A Direct Localization Method for Coprime Arrays Based on Averaging of Redundant Data of Virtual Array Elements

To address the issue that the traditional direct position determination (DPD) method for coprime arrays (CAs) has limited performance in scenarios with low signal‐to‐noise ratio (SNR) and small quantity of observation data, a progressive optimization method based on the averaging of redundant data from virtual array elements is proposed. This method is built on the coprime difference co‐array positioning model. It first employs the redundant data averaging technique of virtual array elements for noise reduction to enhance signal robustness, then selectively introduces virtual array hole interpolation (VAHI) technique according to actual scenario requirements to expand the effective aperture, and combines with Toeplitz matrix reconstruction technique to restore the full‐rank property of the covariance matrix, thereby providing a data foundation for high‐precision positioning. Finally, it utilizes a subspace data fusion algorithm to achieve accurate estimation of the radiation source position. Theoretical analysis and numerical simulations demonstrate that the proposed method improves the equivalent SNR through the utilization of redundant information, and its positioning performance is superior to that of existing methods. Particularly in cases of low SNR and limited observation resources, the advantages are significant, with the localization error reduced by more than 20%. This provides a solution for passive positioning in complex electromagnetic environments.