Generalized Sidelobe Canceller for Ultrasound Imaging based on Eigenvalue Decomposition

Abstract

The improved generalized sidelobe canceller (GSC) based on eigenvalue decomposition beamforming technique for ultrasound imaging is proposed. Firstly, the signal subspace is obtained by performing eigenvalue decomposition on the covariance matrix of received data. Secondly, the weighting vector of GSC is divided into adaptive and non-adaptive two parts. Then the non-adaptive part is projected into the signal subspace to obtain a new steer vector. Subsequently, based on the orthogonal complementary space of the new steer vector, the blocking matrix is constructed. Finally, the weighting vector is updated by projecting the final weighting vector into the signal subspace. In order to verify the proposed algorithm, the simulations of the point targets and the cyst phantom were conducted in Field II. The experimental results indicate that the proposed method has better resolution and contrast ratio than the conventional algorithms. In addition, the algorithm is robust to noises. Furthermore, combining with coherence factor, the contrast ratio of the proposed algorithm can be further improved in comparison with a conventional GSC with coherence factor.