(May 2001)
Sergiy A. Vorobyov, Alex B. Gershman, and Zhi-Quan
(Tom) Luo
License and Referencing
This code package is licensed
under the GPLv2 license. If you in any way use this code for research that
results in publications, please cite our original articles S.A.
Vorobyov, A.B.
Gershman, and Z.-Q. Luo, "Robust adaptive beamforming
using worst-case performance optimization: A solution to the signal mismatch
problem," IEEE Trans. Signal Processing,
vol. 51, no. 2, pp. 313–324, Feb. 2003 and S.A. Vorobyov,
H. Chen, and A.B. Gershman, "On the relationship between
robust minimum variance beamformers with probabilistic and worst-case distrortionless response constraints," IEEE Trans. Signal Processing, vol. 56, no. 11,
pp. 5719–5724, Nov. 2008.
robustBeamforming is a
Matlab implementation of the worst-case-based robust adaptive beamforming
method described in the paper S.A. Vorobyov, A.B. Gershman, and Z.-Q. Luo, "Robust adaptive beamforming
using worst-case performance optimization: A solution to the signal mismatch
problem," IEEE Trans. Signal Processing,
vol. 51, no. 2, pp. 313–324, Feb. 2003. It
summarized the Matlab codes to simulate Example 3 in the paper. The codes for
other examples differ only in the modelling of the corresponding steering
vector mismatches which are given in details in
descriptions for each example. The same code can be used with little
modifications to simulate the results in the paper S.A. Vorobyov, H. Chen, and A.B. Gershman, "On the relationship between
robust minimum variance beamformers with probabilistic and worst-case distrortionless response constraints," IEEE Trans. Signal Processing, vol. 56, no. 11,
pp. 5719–5724, Nov. 2008.
Please report any bugs to Sergiy A. Vorobyov <svor@ieee.org>.
demo3power.m will
generate the figure for output SINR versus SNR for Example 3 in the paper
robustbeam.m and dsfrbfin.m are two subroutines which implement the worst-case-based robust
adaptive beamforming method based on SeDuMi software
package for convex optimization
sedumi.zip is SeDuMi software package for convex optimization