NLOS Positioning Optimization Method Based on Unknown Location IRS

The intelligent reflecting surface (IRS) is similar to an antenna array, which consists of multiple reflecting units. By controlling the phase shift of each reflecting unit, the direction of beam reflection is changed based on the analog beam fugacity theory, thus achieving the purpose of enhancing or constructing a channel. Therefore, IRS has great advantages in solving the channel estimation problem under non-line-of-sight (NLOS) conditions. For this characteristic, this paper proposes a localization method based on compressed sensing technology for the case where the relative position of IRS and base station is unknown, using NLOS path signals for second-order position estimation, first deriving rough localization parameters for IRS cascade channel estimation, and then conducting a joint phase configuration of IRS reflecting The phase configuration of the unit is jointly optimized, and then the second-order precise position estimation is performed. The results show that the proposed method is applicable to the NLOS positioning system with unknown IRS position, and due to the optimization capability of the IRS for the beam, the success rate of the positioning solution is improved by more than 20% and the positioning error is reduced by more than 40%.