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At least 91 records · Page 5

An integrated LANDSAT/ancillary data classification of desert rangeland

Range inventorying methods using LANDSAT MSS data, coupled with ancillary data were examined. The study area encompassed nearly 20,000 acres in Rush Valley, Utah. The vegetation is predominately desert shrub and annual grasses, with some annual forbs. Three LANDSAT scenes were evaluated using a Kauth-Thomas brightness/greenness data transformation (May, June, and August dates). The data was classified using a four-band maximum-likelihood classifier. A print map was taken into the field to determine the relationship between print symbols and vegetation. It was determined that classification confusion could be greatly reduced by incorporating geomorphic units and soil texture (coarse vs fine) into the classification. Spectral data, geomorphic units, and soil texture were combined in a GIS format to produce a final vegetation map identifying 12 vegetation types.

Price, K. P.

Spaceborne SAR data for land-cover classification and change detection

Supervised maximum-likelihood classifications of Seasat, SIR-A, and Landsat pixel data demonstrated that SIR-A data provided the most accurate discrimination (72 percent) between five land-cover categories. Spatial averaging of the SAR data improved classification accuracy significantly due to a reduction in both fading and within-field variability. The best multichannel classification accuracy (97.5 percent) was achieved by combining the SIR-A data with two Seasat images (ascending and descending orbits). In addition, semiquantitative analysis of Seasat-A digital data shows that orbital SAR imagery can be successfully used for multitemporal detection of change related to hydrologic and agronomic conditions by using simple machine processing techniques.

Brisco, B.

Time-resolved speckle effects on the estimation of laser-pulse arrival times

A maximum-likelihood (ML) estimator of the pulse arrival in laser ranging and altimetry is derived for the case of a pulse distorted by shot noise and time-resolved speckle. The performance of the estimator is evaluated for pulse reflections from flat diffuse targets and compared with the performance of a suboptimal centroid estimator and a suboptimal Bar-David ML estimator derived under the assumption of no speckle. In the large-signal limit the accuracy of the estimator was found to improve as the width of the receiver observational interval increases. The timing performance of the estimator is expected to be highly sensitive to background noise when the received pulse energy is high and the receiver observational interval is large. Finally, in the speckle-limited regime the ML estimator performs considerably better than the suboptimal estimators.

Tsai, B.-M.

Einstein X-ray survey of the Pleiades - The dependence of X-ray emission on stellar age

The data obtained with two pointed observations of 1 deg by 1 deg fields of the Pleiades region have been analyzed, and the results are presented. The maximum-likelihood X-ray luminosity functions for the Pleiades G and K stars in the cluster are derived, and it is shown that, for the G stars, the Pleiades X-ray luminosity function is significantly brighter than the corresponding function for Hyades G dwarf stars. This finding indicates a dependence of X-ray luminosity on stellar age, which is confirmed by comparison of the same data with median X-ray luminosities of pre-main sequence and local disk population dwarf G stars. It is suggested that the significantly larger number of bright X-ray sources associated with G stars than with K stars, the lack of detection of M stars, and the relatively rapid rotation of the Pleiades K stars can be explained in terms of the onset of internal differential rotation near the convective envelope-radidative core interface after the spin-up phase during evolution to the main sequence.

Micela, G.

Statistical methods for astronomical data with upper limits. I - Univariate distributions

The statistical treatment of univariate censored data is discussed. A heuristic derivation of the Kaplan-Meier maximum-likelihood estimator from first principles is presented which results in an expression amenable to analytic error analysis. Methods for comparing two or more censored samples are given along with simple computational examples, stressing the fact that most astronomical problems involve upper limits while the standard mathematical methods require lower limits. The application of univariate survival analysis to six data sets in the recent astrophysical literature is described, and various aspects of the use of survival analysis in astronomy, such as the limitations of various two-sample tests and the role of parametric modelling, are discussed.

Feigelson, E. D.

Estimation of the differential pulse propagation times in two-color laser ranging systems

Two-color laser ranging systems can be used to determine the atmospheric delay by measuring the difference in propagation times between two optical pulses transmitted at two different wavelengths. In this paper, the performance of a cross-correlation technique for estimating the differential propagation time is analyzed by considering both speckle and shot noise. For the flat diffuse targets, the differential timing accuracy is highly dependent on the receiver bandwidth and the characteristics of the time-resolved speckle. At low signal levels, when the receiver bandwidth is chosen properly, the performance of the correlation estimator is comparable with that of the maximum-likelihood estimator. At high signal levels, however, speckle places a fundamental limit on the performance of the correlation estimator. For the cube-corner reflector arrays, timing performance is dominated by partially developed speckle. The differential propagation time cannot by resolved to better than the pulse widths of the received signals.

