SERCOM applies the Jensen-Bregman LogDet divergence on the Riemannian manifold of Hermitian positive definite matrices to achieve more robust and accurate direction-of-arrival and power estimation than conventional Euclidean covariance matching methods.
A new metric on the manifold of kernel matrices with ap- plication to matrix geometric means
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Spatial Power Estimation via Riemannian Covariance Matching
SERCOM applies the Jensen-Bregman LogDet divergence on the Riemannian manifold of Hermitian positive definite matrices to achieve more robust and accurate direction-of-arrival and power estimation than conventional Euclidean covariance matching methods.