Sparse representation based direction‐of‐arrival estimation in nonuniform noise via tail minimisation

Abstract

Abstract DOA estimation based on sparse representation in a non‐uniform noise environment is proposed using a tail minimisation technique. The noise‐free covariance matrix is modelled as diagonal and off‐diagonal components relating to incoming signals. In order to combat coherent signals, the auto‐ and cross‐correlation entries of the incident signal are considered separately by using the least square (LS) criterion. Subsequently, from the perspective of difference co‐array a vectorised covariance matrix is obtained to emulate the received signal similar to the output of a single snapshot. The effect of non‐uniform noise is significantly mitigated via a removal operation. A tail minimisation scheme that is capable of deriving sharper spectra peaks is then applied to detect the DOAs. The proposed approach has the advantages of a larger virtual array aperture beneficial to DOA estimations of uncorrelated and/or coherent signals. The technique can suppress false spectral peaks to a certain extent and is also computationally effective. Numerical simulation verifies the effectiveness of the proposed method.

Keywords

• array signal processing
• correlation methods
• covariance matrices
• direction‐of‐arrival estimation
• least squares approximations
• minimisation