  This letter introduces a novel unmanned aerial vehicle (UAV)-intelligent
reflecting surface (IRS) structure into near-field localization systems to
enhance the design flexibility of IRS, thereby obtaining additional performance
gains. Specifically, a UAV-IRS is utilized to improve the harsh wireless
environment and provide localization possibilities. To improve the localization
accuracy, a joint optimization problem considering UAV position and UAV-IRS
passive beamforming is formulated to maximize the receiving signal-to-noise
ratio (SNR). An alternative optimization algorithm is proposed to solve the
complex non-convex problem leveraging the projected gradient ascent (PGA)
algorithm and the principle of minimizing the phase difference of the receiving
signals. Closed-form expressions for UAV-IRS phase shift are derived to reduce
the algorithm complexity. In the simulations, the proposed algorithm is
compared with three different schemes and outperforms the others in both
receiving SNR and localization accuracy.
