Recursive Bayesian beamforming with uncertain projected steering vector and strong interferences. Issue 5 (July 2016)

• Record Type: Journal Article
• Authors: Han, Yubing; Tran, Vanha
• Is Part Of: Signal, image and video processing. Volume 10:Issue 5(2016)
• Page Start: 975
• Page End: 982
• Publication Date: 2016-07
• Subjects: Array processing -- Bayesian method -- Subspace projection beamforming -- Steering vector uncertainty -- Strong interference -- Minimum mean square error (MMSE) estimation; Signal processing -- Digital techniques -- Periodicals; Image processing -- Digital techniques -- Periodicals; Digital video -- Periodicals; 621.3822
• DOI: 10.1007/s11760-015-0848-3
• Languages: English
• ISSNs: 1863-1703

Abstract

Abstract A recursive Bayesian beamforming is proposed for the steering vector uncertainty and strong interferences. Signal and noise powers are unknown, and beamforming weight is modeled as a complex Gaussian vector that characterizes the level of projected steering vector uncertainty. By applying the Bayesian model, a recursive algorithm is developed to estimate beamforming weight. Numerical simulations of linear and planar arrays demonstrate the effectiveness and robustness of the proposed beamforming algorithm. After convergence, the proposed algorithm exhibits a performance similar to that of the optimal $$\mathrm {MaxSINR}$$ MaxSINR beamformer.