Non-Gaussian clutter characterization applied to OTHR using a mixture of two Rayleigh probability density functions

Mathematics – Probability

Scientific paper

Rate now

  [ 0.00 ] – not rated yet Voters 0   Comments 0

Details

Scientific paper

A practical technique for characterizing non-Gaussian radar clutter is specified and demonstrated using Over The Horizon Radar (OTHR) data, as an example. The technique employs maximum likelihood to fit the probability density of the clutter amplitude returns to a mixture of two Rayleigh probability densities instead of the single Rayleigh density typically used for Gaussian clutter. This model for non-Gaussian clutter is fully specified for any set of clutter amplitudes by a log likelihood, two Rayleigh parameters, and a mixing coefficient. A 3D plot of these values yields an easily-visualized clutter characterization, as is illustrated using OTHR data. This technique is a demonstration of clutter characterization using OTHR data, but the method can be applied to characterize other types of clutter data.

No associations

LandOfFree

Say what you really think

Search LandOfFree.com for scientists and scientific papers. Rate them and share your experience with other people.

Rating

Non-Gaussian clutter characterization applied to OTHR using a mixture of two Rayleigh probability density functions does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.

If you have personal experience with Non-Gaussian clutter characterization applied to OTHR using a mixture of two Rayleigh probability density functions, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Non-Gaussian clutter characterization applied to OTHR using a mixture of two Rayleigh probability density functions will most certainly appreciate the feedback.

Rate now

     

Profile ID: LFWR-SCP-O-1271233

  Search
All data on this website is collected from public sources. Our data reflects the most accurate information available at the time of publication.