A Computationally Efficient Algorithm for DOA Estimation with Unfolded Coprime Linear Array

• Published in: Mathematical problems in engineering Vol. 2022; pp. 1 - 12
• Main Authors: Pan, Gong, Huafei, Yin
• Format: Journal Article
• Language: English
• Published: New York Hindawi 05.09.2022; John Wiley & Sons, Inc
• Subjects: Algorithms; Complexity; Computational efficiency; Computing costs; Direction of arrival; Eigenvalues; Linear arrays; Mathematical problems; Sensors; Signal processing; Simulation
• ISSN: 1024-123X; 1026-7077; 1563-5147; 1563-5147
• DOI: 10.1155/2022/5429488

In this paper, we investigate the direction of arrival (DOA) estimation problem with unfolded coprime linear array (UCLA) and propose a low computational complexity signal-subspace fitting (SF) algorithm. SF algorithm is able to achieve excellent DOA estimation performance while it requires global angular search (GAS). Especially in the several source signals situation, expensive complexity cost causes. To decrease computational complexity, we propose an initialized based SF (ISF) algorithm, which involves the several one dimensional (1D) partial angular search (PAS) instead of the multidimensional GAS. Consequently, the complexity is significantly decreased. Due to the full utilization of the array aperture, the proposed method in UCLA can attain better performance than general CLA (GCLA). In addition, as the SF is attractive in practical application, the proposed ISF algorithm lowers the computational cost, while achieving almost approximate estimation performance as traditional SF and noise subspace fitting (NF). Moreover, numerical simulations are provided and verify the effectiveness and the superiority of the proposed algorithm for the UCLA.