Convolution Neural Networks for Localization of Near-Field Sources via Symmetric Double-Nested Array

Table 1

Main steps of the proposed method.

Algorithm for near-field source localization
1.	Construct the phase difference matrix of each near-field source in (8).
2.	Extract the upper right counter-diagonal elements in (8) and perform the trained th autoencoder to obtain the output of the th subregion .
3.	Perform the trained classification CNN to obtain the corresponding output of the th spatial spectrum .
4.	Splice the output of the AOA spatial spectrum and search the spatial peaks to determine the AOAs of the near-field sources.
5.	Construct a particular range vector in (17) to eliminate the estimated AOA of the th near-field source.
6.	Perform the trained regression CNN with to determine the corresponding range of the th near-field source.