TY - GEN
T1 - Robust adaptive beamforming based on interference covariance matrix reconstruction and mismatched steering vector compensation
AU - Yan, Lu
AU - Yang, Xiaopeng
AU - Xi, Wen
AU - Zhang, Zongao
AU - Sarkar, Tapan K.
N1 - Publisher Copyright:
© 2014 IEEE.
PY - 2014/12/18
Y1 - 2014/12/18
N2 - The performance of adaptive beamforming degrades in presence of signal model mismatches. In particular, when the desired signal is present in training snapshots, the adaptive beamforming is quite sensitive to desired signal steering vector mismatch. Therefore, a robust adaptive beamforming for actual system is proposed based on the reconstruction of interference covariance matrix and mismatched steering vector compensation. In the proposed method, the interference covariance matrix is firstly reconstructed by using Root-MUSIC method to estimate Direction-of-Arrival (DOA) of signals, where the desired signal component is removed from the training snapshots. Subsequently, the mismatched desired signal steering vector is compensated by solving a quadratically constrained quadratic programming problem. Simulation results show that the performance of proposed algorithm outperforms the existing robust adaptive beamforming, and the output signal-to-interference-plus-noise ratio (SINR) is close to optimal values. Therefore, the proposed algorithm could be significantly effective for actual system.
AB - The performance of adaptive beamforming degrades in presence of signal model mismatches. In particular, when the desired signal is present in training snapshots, the adaptive beamforming is quite sensitive to desired signal steering vector mismatch. Therefore, a robust adaptive beamforming for actual system is proposed based on the reconstruction of interference covariance matrix and mismatched steering vector compensation. In the proposed method, the interference covariance matrix is firstly reconstructed by using Root-MUSIC method to estimate Direction-of-Arrival (DOA) of signals, where the desired signal component is removed from the training snapshots. Subsequently, the mismatched desired signal steering vector is compensated by solving a quadratically constrained quadratic programming problem. Simulation results show that the performance of proposed algorithm outperforms the existing robust adaptive beamforming, and the output signal-to-interference-plus-noise ratio (SINR) is close to optimal values. Therefore, the proposed algorithm could be significantly effective for actual system.
KW - Adaptive beamforming
KW - Root-MUSIC
KW - quadratically constrained quadratic programming
KW - reconstructed interference covariance
UR - http://www.scopus.com/inward/record.url?scp=84921407226&partnerID=8YFLogxK
U2 - 10.1109/APCAP.2014.6992449
DO - 10.1109/APCAP.2014.6992449
M3 - Conference contribution
AN - SCOPUS:84921407226
T3 - Proceedings of 3rd Asia-Pacific Conference on Antennas and Propagation, APCAP 2014
SP - 189
EP - 192
BT - Proceedings of 3rd Asia-Pacific Conference on Antennas and Propagation, APCAP 2014
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 3rd Asia-Pacific Conference on Antennas and Propagation, APCAP 2014
Y2 - 26 July 2014 through 29 July 2014
ER -