Robust beamforming algorithm based on undesired disturbance cancellation and steering vector constraint

Chang Ge; Gaoxiang Xing; Tao Luo

doi:10.1117/12.2640308

1 August 2022 Robust beamforming algorithm based on undesired disturbance cancellation and steering vector constraint

Chang Ge, Gaoxiang Xing, Tao Luo

Proceedings Volume 12257, 4th International Conference on Information Science, Electrical, and Automation Engineering (ISEAE 2022); 122571U (2022) https://doi.org/10.1117/12.2640308
Event: 4th International Conference on Information Science, Electrical, and Automation Engineering (ISEAE 2022), 2022, Guangzhou, China

Abstract

An adaptive beamforming algorithm based on undesired disturbance cancellation and steering vector constraint is proposed to solve the problem of beamforming performance degradation caused by formation distortion and array model mismatch during passive sonar operation. This algorithm reconstructs interference-plus-noise covariance matrix (INCM), which is closer to the real value through the uncertainty set constraint of the steering vector, discusses the composition and estimation method of the undesired disturbance of Capon power spectrum, and gives the basic implementation flow of the covariance matrix reconstruction algorithm. The robustness of the algorithm is verified by simulation results.

Citation Download Citation

Chang Ge, Gaoxiang Xing, and Tao Luo "Robust beamforming algorithm based on undesired disturbance cancellation and steering vector constraint", Proc. SPIE 12257, 4th International Conference on Information Science, Electrical, and Automation Engineering (ISEAE 2022), 122571U (1 August 2022); https://doi.org/10.1117/12.2640308

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available