earticle

영어

Subspace partition is a common method in normal MUSIC algorithm that divides the signal covariance matrix into signal subspace and noise subspace by eigenvalue decomposition. By this method, the effect of environmental noise is curbed. However, when the signal angle interval becomes small and the signal-noise ratio reduces, some certain limitations in multiple signal estimation such as loss and confusion will be presented, which means the normal method of estimation is unable to distinguish those signals we need actually. A modified MUSIC algorithm is proposed in this paper to solve the problem. A modified part in the spatial spectrum called weighting function is introduced. Some weighted operation are given to the steering vectors when the spatial spectrum is formed, making the most of subspaces and there eigenvalues. Some simulations followed are taken to discuss the performace of the modified method. Through the analysis we can see that, under the condition of a small signal angle interval and a low signal-noise ratio, the improved algorithm could achieve satisfactory result for the DOA estimation.