Gene

Interference (communication)

Quantum mechanics

Algorithm

Control (management)

Engineering

Covariance matrix

Robustness (evolution)

Signal-to-noise ratio (imaging)

Noise power

Telecommunications

Power (physics)

Biochemistry

Computer science

Adaptive beamformer

Beamforming

Physics

Image (mathematics)

Electronic engineering

Artificial intelligence

Chemistry

Channel (broadcasting)

Control theory (sociology)

Noise (video)

IEEE Transactions on Aerospace and Electronic Systems

Adaptive beamformer is very sensitive to model mismatch, especially when the signal-of-interest is present in the training data. In this paper, we focus on the topic of robust adaptive beamforming (RAB) based on interference-plus-noise covariance matrix (INCM) reconstruction. First, we analyze the effectiveness of several INCM reconstruction schemes, and particularly analyze the impacts of interference power estimation on RAB. Second, according to the analysis results, we develop a simplified algorithm to estimate the interference powers, and a RAB algorithm based on INCM reconstruction is then presented. Compared with some existing methods, the proposed algorithm simplifies the interference power estimation of INCM reconstruction. Aligned with our analysis, simulation results demonstrate that the overestimation of interference powers hardly degrades the performance of adaptive beamforming, and our proposed algorithm achieves nearly optimal performance across a wide range of signal-to-noise ratios.

Robust Adaptive Beamforming via Simplified Interference Power Estimation