In view that the active visual matching algorithm in the monocular visual navigation method with 1-point random sample consensus (RANSAC) has a matching failure problem, a monocular visual navigation method with 1-Point RANSAC based on aided matching is proposed. Firstly, the scale invariant feature transform (SIFT) algorithm is introduced to complete the feature matching. Secondly, the RANSAC algorithm is used to calculate the fundamental matrix and the matching points. Finally, the effectiveness of the proposed method is verified by experiments. Results show that the active visual matching failure problem is solved and the accuracy of the the 1-point RANSAC navigation method is improved. The accuracy of the matching points calculated by the SIFT algorithm is within 5 pixels. The mean errors of the camera’s course, pitch, and roll angles estimated by the proposed method are decreased by 5.04°, 1.21°, and 3.03°, respectively.