Modified eigenspace projection approach for signal separation

For multiple targets signal separation problem, the separation effect will degrade dramatically with the existence of the signal steering vector error. To solve this problem, a modified eigenspace projection beamforming algorithm (MESB) is proposed and applied in the signal separation issue in this paper. First, a more accurate covariance matrix estimate is obtained based on a shrinkage method according to the MMSE criterion. Then, the signal steering vector is projected onto the signal subspace which is estimated from the eigenvetors of the enhanced covariance matrix, and a calibrated steering vector of the desired signal is obtained corresponding to the signal direction with the biggest projection value. Finally, the robust adaptive beamformer weight is obtained from the estimated covariance matrix and the calibrated steering vector. Simulation results show that compared with traditional methods, the MESB approach has greater output SINR and similarity coefficient, robustness has also been better improved, which could separate the desired target signal more accurately.