Learning strategies for radar clutter classification
P Addabbo, S Han, D Orlando… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
In this paper, we address the problem of classifying clutter returns into statistically
homogeneous subsets. The classification procedures are devised assuming latent …
homogeneous subsets. The classification procedures are devised assuming latent …
A robust direction-of-arrival estimation method for impulsive noise environments
M Wang, DZ Feng, MH Chen, TT Su, XJ Zhang - Signal Processing, 2023 - Elsevier
The performance of conventional direction-of-arrival (DOA) estimation methods degrades
greatly when there are few snapshots and the noise model is mismatched, especially in …
greatly when there are few snapshots and the noise model is mismatched, especially in …
Highly robust complex covariance estimators with applications to sensor array processing
JA Fishbone, L Mili - IEEE Open Journal of Signal Processing, 2023 - ieeexplore.ieee.org
Many applications in signal processing require the estimation of mean and covariance
matrices of multivariate complex-valued data. Often, the data are non-Gaussian and are …
matrices of multivariate complex-valued data. Often, the data are non-Gaussian and are …
Riemannian optimization for non-centered mixture of scaled Gaussian distributions
This article studies the statistical model of the non-centered mixture of scaled Gaussian
distributions (NC-MSG). Using the Fisher-Rao information geometry associated with this …
distributions (NC-MSG). Using the Fisher-Rao information geometry associated with this …
Matched and mismatched estimation of kronecker product of linearly structured scatter matrices under elliptical distributions
The estimation of covariance matrices is a core problem in many modern adaptive signal
processing applications. For matrix-and array-valued data, eg, MIMO communication …
processing applications. For matrix-and array-valued data, eg, MIMO communication …
The Fisher–Rao Geometry of CES Distributions
When dealing with a parametric statistical model, a Riemannian manifold can naturally
appear by endowing the parameter space with the Fisher information metric. The geometry …
appear by endowing the parameter space with the Fisher information metric. The geometry …
New highly efficient high‐breakdown estimator of multivariate scatter and location for elliptical distributions
J Fishbone, L Mili - Canadian Journal of Statistics, 2024 - Wiley Online Library
High‐breakdown‐point estimators of multivariate location and shape matrices, such as the
MM‐estimator with smoothed hard rejection and the Rocke S‐estimator, are generally …
MM‐estimator with smoothed hard rejection and the Rocke S‐estimator, are generally …
A Tyler-type estimator of location and scatter leveraging Riemannian optimization
We consider the problem of jointly estimating the location and scatter matrix of a Compound
Gaussian distribution with unknown deterministic texture parameters. When the location is …
Gaussian distribution with unknown deterministic texture parameters. When the location is …
Contributions aux méthodes de calibration et d'imagerie pour les radio-interféromètres en présence d'interférences
Y Mhiri - 2023 - theses.hal.science
Les radiotélescopes interféromètres permettent de reconstruire des images des émissions
radio provenant de sources célestes. Ces images sont d'un grand intérêt pour les …
radio provenant de sources célestes. Ces images sont d'un grand intérêt pour les …
[PDF][PDF] Highly robust and efficient estimators of multivariate location and covariance with applications to array processing and financial portfolio optimization
JA Fishbone - 2021 - vtechworks.lib.vt.edu
Throughout stochastic data processing fields, mean and covariance matrices are commonly
employed for purposes such as standardizing multivariate data through decorrelation. For …
employed for purposes such as standardizing multivariate data through decorrelation. For …