Covariance Matrix Construction with Preprocessing-Based Spatial Sampling for Robust Adaptive Beamforming

• URL: http://arxiv.org/abs/2510.17823v1
• Date: Tue, 30 Sep 2025 17:46:44 GMT
• Title: Covariance Matrix Construction with Preprocessing-Based Spatial Sampling for Robust Adaptive Beamforming
• Authors: Saeed Mohammadzadeh, Rodrigo C. de Lamare, Yuriy Zakharov,
• Abstract summary: This work proposes an efficient, robust adaptive beamforming technique to deal with steering vector estimation mismatches.<n>In particular, the direction-of-arrival(DoA) of interfering sources is estimated with available snapshots in which the angular sectors of the interfering signals are computed adaptively.<n>An analysis of the array beampattern in the proposed PPBSS technique is carried out, and a study of the computational cost of competing approaches is conducted.
• Score: 13.635183363631299
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: This work proposes an efficient, robust adaptive beamforming technique to deal with steering vector (SV) estimation mismatches and data covariance matrix reconstruction problems. In particular, the direction-of-arrival(DoA) of interfering sources is estimated with available snapshots in which the angular sectors of the interfering signals are computed adaptively. Then, we utilize the well-known general linear combination algorithm to reconstruct the interference-plus-noise covariance (IPNC) matrix using preprocessing-based spatial sampling (PPBSS). We demonstrate that the preprocessing matrix can be replaced by the sample covariance matrix (SCM) in the shrinkage method. A power spectrum sampling strategy is then devised based on a preprocessing matrix computed with the estimated angular sectors' information. Moreover, the covariance matrix for the signal is formed for the angular sector of the signal-of-interest (SOI), which allows for calculating an SV for the SOI using the power method. An analysis of the array beampattern in the proposed PPBSS technique is carried out, and a study of the computational cost of competing approaches is conducted. Simulation results show the proposed method's effectiveness compared to existing approaches.

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