Adaptive Beamforming With Joint Robustness Against Mismatched Signal Steering Vector and Interference Nonstationarity

TLDR

Adaptive beamforming methods degrade when both signal steering vector errors and interference nonstationarity are present. The study develops a new adaptive beamforming approach jointly robust to signal steering vector errors and interference nonstationarity. The beamformer is designed by optimizing worst‑case performance and computed via a computationally efficient convex‑optimization algorithm. Simulations show that the proposed beamformer outperforms other popular robust beamforming algorithms in robustness.

Abstract

Adaptive beamforming methods degrade in the presence of both signal steering vector errors and interference nonstationarity. We develop a new approach to adaptive beamforming that is jointly robust against these two phenomena. Our beamformer is based on the optimization of the worst case performance. A computationally efficient convex optimization-based algorithm is proposed to compute the beamformer weights. Computer simulations demonstrate that our beamformer has an improved robustness as compared to other popular robust beamforming algorithms.