Fuzzy inference based robust beamforming

This paper presents a new approach to robust beamforming based on fuzzy logic theory that is suitable for both point and scattered sources. The presented technique is based on the optimum beamformer and makes it robust to an imperfect estimate of the direction of arrival (DOA) even when powerful interferences are within the uncertainty range of the desired source. This robust approach solves the deficiencies of the classical non-robust space reference beamformers (SRB) in which the real DOA and the presumed one are taken as equal, although they are not. At low signal-to-noise ratio (SNR) the fuzzy inference-based beamformer relies on the fuzzy description of the DOA estimation, and at high SNR it places more emphasis on the estimated DOA. Interference rejection is well achieved for Interference to noise ratios (INRs) over the SNR. When the number of antennas is large, the fuzzy inference based beamformer can be implemented by means of a general side lobe canceller (GSLC) architecture and stability improves while the beamformer is still capable of suppressing weak interferences. The proposed schemes are compared with existing techniques, showing that the fuzzy inference beamformer can be an alternative when considering scenarios with DOA uncertainty and interferences. The main goals of the proposed scheme are: DOA robustness, adjustability, and numerical stability, which shortens the distance between theory and implementation.