Covariance matrix estimation for CFAR detection in correlated heavy tailed clutter
By Fulvio Gini, Maria Sabrina Greco. Signal Processing, 2002
405 citations recorded by the source corpus.
Subfields: Aerospace Engineering, Artificial Intelligence
View Paper: https://www.semanticscholar.org/paper/2db1f33c4408d56f8ae066ee40974fa03594f7e9
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In Aerospace Engineering
- M. Rangaswamy
- Pietro Stinco
- Maria Sabrina Greco
- Fulvio Gini
- Jun Shi
- H. Vincent Poor
- Visa Koivunen
- Shunjun Wei
In Artificial Intelligence
Citations in the corpus
- HRSID: A High-Resolution SAR Images Dataset for Ship Detection and Instance Segmentation (2020, methodology): “For specific needs, CFAR detection has been incorporated with diverse modules to improve detection precision [13]–[17].”
- Impact of Sea Clutter Nonstationarity on Disturbance Covariance Matrix Estimation and CFAR Detector Performance (2010, methodology): “Note that zi M zi=N represents the ML estimate of the texture when M is known [11].”
- Covariance Structure Maximum-Likelihood Estimates in Compound Gaussian Noise: Existence and Algorithm Analysis (2008, methodology): “derived in [12] an AML estimate as the solution of the following:”
- Complex Elliptically Symmetric Distributions: Survey, New Results and Applications (2012, background): “The above MLE was also derived in [33] and also recently studied [17] and [78].”