@article{
  author = {M. Rihan, Mingyang Chen, Qiang Li, Xiao Peng Li, and Lei Huang},
  year = {2024},
  month = {Jan},
  title = {One-Bit DoA Estimation for Deterministic Signals Based on ℓ2,1-Norm Minimization},
  volume = {60},
  number = {02},
  publisher = {Institute of Electrical and Electronics Engineers (IEEE)},
  pages = {2438 - 2444},
  ISBN = {0018-9251},
  URL = {https://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=7},
  abstract={One-bit direction-of-arrival (DoA) estimation has drawn considerable attention in recent years with the increasing demand for low power consumption and high sampling rate. In this work, the 1-bit DoA estimation for deterministic signals is addressed from the viewpoint of sparse matrix recovery. First, using maximum likelihood (ML) and compressive sensing techniques, 1-bit DoA estimation is formulated as an ML-based row sparse matrix optimization in terms of least-absolute-shrinkage-and-selection-operator form with an ℓ2,1 regularization. After that, by complex-valued conjugate gradient and steepest descent operations, an iterative closed-form solution in the form of a row-sparse matrix is expected to be obtained. At last, the estimates of source numbers and DoAs are simultaneously completed by making sense of the structure of the row-sparse matrix. Numerical results showcase that the proposed algorithm outperforms the state-of-the-art approaches in terms of estimation accuracy.},
  journal={IEEE Transactions on Aerospace and Electronic Systems}
}