English

Direction-of-Arrival and Noise Covariance Matrix joint estimation for beamforming

Audio and Speech Processing 2026-01-21 v4 Optimization and Control

Abstract

We propose a joint estimation method for the Direction-of-Arrival (DoA) and the Noise Covariance Matrix (NCM) tailored for beamforming applications. Building upon an existing NCM framework, our approach simplifies the estimation procedure by deriving an quasi-linear solution, instead of the traditional exhaustive search. Additionally, we introduce a novel DoA estimation technique that operates across all frequency bins, improving robustness in reverberant environments. Simulation results demonstrate that our method outperforms classical techniques, such as MUSIC, in mid- to high-angle scenarios, achieving lower angular errors and superior signal enhancement through beamforming. The proposed framework was also fared against other techniques for signal enhancement, having better noise rejection and interference canceling capabilities. These improvements are validated using both theoretical and empirical performance metrics.

Keywords

Cite

@article{arxiv.2511.10639,
  title  = {Direction-of-Arrival and Noise Covariance Matrix joint estimation for beamforming},
  author = {Vitor Gelsleichter Probst Curtarelli and Stephan Paul and Anderson Wedderhoff Spengler},
  journal= {arXiv preprint arXiv:2511.10639},
  year   = {2026}
}