Spatial Differencing Method for Mixed Far-Field and Near-Field Sources Localization
Guohong Liu, Xiaoying Sun · IEEE Signal Processing Letters · 2014
In this letter, we present a covariance difference algorithm to cope with the mixed far-field and near-field sources localization problem. By exploiting the eigenstructure differences between the far-field covariance matrix and the near-field one, the spatial differencing technique can be adopted to classify the signals types. Based on the symmetric property of the uniform linear array geometry, a near-field estimator without any spectral search or parameter-pairing is performed. Compared to the previous works, the resultant algorithm can realize a more reasonable classification of the signals types, as well as provide the improved estimation accuracy. Computer simulations are carried out to evaluate the performance of the proposed algorithm.