This paper presents a novel algorithm for the localization of mixed far-field sources (FFSs) and near-field sources (NFSs) without estimating the source number. Firstly, the algorithm decouples the direction-of-arrival (DOA) estimation from the range estimation by exploiting fourth-order spatial-temporal cumulants of the observed data. Based on the joint diagonalization structure of multiple spatial-temporal cumulant matrices, a new one-dimensional (1-D) spatial spectrum function is derived to generate the DOA estimates of both FFSs and NFSs. Then, the FFSs and NFSs are identified and the range parameters of NFSs are determined via beamforming technique. Compared with traditional mixed sources localization algorithms, the proposed algorithm avoids the performance deterioration induced by erroneous source number estimation. Furthermore, it has a higher resolution capability and improves the estimation accuracy. Computer simulations are implemented to verify the effectiveness of the proposed algorithm.

A novel real‐valued near‐field localisation algorithm for non‐circular sources is proposed using the uniform linear array. On the basis of non‐circularity of signals, an extended real‐valued covariance matrix is constructed. Then, utilising the symmetric property of the extended array manifold, the direction of arrival and range parameters are obtained by two one‐dimensional rank reduction estimators. The proposed algorithm is efficient in that it only requires second‐order statistics (SOS) and real‐valued computations. Moreover, it can improve the estimation accuracy and resolve more sources than the conventional SOS‐based methods.