DOA Estimation of Coherent Sources Using Coprime Array via Reweighted Atomic Norm Minimization

The article introduces a sophisticated DOA estimation algorithm for coherent sources using coprime arrays, a type of sparse linear array known for its superior performance. Traditional methods struggle with coherent sources due to rank deficiency in the covariance matrix, but this algorithm leverages coprime array interpolation and reweighted atomic norm minimization to overcome these challenges. The algorithm enhances sparsity and resolution, leading to more accurate DOA estimation. Numerical results demonstrate the superior performance of the proposed method compared to existing compressed sensing and spatial smoothing algorithms. The algorithm's effectiveness is highlighted through various simulations, showing improved resolution and lower RMSE, particularly in scenarios with coherent sources and varying SNR and snapshot conditions. The method's ability to handle coherent sources and its robust performance make it a significant advancement in the field of DOA estimation.