Im, K. E.

Modeling, estimation and identification methods for static shape determination of flexible structures

This paper outlines methods for modeling, identification and estimation for static determination of flexible structures. The shape estimation schemes are based on structural models specified by (possibly interconnected) elliptic partial differential equations. The identification techniques provide approximate knowledge of parameters in elliptic systems. The techniques are based on the method of maximum-likelihood that finds parameter values such that the likelihood functional associated with the system model is maximized. The estimation methods are obtained by means of a function-space approach that seeks to obtain the conditional mean of the state given the data and a white noise characterization of model errors. The solutions are obtained in a batch-processing mode in which all the data is processed simultaneously. After methods for computing the optimal estimates are developed, an analysis of the second-order statistics of the estimates and of the related estimation error is conducted. In addition to outlining the above theoretical results, the paper presents typical flexible structure simulations illustrating performance of the shape determination methods.

Rodriguez, G.

An integrated Landsat/ancillary data classification of desert rangeland

Range inventorying methods using Landsat MSS data, coupled with ancillary data were examined. The study area encompassed nearly 20,000 acres in Rush Valley, UT. The vegetation is predominately desert shrub and annual grasses, with same annual forbs. Three Landsat scenes were evaluated using a Kauth-Thomas brightness/greenness data transformation (May, June, and August dates). The data was classified using a four-band maximum-likelihood classifier. A print map was taken into the field to determine the relationship between print symbols and vegetation. It was determined that classification confusion could be greatly reduced by incorporating geomorphic units and soil texture (coarse vs fine) into the classification. Spectral data, geomorphic units, and soil texture were combined in a GIS format to produce a final vegetation map identifying 12 vegetation types.

Price, K. P.

On the synchronizability and detectability of random PPM sequences

The problem of synchronization and detection of random pulse-position-modulation (PPM) sequences is investigated under the assumption of perfect slot synchronization. Maximum-likelihood PPM symbol synchronization and receiver algorithms are derived that make decisions based both on soft as well as hard data; these algorithms are seen to be easily implementable. Bounds derived on the symbol error probability as well as the probability of false synchronization indicate the existence of a rather severe performance floor, which can easily be the limiting factor in the overall system performance. The performance floor is inherent in the PPM format and random data and becomes more serious as the PPM alphabet size Q is increased. A way to eliminate the performance floor is suggested by inserting special PPM symbols in the random data stream.

Georghiades, Costas N.

Image statistics decoding for convolutional codes

It is a fact that adjacent pixels in a Voyager image are very similar in grey level. This fact can be used in conjunction with the Maximum-Likelihood Convolutional Decoder (MCD) to decrease the error rate when decoding a picture from Voyager. Implementing this idea would require no changes in the Voyager spacecraft and could be used as a backup to the current system without too much expenditure, so the feasibility of it and the possible gains for Voyager were investigated. Simulations have shown that the gain could be as much as 2 dB at certain error rates, and experiments with real data inspired new ideas on ways to get the most information possible out of the received symbol stream.

Pitt, G. H., III

A structural-stochastic model for the analysis and synthesis of cloud images

A structural-stochastic image model is developed for the analysis and synthesis of cloud images. The ability of the model to characterize the visual appearance of cloud fields observed by satellite with a limited number of parameters is demonstrated. The model merges structural and stochastic information, the stochastic model acting as a local statistical operator applied to the output of the structural model. The structural or large-scale organization of the scene is retrieved from the two-dimensional Fourier representation of the digital image. The pattern generated by the major Fourier components provides a first guess of the scene. The stochastic aspect is described by a Markov model of texture that assumes a binomial probability distribution for the local grey-level variability. This Markov model provides four parameters that represent the clustering strength in the horizontal, vertical and diagonal directions. These parameters are estimated by a standard maximum-likelihood technique. The image can be reproduced with a fair degree of verisimilitude from these parameters. The data compression factor is of the order of one hundred to several hundreds.

Garand, L.

Estimating the arrival times of photon-limited laser pulses in the presence of shot and speckle noise

Maximum-likelihood (ML) receivers are frequently used to optimize the timing performance of laser-ranging and laser-altimetry systems in the presence of shot and speckle noise. Monte Carlo method was used to examine ML-receiver performance with return signals in the 10-5000-photoelectron (pe) range. The simulations were performed for shot noise only and for shot and speckle noise. The results agree with previous theory for signal strengths greater than about 100 pe's but show that the theory can significantly underestimate timing errors for weaker received signals. Sharp high-bandwidth features in the detected signals are shown to improve timing performance only if their signal levels are greater than 4-5 pe's.

