Joint Estimation of Coherent Signal DOA and Polarization Parameters Based on Improved BSBL

This paper introduces a method for estimating signal direction of arrival (DOA) and polarization parameters with coherent signal sources based on an improved block structure of block sparse Bayesian learning (BSBL). The array is a uniform linear dual-polarization array composed of doubly fed orthogonal linearly polarized elements and is used to receive the horizontal electric field component and the vertical electric field component. By constructing a decoupled block sparse Bayesian model, the parameter estimation problem is transformed into a sparse recovery problem, and the improved block structure is used to achieve joint estimation of the DOA and polarization parameters in the complex domain within the sparse Bayesian framework. The estimation method enhances the signal discrimination ability in multiple near-angle source incidence scenarios, its parameter estimation performance is superior under the condition of small sampling, and the excellent performance of the algorithm is proved by the analysis and simulation of the estimation error.