Owing to the widespread availability of multiple remote sensing methods, regions are often covered by satellite observation from multiple sources. However, the geometric positioning accuracy of optical satellites, which are the most common data source, is generally insufficient. An intuitive idea to improve accuracy is to integrate the dominant accuracy of multisource information. Previous studies have used synthetic aperture radar (SAR) and Geoscience Laser Altimetry System (GLAS) data with improved geo-positioning accuracy. However, the accuracy and applicability of existing combination methods are unsatisfactory because of various restrictions. In this study, a pipeline with automatic extraction of tie points and combined adjustment was designed based on non-stereo SAR images and GLAS data, considering both the high precision and wide distribution of multi-source data. Experiments using real satellite data (ZY-3, GF-7, GF-3, and ICESat-2) and test areas covering complex landforms demonstrated the feasibility and effectiveness of the proposed pipeline. The geo-positioning accuracy in three experimental areas reached 3.16, 3.36, and 3.17 m in the horizontal direction and 1.45, 1.25, and 1.28 m in the vertical direction. Our pipeline not only permits high accuracy close to the nominal accuracy of heterogeneous reference data but can also be extended to global high-precision geo-positioning without ground control.