Majorization-minimization Algorithms Using a Coprime Array for DOA Estimation
Kun Ye, Zhendong Chen, Yongfeng Huang, Lang Zhou, Xuebo Zhang, Haixin Sun · 2024
The sparse Bayesian learning (SBL)-based direction-of-arrival algorithms are sensitive to different priors, updating rules, and signal models. Herein, we develop a novel type-II maximum likelihood-based hyperparameter updating rule in the presence of a coprime array (CPA) using the majorization-minimization (MM) method, which is called CPA-MM-SBL. The simulation results are also provided, which prove that CPA-MM-SBL is much better than off-grid SBL and spatial smoothing-based multiple signal classification when considering low signal-to-noise ratio and different snapshots.