Grid Reconfiguration Method for Off-Grid DOA Estimation

• DOI: 10.3390/electronics8111209
• Publication Date: 2019-10-25T07:20:36Z
• Authors: Yun Ling; Huotao Gao; Guobao Ru; Haitao Chen; Boya Li; Ting Cao
• Keywords: Control reconfiguration; Position (finance)

Off-grid algorithms for direction of arrival (DOA) estimation have become attractive because their advantages in resolution and efficiency over conventional ones. In this paper, we propose a grid reconfiguration (GRDOA) method based on sparse Bayesian learning. Unlike other off-grid methods, the points GRDOA are treated as dynamic parameters. The number position varied iteratively via root fission process. Then, gets reconfigured through some criteria. By updating grid, DOAs estimated completely. Since has fewer points, it better computational than previous methods. Moreover, can achieve relatively higher accuracy. Numerical simulation results validate effectiveness GRDOA.