Decorrelation and Decoupling of Coherent Signals in the Presence of Mutual Coupling Using Single Snapshot

The performance of subspace estimation algorithms degrades substantially in the presence of mutual coupling and coherent environments by the perturbance of steering matrix and the rank defect of covariance matrix. In order to settle these issues, a novel modified single snapshot algorithm for decorrelation and decoupling using only single snapshot is proposed. The algorithm utilizes single snapshot to constitute equivalent receiving data covariance matrix, the mutual coupling cofficients can be isolated from steering matrix and be absorbed into equivalent signal covariance matrix by decomposing the equivalent receiving data covariance matrix, so the decoupling is accomplished. Equivalent signal covariance matrix is a diagonal matrix, and its diagonal elements are unrelated to the correlation of signals, so the decorrelation is accomplished. The simulation results show that the proposed algorithm can restrain mutual coupling and be applied to high calculation speed scenarios. The performance of the algorithm is equivalent to the performance of the algorithm without mutual coupling.