Low-Complexity Uncertainty Set Based Robust Adaptive Beamforming for Passive Sonar

Recent work has highlighted the potential benefits of exploiting ellipsoidal uncertainty set based robust Capon beamformer (RCB) techniques in passive sonar. Regrettably, the computational complexity of forming RCB weights is cubic in the number of adaptive degrees of freedom, which is often prohibitive in practice. For this reason, several low-complexity techniques for computing RCB weights, or equivalent worst-case robust adaptive beamformer (WC-RAB) weights, have recently been developed, whose complexities are only quadratic in the number of adaptive degrees of freedom. In this work, we review several such techniques for passive sonar, evaluating them initially on simulated data. The best performing methods are then evaluated on in-water recorded passive sonar data. Index Terms Efficient robust adaptive beamforming, robust Capon beamforming, worst-case robust adaptive beamforming, robust adaptive beamforming, underwater acoustics.