Robust Adaptive Beamforming Based on Low-Complexity Discrete Fourier Transform Spatial Sampling

Autor(es)

Mohammadzadeh, Saeed ^[1] ; Nascimento, Vitor H. ^[1] ; De Lamare, Rodrigo C. ^[2] ; Kukrer, Osman ^[3]

Afiliação do(s) autor(es)

^[1] Univ Sao Paulo, Dept Elect Syst Engn, BR-05508900 Sao Paulo - Brazil

^[2] Pontificia Univ Catolica Rio de Janeiro, CETUC, BR-22451900 Rio de Janeiro - Brazil

^[3] Eastern Mediterranean Univ, Dept Elect & Elect Engn, TR-99450 Famagusta - Turkey

• Tipo de documento: Artigo Científico
• Fonte: IEEE ACCESS; v. 9, p. 84845-84856, 2021.
• Citações Web of Science: 0

Resumo

In this paper, a novel and robust algorithm is proposed for adaptive beamforming based on the idea of reconstructing the autocorrelation sequence (ACS) of a random process from a set of measured data. This is obtained from the first column and the first row of the sample covariance matrix (SCM) after averaging along its diagonals. Then, the power spectrum of the correlation sequence is estimated using the discrete Fourier transform (DFT). The DFT coefficients corresponding to the angles within the noise-plus-interference region are used to reconstruct the noise-plus-interference covariance matrix (NPICM), while the desired signal covariance matrix (DSCM) is estimated by identifying and removing the noise-plus-interference component from the SCM. In particular, the spatial power spectrum of the estimated received signal is utilized to compute the correlation sequence corresponding to the noise-plus-interference in which the dominant DFT coefficient of the noise-plus-interference is captured. A key advantage of the proposed adaptive beamforming is that only little prior information is required. Specifically, an imprecise knowledge of the array geometry and of the angular sectors in which the interferences are located is needed. Simulation results demonstrate that compared with previous reconstruction-based beamformers, the proposed approach can achieve better overall performance in the case of multiple mismatches over a very large range of input signal-to-noise ratios. (AU)

• Processo FAPESP: 18/12579-7 - Tecnologias habilitadores para a Internet das Coisas
• Beneficiário: Vitor Heloiz Nascimento
• Modalidade de apoio: Auxílio à Pesquisa - Temático
• Processo FAPESP: 19/19387-9 - Técnicas de processamento de sinais em beamforming e esquemas de codificação em sistemas de comunicações de IoT
• Beneficiário: Saeed Mohammadzadeh
• Modalidade de apoio: Bolsas no Brasil - Pós-Doutorado