  Localization which uses holographic multiple input multiple output surface
such as reconfigurable intelligent surface (RIS) has gained increasing
attention due to its ability to accurately localize users in non-line-of-sight
conditions. However, existing RIS-enabled localization methods assume the users
at either the near-field (NF) or the far-field (FF) region, which results in
high complexity or low localization accuracy, respectively, when they are
applied in the whole area. In this paper, a unified NF and FF localization
method is proposed for the RIS-enabled localization system to overcome the
above issue. Specifically, the NF and FF regions are both divided into grids.
The RIS reflects the signals from the user to the base station~(BS), and then
the BS uses the received signals to determine the grid where the user is
located. Compared with existing NF- or FF-only schemes, the design of the
location estimation method and the RIS phase shift optimization algorithm is
more challenging because they are based on a hybrid NF and FF model. To tackle
these challenges, we formulate the optimization problems for location
estimation and RIS phase shifts, and design two algorithms to effectively solve
the formulated problems, respectively. The effectiveness of the proposed method
is verified through simulations.
