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Toeplitz Structured Covariance Matrix Estimation for Radar Applications
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DOI：10.1109/LSP.2020.2984431.png)
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摘要
En 中文
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.
Keyword:
Covariance matrices
Estimation
Radar
Jamming
Interference
Optimization
Linear matrix inequalities
Radar signal processing
covariance matrix estimation
projection
Toeplitz structure
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9.6
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1.1W
被引数:
1.7W
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