TY - GEN
T1 - Robust adaptive beamforming for antenna sensor array based on the reconstruction shrinkage method
AU - Gong, Yanyun
AU - Chen, Qinglang
AU - Wang, Haitao
AU - Wang, Yufei
N1 - Publisher Copyright:
© 2023 IEEE.
PY - 2023
Y1 - 2023
N2 - An advanced interference plus noise covariance matrix (ICM) reconstruction approach was proposed to facilitate robust adaptive beamforming for antenna sensor arrays The proposed method involves the calculation of the eigenvectors and eigenvalues of the signal of interest (SOI) and the interference through eigen-projection processing. Following this, the covariance matrix without the required signal component is formed by amending the diagonal matrix of the eigenvalue Then, the mixed ICM is constructed using the shrinkage method. A quadratically constrained quadratic programming (QCQP) dilemma can be worked out to ascertain the difference between the proposed steering vector (SV) and the true vector. The benefit of the proposed method is that the ICM can be obtained on the move and also can be obtained more precisely in the situation of high signal-to-noise ratio (SNR). Finally, the results of the theoretical analysis and simulation demonstrate the robustness and efficacy of the proposed method.
AB - An advanced interference plus noise covariance matrix (ICM) reconstruction approach was proposed to facilitate robust adaptive beamforming for antenna sensor arrays The proposed method involves the calculation of the eigenvectors and eigenvalues of the signal of interest (SOI) and the interference through eigen-projection processing. Following this, the covariance matrix without the required signal component is formed by amending the diagonal matrix of the eigenvalue Then, the mixed ICM is constructed using the shrinkage method. A quadratically constrained quadratic programming (QCQP) dilemma can be worked out to ascertain the difference between the proposed steering vector (SV) and the true vector. The benefit of the proposed method is that the ICM can be obtained on the move and also can be obtained more precisely in the situation of high signal-to-noise ratio (SNR). Finally, the results of the theoretical analysis and simulation demonstrate the robustness and efficacy of the proposed method.
KW - antenna sensor array
KW - covariance matrix reconstruction
KW - robust adaptive beamforming
KW - steering vector estimation
UR - http://www.scopus.com/inward/record.url?scp=85159020983&partnerID=8YFLogxK
U2 - 10.1109/NNICE58320.2023.10105747
DO - 10.1109/NNICE58320.2023.10105747
M3 - 会议稿件
AN - SCOPUS:85159020983
T3 - 2023 3rd International Conference on Neural Networks, Information and Communication Engineering, NNICE 2023
SP - 260
EP - 265
BT - 2023 3rd International Conference on Neural Networks, Information and Communication Engineering, NNICE 2023
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 3rd International Conference on Neural Networks, Information and Communication Engineering, NNICE 2023
Y2 - 24 February 2023 through 26 February 2023
ER -