Open AccessGridless sparsity‐based DOA estimation for sparse linear array
Author(s) -
Zhang Yu,
Zhang Gong,
Kong Yingying,
Wen Fangqing
Publication year - 2019
Publication title -
the journal of engineering
Language(s) - English
Resource type - Journals
ISSN - 2051-3305
DOI - 10.1049/joe.2019.0143
Subject(s) - computer science , sparse array , estimation , algorithm , pattern recognition (psychology) , artificial intelligence , engineering , systems engineering
A novel two‐stage gridless sparsity‐based method for sparse linear array direction‐of‐arrival (DOA) estimation is presented. First, the covariance matrix gridless sparse representation method based on atomic norm minimisation is proposed for corresponding structured Toeplitz matrix construction and source number detection. Then, the conventional MUSIC algorithm can be employed for DOA estimation. Compared with conventional subspace‐based algorithms, the proposed two‐stage method can be carried out without knowing source number and directly detect more source signals than sensors. Numerical simulations demonstrate the effectiveness and outperformance of the proposed method.