This paper studies the use of visual guidance system for autonomous landing of fixed-wing unmanned aerial vehicles (UAVs). The research is mainly aimed at improving the speed and accuracy of the visual navigation system to obtain the navigation parameters. The acquisition of parameters by the visual navigation system can be divided into two steps: runway detection and recognition, and relative pose estimation of fixed-wing UAVs. To improve the acquisition speed of navigation system parameters, we mainly improve the detection and recognition efficiency of the time-consuming runway detection and recognition algorithm. In this paper, the spatiotemporal consistency of the runway in the sequence image is used to extract candidate regions, and the invalid candidate regions are reduced without affecting the recall rate. Then the efficiency of runway detection is improved and ultimately the speed of the visual guidance system to obtain guidance parameters is improved. In order to improve the accuracy of the estimated guidance parameters, this paper combines the point and line features on the runway for pose estimation. That improves the pose estimation accuracy by increasing the number of available features. The experimental results show that the proposed method can effectively improve the speed and accuracy of the visual navigation system to obtain the navigation parameters.