Aerial-space image matching is one of the significant research directions of unmanned aerial vehicles. This paper systematically constructs a framework for matching heterogeneous aerial-space images and provides an in-depth analysis of its key components. Based on literature review, this paper categorizes the key technologies of the heterogeneous image matching framework into three major types: image quality assessment technology, image preprocessing technology, and image matching technology. It summarizes the latest advancements in each of these technologies, with a particular focus on analyzing the technical differences in their application to the UAV field. Based on this, cross-comparison experiments are conducted using datasets to analyze the specific effects of each method. Finally, the paper summarizes the challenges faced in matching heterogeneous aerial and space images and provides an outlook on future research directions and development trends.