Performance analysis for time-frequency MUSIC algorithm in presence of both additive noise and array calibration errors
暂无分享,去创建一个
[1] Kevin Buckley,et al. Performance analysis of the MVDR spatial spectrum estimator , 1995, IEEE Trans. Signal Process..
[2] A. Lee Swindlehurst,et al. A Performance Analysis ofSubspace-Based Methods in thePresence of Model Errors { Part I : The MUSIC AlgorithmA , 1992 .
[3] A. Lee Swindlehurst,et al. The effects of array calibration errors on DF-based signal copy performance , 1995, IEEE Trans. Signal Process..
[4] A. Swindlehurst,et al. A maximum a posteriori approach to beamforming in the presence of calibration errors , 1996, Proceedings of 8th Workshop on Statistical Signal and Array Processing.
[5] A. Zoubir,et al. EURASIP Journal on Advances in Signal Processing , 2011 .
[6] Moeness G. Amin,et al. Blind source separation based on time-frequency signal representations , 1998, IEEE Trans. Signal Process..
[7] F. Li,et al. Performance analysis for DOA estimation algorithms: unification, simplification, and observations , 1993 .
[8] Moeness G. Amin,et al. Time-frequency MUSIC , 1999, IEEE Signal Processing Letters.
[9] Yimin Zhang,et al. Subspace analysis of spatial time-frequency distribution matrices , 2001, IEEE Trans. Signal Process..
[10] Moeness G. Amin,et al. New approach for blind source separation using time-frequency distributions , 1996, Optics & Photonics.
[11] Petre Stoica,et al. MUSIC, maximum likelihood, and Cramer-Rao bound , 1989, IEEE Transactions on Acoustics, Speech, and Signal Processing.
[12] F. Li,et al. Sensitivity analysis of DOA estimation algorithms to sensor errors , 1992 .