Focusing on the construction of autonomous navigation capabilities for large unmanned surface vessels (USVs) at sea, and aiming to leverage the functional characteristics of different perception sensors, a situational awareness system for large USVs based on multi-source heterogeneous sensors was designed and constructed. A software-hardware co-design architecture for information fusion in the situational awareness system was proposed. Based on the constructed situational awareness system, preliminary maritime situational awareness experiments were carried out, verifying relevant target detection and identification algorithms, and identifying and defining multiple practical engineering challenges. On this basis, some key technologies related to situational awareness of large USVs were analyzed and summarized, including the clock unity accuracy requirements for multi-source data fusion in situational awareness, radar low observability and target tracking detection technology in wave environments, radar-optical collaborative tracking and fusion technology, etc. These can provide references for improving the situational awareness and autonomous navigation capabilities of large USVs.