Iterative Beamspace Covariance Refinement for Precise DOA Estimation in Uniform Circular Arrays under Low-snapshot Conditions
DOI:
https://doi.org/10.26636/jtit.2026.1.2392Keywords:
beamspace covariance matrix, direction of arrival estimation, low snapshot, root-MUSIC, subspace leakage, uniform circular arrayAbstract
Uniform circular arrays (UCA) provide 360° angular coverage and uniform directional response, making them preferable for direction-of-arrival estimation (DOAE). This paper proposes an iterative enhancement technique for root-MUSIC-based methods under UCA configurations, particularly effective in low-snapshot scenarios. The idea is to iteratively refine the beamspace sample covariance matrix (BSCM) by estimating and suppressing residual components that alter the signal and noise subspaces. This refinement significantly improves the accuracy of DOAE, even under limited data conditions. Numerical simulations demonstrate that the proposed method outperforms conventional UCARM, sparse UCARM, UCARBRM and unitary UCARM algorithms in terms of estimation error, beamspace leakage, conditional mean square error (CMSE) and resolution probability - across uncorrelated and correlated signal scenarios. The proposed technique is also applicable to RARE-based approaches for 2D DOAE, while preserving the beamspace covariance structure. Furthermore, the proposed method is suitable for electronic surveillance systems and low-power sensor networks.
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