A MUSIC like DOA estimation method for signals with low SNR

A new kind of noise subspace based direction-of-arrival (DOA) estimation method is proposed. Unlike the MUSIC algorithm , the novel MUSIC like method use signal subspace estimated by multi-stage Wiener filter (MSWF) instead of array steering vectors for orthogonality test. Simulation shows that the proposed method offers improvements in precision and resolution performance for signals with low SNR, compared to MUSIC and ESPRIT algorithms.

[1]  Eric James Grimme,et al.  Krylov Projection Methods for Model Reduction , 1997 .

[2]  Michael L. Honig,et al.  Performance of reduced-rank linear interference suppression , 2001, IEEE Trans. Inf. Theory.

[3]  Louis L. Scharf,et al.  A Multistage Representation of the Wiener Filter Based on Orthogonal Projections , 1998, IEEE Trans. Inf. Theory.

[4]  Lei Huang,et al.  Low-complexity ESPRIT method for direction finding , 2005, Proceedings. (ICASSP '05). IEEE International Conference on Acoustics, Speech, and Signal Processing, 2005..

[5]  T. Kailath,et al.  Fast Estimation of Principal Eigenspace Using LanczosAlgorithm , 1994 .

[6]  R. O. Schmidt,et al.  Multiple emitter location and signal Parameter estimation , 1986 .

[7]  Thomas Kailath,et al.  ESPRIT-estimation of signal parameters via rotational invariance techniques , 1989, IEEE Trans. Acoust. Speech Signal Process..