Topic
K-distribution
About: K-distribution is a research topic. Over the lifetime, 1281 publications have been published within this topic receiving 51774 citations.
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07 May 1990
TL;DR: Simple empirical models are described which enable the radar designer to determine single-scan detection probabilities from the signal-to-clutter ratio and false alarm probability, for the compound K-distribution clutter model.
Abstract: Simple empirical models are described which enable the radar designer to determine single-scan detection probabilities from the signal-to-clutter ratio and false alarm probability, for the compound K-distribution clutter model. The method to apply these results is discussed in detail, and the variability of the clutter rejection coefficient is briefly reviewed. Results covering the following are presented: the average clutter reflectivity, the shape parameter for the K-distributed clutter amplitude distribution, detection performance for targets in clutter, and evaluation of performance in clutter and noise. >
10 citations
10 citations
TL;DR: In this article, multichannel synthetic aperture radar (SAR) observations from the spaceborne imaging radar-C/X-band SAR experiment in the NE Atlantic (April 1994) are analyzed to test models of both the mean and the distribution of radar backscatter from the sea surface.
Abstract: Multichannel synthetic aperture radar (SAR) observations from the spaceborne imaging radar-C/X-band SAR (SIR-C/X-SAR) experiment in the NE Atlantic (April 1994) are analyzed to test models of both the mean and the distribution of radar backscatter from the sea surface. The data cover incidence angles from about 20° to 40° and wind speeds from about 5 to 10 m s -1 . Empirical models of the mean fit the data well at C band to an accuracy of within 1-2 dB. Discrepancies at L band are a function of incidence angle, and we cannot rule out the possibility that they arise from systematic calibration errors. Single-look SIR-C/X-SAR data (spatial resolution ∼ 7-10 m) fit well to a K distribution, but multilook data (spatial resolution ∼25 m) fit better to a lognormal distribution. The observed second moments of image intensity can be explained by the modulations of resolved ocean surface waves but only if relatively large hydrodynamic modulations, which are generally consistent with those inferred from tower radar data, are assumed.
10 citations
TL;DR: A family of probability distributions is called factor-closed (f.c.) if it is closed under the operation of factorization as discussed by the authors, and the classical binomial family and certain generalizations of its are shown to be f.c.
Abstract: A family of probability distributions is called "factor-closed" (f.c.) if it is closed under the operation of factorization. The classical binomial family and certain generalizations of its are shown to be f.c. The multinomial family is also f.c. Most families of infinitely divisible distributions are not f.c.
10 citations
DOI•
14 Oct 2015
TL;DR: The authors used the logarithm of maximum likelihood ratio (MLR) as a test for discriminating between inverse Gaussian and gamma distributions for failure time distributions with positively skewed data.
Abstract: One of the problems that appear in reliability and survival analysis is how we choose the best distribution that fitted the data. Sometimes we see that the handle data have two fitted distributions. Both inverse Gaussian and gamma distributions have been used among many well-known failure time distributions with positively skewed data. The problem of selecting between them is considered. We used the logarithm of maximum likelihood ratio as a test for discriminating between these two distributions. The test has been carried out on six different data sets.
10 citations