As sensor technology advances and data collection capabilities improve, information fusion from multiple sensors and data sources has become an important research topic, with applications in fields such as autonomous driving, robots, and remote sensing. This statement improves the accuracy and reliability of target registration and tracking. This paper provides a full explanation of multi-source information fusion methodologies and algorithms, as well as the most recent breakthroughs in fusion optimization and artificial intelligence techniques. Furthermore, the essay provides a thorough review of the target registration technique and underlines the need of multi-source information fusion in target tracking. The study intends to provide significant insights and suggestions for the research field and its industrial applications.