We analyze convergence properties of the parallel classical block Jacobi method for the symmetric eigenvalue problem using dynamic ordering strategy of Bečka et al. It is shown that the method is globally convergent. It is also shown that the order of convergence is ultimately quadratic if there are no multiple eigenvalues.

We consider estimating the direction of arrival (DOA) in the presence of sensor array error. In the proposed method, a blind signal separation method, the Joint Approximation and Diagonalization of Eigenmatrices (JADE) algorithm, is implemented to separate the signal vector and the mixing matrix consisting of the array manifold matrix and the sensor array error matrix. Based on a new mixing matrix and the reconstruction of the array output vector of each individual signal, we propose a novel DOA estimation method and sensor array error calibration procedure. This method is independent of array phase errors and performs well against

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