Study on ES-DOA Estimation Algorithm of Minimum-Redundancy Linear Arrays

Arrays aperture can be improved greatly with minimum-redundancy linear arrays(MRLA). But MRLA’s covariance matrix is not a Toeplitz matrix, which makes spatial smoothing decorrelation method and etc futile to constrain MRLA’s applications in correlated circumstances. Eigenspace-DOA (ESDOA) algorithm, uniting the estimation of signals’ powers, can produce high resolutions of DOA estimation with a lower SNR. ES-DOA algorithm, utilizing forward-back technique meanwhile, does no harm to arrays’ aperture. ES-DOA algorithm in MRLA has improved MRLA’s DOA estimation capability without impairing its aperture. Simulation results have also shown its high precision and robustness.