In order to improve the state estimation of UAV in a large range of weak texture scenes, an improved visual inertial odometer combined with GPS positioning method is proposed. Firstly, the geometric structure information of the environment was represented by adding line features into the visual inertial odometer to improve the accuracy of pose estimation. Secondly, by introducing length threshold screening, the short line segments that do not contribute much to pose estimation are eliminated to improve the robustness of feature tracking. Finally, the GPS measurement information is fused with the improved visual inertial odometer in a nonlinear optimization way to correct the cumulative error of the visual inertial odometer. The simulation experiment based on EuRoC dataset and the real scene experiment applied to UAV show that, compared with the original algorithm, the positioning error of the line feature algorithm is reduced by 39.14% in the simulation experiment, 23.48% in the indoor scene and 33.58% in the outdoor scene. The point and line feature algorithm integrated with GPS. The positioning error was reduced by 53.99%.