complementary to the 'Haltenbanken' field campaign off the coast of Norway. At a Numerical Weather Prediction (NWP) center a wealth of verifying data is available both in time and space. This data is used to redefine the wind retrieval procedure given the instrumental characteristics. It was found that a maximum likelihood estimation procedure to obtain the coefficients of a reformulated sigma deg to wind relationship should use radar measurements in logarithmic rather than physical space, and use winds as the wind components rather than wind speed and direction. Doing this, a much more accurate transfer function than the one currently operated by ESA was derived. Sigma deg measurement space shows no signature of a separation in an upwind solution cone and a downwind solution cone. As such signature was anticipated in ESA's wind direction ambiguity removal algorithm, reconsideration of the procedure is necessary. Despite the fact that revisions have to be made in the process of wind retrieval; a grid potential is shown for scatterometry in meteorology and climatology.

Stoffelen, AD↗

NASA NTRS1993

The probabilistic neural network architecture for high speed classification of remotely sensed imagery

In this paper we discuss a neural network architecture (the Probabilistic Neural Net or the PNN) that, to the best of our knowledge, has not previously been applied to remotely sensed data. The PNN is a supervised non-parametric classification algorithm as opposed to the Gaussian maximum likelihood classifier (GMLC). The PNN works by fitting a Gaussian kernel to each training point. The width of the Gaussian is controlled by a tuning parameter called the window width. If very small widths are used, the method is equivalent to the nearest neighbor method. For large windows, the PNN behaves like the GMLC. The basic implementation of the PNN requires no training time at all. In this respect it is far better than the commonly used backpropagation neural network which can be shown to take O(N6) time for training where N is the dimensionality of the input vector. In addition the PNN can be implemented in a feed forward mode in hardware. The disadvantage of the PNN is that it requires all the training data to be stored. Some solutions to this problem are discussed in the paper. Finally, we discuss the accuracy of the PNN with respect to the GMLC and the backpropagation neural network (BPNN). The PNN is shown to be better than GMLC and not as good as the BPNN with regards to classification accuracy.

Chettri, Samir R.↗

NASA NTRS1993

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.↗

NASA NTRS1993

Combinatorial pulse position modulation for power-efficient free-space laser communications

A new modulation technique called combinatorial pulse position modulation (CPPM) is presented as a power-efficient alternative to quaternary pulse position modulation (QPPM) for direct-detection, free-space laser communications. The special case of 16C4PPM is compared to QPPM in terms of data throughput and bit error rate (BER) performance for similar laser power and pulse duty cycle requirements. The increased throughput from CPPM enables the use of forward error corrective (FEC) encoding for a net decrease in the amount of laser power required for a given data throughput compared to uncoded QPPM. A specific, practical case of coded CPPM is shown to reduce the amount of power required to transmit and receive a given data sequence by at least 4.7 dB. Hardware techniques for maximum likelihood detection and symbol timing recovery are presented.

Budinger, James M.↗

NASA NTRS1991

Distributed parameter estimation for NASA Mini-Mast truss through displacement measurements

Most methods of system identification of large flexible structures by far are based on the lumped parameter approach. Because of the considerable computational burden due to the large number of unknown parameters, distributed parameter approach, which greatly decreases the number of unknowns, has being investigated. In this paper a distributed parameter model for the estimation of modal characteristics of NASA Mini-Mast truss has been formulated. Both Bernoulli-Euler beam and Timoshenko beam equations are used to characterize the lateral bending vibrations of the truss. The measurement of the lateral displacement at the tip of the truss is provided to the maximum likelihood estimator. Closed-form solutions of the partial differential equations and closed-form expressions of the sensitivity functions are derived so that the estimation algorithm is highly efficient. The resulting estimates from test data by using Timoshenko beam model are found to be comparable to those derived from finite element analysis.

Huang, Jen-Kuang↗

NASA NTRS1991

High-speed laser anemometry based on spectrally resolved Rayleigh scattering

Laser anemometry in unseeded flows based on the measurement of the spectrum of Rayleigh scattered laser light is reviewed. The use of molecular scattering avoids the well-known problems (particle lag, biasing effects, seed generation, seed injection) of seeded flows. The fundamental limits on velocity measurement accuracy are determined using maximum likelihood methods. Measurement of the Rayleigh spectrum with scanning Fabry-Perot interferometers is analyzed and accuracy limits are established for both single pass and multi-pass configurations. Multi-pass configurations have much higher selectivity and are needed for measurements where there is a large amount of excess noise caused by stray laser light. It is shown that Rayleigh scattering is particularly useful for supersonic and hypersonic flows. The results of the analysis are compared with measurements obtained with a Rayleigh scattering diagnostic developed for study of the exhaust plume of a small hydrogen-oxygen rocket, where the velocities are in the range 1000 to 5000 m/sec.

Seasholtz, R. G.↗

NASA NTRS1991

Signal processing considerations for low signal to noise ratio laser Doppler and phase Doppler signals

The relative performance of current methods used for estimating the phase and the frequency in LDV and phase Doppler applications in low signal to noise ratio conditions is analyzed. These methods include the Fourier analysis and the correlation techniques. Three methods that use the correlation function for frequency and phase estimations are evaluated in terms of accuracy and speed of processing. These methods include: (1) the frequency estimation using zero crossings counting of the auto-correlation function, (2) the Blackman-Tukey method, and (3) the AutoRegressive method (AR). The relative performance of these methods is evaluated and compared with the Fourier analysis method which provides the optimum performance in terms of the Maximum Likelihood (ML) criteria.

Ibrahim, K. M.↗

NASA NTRS1992

X-ray emission at low-mass end of the MS - Results from an extensive Einstein Observatory survey

The 0.16-4.0 keV X-ray emission from K and M stars of luminosity classes IV, V, and VI within 25 parsec of the sun was measured using all available Einstein Observatory IPC data and a critical compilation of catalogued optical data. Fifty four of 88 stars were detected, 70 of 138 M stars with Mv less than 13.4 (corresponding to M6) and 15 or 31 fainter M stars. The surveyed stars were grouped, on the basis of U, V, W space velocity components, into old-disk, young-disk, and halo population stars. Then, a subsample was selected which is statistically representative of the population of K and M stars in the solar neighborhood, on the basis of which unbiased Maximum Likelihood X-ray luminosity functions were constructed for K, early M, and late M stars. The investigation revealed a decrease of X-ray luminosity with increasing stellar age in the range of ages of disk population stars.

Barbera, M.↗