Near-field signal source positioning method, system and device based on sparse Bayesian learning

The invention discloses a near-field signal source positioning method, system and device based on sparse Bayesian learning. The method comprises the following steps of: solving a covariance matrix based on a near-field signal model received by a symmetric uniform linear array; constructing a virtual far-field signal model based on reverse diagonal elements of the covariance matrix; constructing a sparse Bayesian learning model based on the virtual far-field model; estimating the direction of arrival of a near-field signal source in the iteration process based on a sparse Bayesian learning model; effectively estimating the range by using a subspace-based approach; the virtual far-field model is constructed by extracting reverse diagonal elements of a signal covariance matrix, the sparse Bayesian learning model for direction of arrival estimation is established, the direction of arrival of a near-field signal source is estimated by using a gradient descent method in an iterative process based on the model, and