A Low Complexity Localization Algorithm for Mixed Far-Field and Near-Field Sources

In this letter, a low complexity localization algorithm based on Discrete Fourier Transform (DFT) and Orthogonal Matching Pursuit (OMP) is proposed for mixed far-field and near-field sources. The angular parameters of mixed sources can be classified and estimated by performing DFT on the anti-diagonal elements of covariance matrix and the received signal. Moreover, the estimated angular parameters and covariance are used to construct a sparse reconstruction problem related with range parameters, which can be solved by OMP algorithm. Furthermore, an iteration method is also proposed to compensate the bias of DFT. Numerical results demonstrate the superiority of proposed localization algorithm.