To meet the demands for comprehensive three-dimensional coverage and massive connectivity in sixth generation of communication system （6G）， establishing a space-air-ground integrated networks （SAGIN） has become a crucial development direction. However， both standalone radio frequency （RF） and free-space optical （FSO） communication technologies have inherent limitations， making it challenging for either to independently fulfill the future network’s comprehensive requirements for ultra-high speed， ultra-high reliability， and wide-area dynamic access. Against this backdrop， integrating the complementary advantages of RF and FSO communications to build an intelligent and cooperative hybrid RF/FSO transmission network for SAGIN has become a key pathway to overcoming current technological bottlenecks. This paper provides a systematic review of domestic and international research advancements in this field， proposing an integrated optical and RF for cognitive software defined network architecture for SAGIN. It focuses on channel modeling methodologies for RF and FSO links applicable to heterogeneous space-air-ground environments， whilst conducting an in-depth analysis of core challenges including high-dynamic link precision alignment， intelligent allocation of heterogeneous resources， and robust transmission under extreme conditions. The paper then elaborates on key enabling technologies such as hybrid RF/FSO beam tracking， adaptive RF/FSO switching， parallel collaborative transmission， and scenario-specific link selection. Future research trends are also outlined， encompassing deep integration of intelligent algorithms， enhancement of cross-domain disturbance-resistant transmission， and holistic system performance optimization. Studies demonstrate that hybrid RF/FSO technology can significantly improve the overall performance of SAGIN. Nevertheless， its path towards large-scale application necessitates further in-depth research on cross-layer coordination mechanisms， dynamic resource management， and system-level performance evaluation.