Study On Robust Array Beamforming Algorithm

Adaptive beamforming technology performs well in theory. However, onceaffected by array errors (such as steering vector mismatch) in practical applications, itsperformance will show a sharp decline. Therefore, robust adaptive beamformingtechnology has been a hot issue.This thesis focuses on the research of array robust beamforming algorithm. On thebasis of analyzing the performance of beamforming algorithm, which is affected bysteering vector mismatch in traditional robust beamforming algorithm, a new robustbeamforming algorithm using worst-case optimization is studied. When compared withthe traditional ones, the algorithm shows a sharp improvement in the performance ofoutput Signal-to-Interference-plus-Noise Ratio. Then a new way to obtain Lagrangefactor is simulated. Concerned the issue of some performance loss, which is caused bythe conservatism in worst-case algorithm, a reformed robust beamforming algorithmbased on probability-constrained is in the research. Unlike the worst-case optimization,the issue is focused on the improvement of array output SINR performance in twodifferent kinds of steering vector mismatch distributions. Thus a more detailedcomparison between the worst-case and the probability-constrained has been done. Inthe end, a new way based on probability-constrained is proposed to compute theparameters in robust Capon beamforming algorithm. Compared with the originalalgorithm in the loss of pattern and SNR, the method using probability-constrained isproved better in robustness.