Direction-of-Arrival and Range Estimation of Near-Field Sources Based on Subspace Fitting

A new algorithm is proposed to address the problem of near-field source localization using weighted subspace fitting (WSF) in this paper. Through separating the two parameters of bearings and ranges, the two-dimensional parameter estimation problem is first transformed into one-dimensional parameter estimation problem. The specific method is to construct a Toeplitz-like correlation matrix by using the anti-diagonal elements of the near-field source signal covariance matrix. Then the subspace fitting algorithm of sparse recovery is used to estimate the direction of arrival (DOA). The estimated direction is substituted back to the original near-field source model. After that, the sparse recovery algorithm based on singular value decomposition can be used to calculate the estimated value of the ranges. Computer simulations verify the excellent performance of the algorithm. In addition, the algorithm has lower requirements for SNR and snapshots.