Abshire, James B.

A comparative study of several wind estimation algorithms for spaceborne scatterometers

The paper presents a comparison study for the performances of seven wind estimation algorithms for spaceborne scatterometers. These algorithms are weighted least square in log domain, maximum-likelihood, least square weighted least square, adjustable weighted least square, L1 norm, and least wind speed square algorithms using radar scatterometer measurements. For each algorithm, the system performance simulation results are presented for the NASA scatterometer system planned to be launched in the 1990's.

Chi, Chong-Yung

Systematic properties of CO emission from galaxies. I - Luminosity function

A sensitive survey of normal galaxies covering a wide range of luminosities and morphological types is combined with galaxy observations in the literature to provide a sample for statistical study. The global CO emission of these galaxies is extrapolated by modeling the galaxies with an exponential radial profile. The maximum-likelihood distribution functions of CO luminosity and CO/H I flux ratio are similar in behavior. Both have long tails of bright galaxies. However, the typical galaxy has a CO luminosity of about 10 to the 6th Jy km/s Mpc-squared or less and a CO/H I ratio of the order of 10 or less. Averages of the distributions of CO luminosity and CO/H I flux ratio are higher for galaxies of Hubble type Sb-Sbc than for groups of earlier or later types. Quantitative estimates of the possible error sources in the conversion of CO luminosity to molecular mass indicates that the peaking of CO emission at intermediate types is a fairly confident result.

Verter, Frances

Narrow-angle tail radio sources and evidence for radial orbits in Abell clusters

Published observational data on the tail orientations (TOs) of 60 narrow-angle-tail (NAT) radio sources in Abell clusters of galaxies are analyzed statistically using a maximum-likelihood approach. The results are presented in a table, and it is found that the observed TO distributions in the whole sample and in subsamples of morphologically regular NATs and NATs with pericentric distances d greater than 500 kpc are consistent with isotropic orbits, whereas the TOs for NATs with d less than 500 kpc are consistent with highly radial orbits. If radial orbits were observed near the centers of other types of cluster galaxies as well, it could be inferred that violent relaxation during cluster formation was incomplete, and that clusters form by spherical collapse and secondary infall, as proposed by Gunn (1977).

O'Dea, Christopher P.

Bit error probability calculations for convolutional codes with short constraint lengths on very noisy channels

A technique for estimating convolutional code performance on very noisy channels is considered. Specifically, the performance of short constraint length codes operating near the channel cutoff rate is estimated. Decoding convolutional codes with a sliding window decoder (SWD) are considered. This decoder is an optimal (maximum likelihood) symbol decoder as the window size grows toward infinity, while the Viterbi decoder is the maximum-likelihood sequence estimator. The difference in the decoded BERs (bit error rates) between the two decoders is very small and approaches zero asymptotically as the channel BER decreases. Therefore, an estimate on the decoded BER for the SWD can also be used as an estimate of the decoded BER for Viterbi decoding.

Herro, Mark A.

Statistics of Sxy estimates

The statistics of Sxy estimates derived from orthogonal-component measurements are examined. Based on results of Goodman (1957), the probability density function (pdf) for Sxy(f) estimates is derived, and a closed-form solution for arbitrary moments of the distribution is obtained. Characteristic functions are used to derive the exact pdf of Sxy(tot). In practice, a simple Gaussian approximation is found to be highly accurate even for relatively few degrees of freedom. Implications for experiment design are discussed, and a maximum-likelihood estimator for a posterior estimation is outlined.

Freilich, M. H.

Bounds of the bit error probability of a linear cyclic code over GF(2 exp l) and its extended code

An upper bound on the bit-error probability (BEP) of a linear cyclic code over GF(2 exp l) with hard-decision (HD) maximum-likelihood (ML) decoding on memoryless symmetric channels is derived. Performance results are presented for Reed-Solomon codes on GF(32), GF(64), and GF(128). Also, a union upper bound on the BEP of a linear cyclic code with either HD or soft-decision (SD) ML decoding is developed, as well as the corresponding bounds for the extended code of a linear cyclic code. Using these bounds, which are tight at low bit error rate, the performance advantage of SD and HD ML over bounded-distance decoding is established.

Cheng, Unjeng