Positioning Algorithm of UWB based on TDOA Technology in Indoor Environment

Abstract

Most of the localization algorithms can achieve extremely high positioning accuracy in line of sight (LOS) environment. However, they are unable to obtain ideal accuracy due to the obstacles in non-line of sight (NLOS) environment. In order to reduce the influence of NLOS on positioning accuracy in indoor environment, Fang algorithm, Chan algorithm and Taylor algorithm based on TDOA in UWB indoor positioning technology are analyzed and tested. Through comparative simulation analysis, it can be concluded that in the case of Gaussian noise, regardless of the number of base stations, Chan algorithm has the best performance, Taylor algorithm is the second, and Fang algorithm has the worst performance. When the number of base stations reaches a certain number, Chan algorithm and Taylor algorithm are not sensitive to the number of base stations, but they can use all TDOA information to obtain more accurate parameter solutions, and can also be adapted to different measurement environments.