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Full-Text Articles in Engineering
Spaceborne Radar Measurement Of Wind Velocity Over The Ocean-An Overview Of The Nscat Scatterometer System, David G. Long, F. M. Naderi, Michael H. Freilich
Spaceborne Radar Measurement Of Wind Velocity Over The Ocean-An Overview Of The Nscat Scatterometer System, David G. Long, F. M. Naderi, Michael H. Freilich
Faculty Publications
Scatterometry and scatterometer design issues are reviewed. The design of the NASA Scatterometer (NSCAT) to be flown on the Japanese ADEOS mission is presented. Building on Seasat experience, the NSCAT system includes several enhancements, such as three antenna azimuths in each of two swaths, and an onboard digital Doppler processor to allow backscatter measurements to be colocated everywhere within the orbit. These enhancements will greatly increase the quality of the NSCAT wind data. The ground processing of data is discussed, and scatterometers of the next decade are briefly described.
Identifiability In Wind Estimation From Scatterometer Measurements, David G. Long, Jerry M. Mendel
Identifiability In Wind Estimation From Scatterometer Measurements, David G. Long, Jerry M. Mendel
Faculty Publications
The problem of identifiability of a wind vector that is estimated from wind scatterometer measurements of the radar backscatter of the ocean's surface is addressed. The traditional wind estimation approach produces multiple estimates of the wind direction. A second processing step, known as dealiasing or ambiguity removal, is used to select a single wind estimate from these multiple solutions. Dealiasing is typically based on various ad hoc considerations. The traditional wind estimation approach results in multiple solutions associated with local minima in an objective function formed from the noisy backscatter measurements. The authors discuss the question of the uniqueness of …
Convex Bayes Decision Theory, Wynn C. Stirling, Darryl Morrell
Convex Bayes Decision Theory, Wynn C. Stirling, Darryl Morrell
Faculty Publications
The basic concepts of Levi's epistemic utility theory and credal convexity are presented. Epistemic utility, in addition to penalizing error as is done with traditional Bayesian decision methodology, permits a unit of informational value to be distributed among the hypotheses of a decision problem. Convex Bayes decision theory retains the conditioning structure of probability-based inference, but addresses many of the objections to Bayesian inference through relaxation of the requirement for numerically definite probabilities. The result is a decision methodology that stresses avoiding errors and seeks decisions that are likely to be highly informative as well as true. By relaxing the …
Set-Valued Filtering And Smoothing, Wynn C. Stirling, Darryl Morrell
Set-Valued Filtering And Smoothing, Wynn C. Stirling, Darryl Morrell
Faculty Publications
A theory of discrete-time optimal filtering and smoothing based on convex sets of probability distributions is presented. Rather than propagating a single conditional distribution as does conventional Bayesian estimation, a convex set of conditional distributions is evolved. For linear Gaussian systems, the convex set can be generated by a set of Gaussian distributions with equal covariance with means in a convex region of state space. The conventional point-valued Kalman filter is generated to a set-valued Kalman filter consisting of equations of evolution of a convex set of conditional means and a conditional covariance. The resulting estimator is an exact solution …
A Median-Filter-Based Ambiguity Removal Algorithm For Nscat, David G. Long, Scott J. Shaffer, R. Scott Dunbar, S. Vincent Hsiao
A Median-Filter-Based Ambiguity Removal Algorithm For Nscat, David G. Long, Scott J. Shaffer, R. Scott Dunbar, S. Vincent Hsiao
Faculty Publications
A description is given of the baseline NSCAT (the NASA scatterometer) ambiguity removal algorithm and the method used to select the set of optimum parameter values. An extensive simulation of the NSCAT instrument and ground data processor provides a means of testing the resulting tuned algorithm. This simulation generates the ambiguous wind-field vectors expected from the instrument as it orbits over a set of realistic mesoscale wind fields. The ambiguous wind field is then de-aliased using the median-filter-based ambiguity removal algorithm. Performance is measured by comparison of the selected wind fields with the true wind fields. Results have shown that …