Study of Robust Direction Finding Based on Joint Sparse Representation
CoRR(2024)
摘要
Standard Direction of Arrival (DOA) estimation methods are typically derived
based on the Gaussian noise assumption, making them highly sensitive to
outliers. Therefore, in the presence of impulsive noise, the performance of
these methods may significantly deteriorate. In this paper, we model impulsive
noise as Gaussian noise mixed with sparse outliers. By exploiting their
statistical differences, we propose a novel DOA estimation method based on
sparse signal recovery (SSR). Furthermore, to address the issue of grid
mismatch, we utilize an alternating optimization approach that relies on the
estimated outlier matrix and the on-grid DOA estimates to obtain the off-grid
DOA estimates. Simulation results demonstrate that the proposed method exhibits
robustness against large outliers.
更多查看译文
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要