Gridless sparsity-based DOA estimation for sparse linear array

Abstract

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.

Keywords

• toeplitz matrices
• array signal processing
• eigenvalues and eigenfunctions
• covariance matrices
• direction-of-arrival estimation
• gridless sparsity-based doa estimation
• sparse linear array
• two-stage gridless sparsity-based method
• array direction-of-arrival estimation
• covariance matrix gridless sparse representation method
• atomic norm minimisation
• corresponding structured toeplitz matrix construction
• source number
• conventional music algorithm
• conventional subspace-based algorithms
• two-stage method