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Toeplitz Structured Covariance Matrix Estimation for Radar Applications
- Source :
- SAM
- Publication Year :
- 2020
- Publisher :
- Institute of Electrical and Electronics Engineers (IEEE), 2020.
-
Abstract
- Following a geometric paradigm, the estimation of a Toeplitz structured covariance matrix is considered. The estimator minimizes the distance from the Sample Covariance Matrix (SCM) while complying with some specific constraints modeling the covariance structure. The resulting constrained optimization problem is solved globally resorting to the Dykstra’ projection framework. Each step of the procedure involves the solution of two convex sub-problems, whose minimizers are available in closed form. Simulation results related to typical radar environments highlight the effectiveness of the devised method.
- Subjects :
- 020301 aerospace & aeronautics
Computer science
Covariance matrix
Applied Mathematics
Regular polygon
MathematicsofComputing_NUMERICALANALYSIS
Structure (category theory)
Estimator
020206 networking & telecommunications
02 engineering and technology
Covariance
Sample mean and sample covariance
Projection (linear algebra)
Toeplitz matrix
law.invention
0203 mechanical engineering
law
Signal Processing
0202 electrical engineering, electronic engineering, information engineering
Electrical and Electronic Engineering
Radar
Algorithm
Subjects
Details
- ISSN :
- 15582361 and 10709908
- Volume :
- 27
- Database :
- OpenAIRE
- Journal :
- IEEE Signal Processing Letters
- Accession number :
- edsair.doi.dedup.....aa58ec74667594797c8d98ccc16ab1b0
- Full Text :
- https://doi.org/10.1109/lsp.2020.2984431