With the emergence of autonomous navigation systems such as robots and unmanned vehicles,positioning and navigation technology has developed rapidly in the past 20 years.However,new user requirements have been raised for update of positioning and navigation,which include reliable positioning and navigation ability in any environment at any time and on any platform.Multi-source fusion positioning algorithm is the only feasible way to achieve this goal.Based on the sensor model,scene model and vehicle dynamics model,we summarize positioning methods of GNSS,inertial navigation,visual sensor,and LiDAR.Then we analyze the influence that the positioning scene and vehicle dynamics pose on the multi-source fusion positioning.Finally,the multi-source fusion positioning algorithms are detailed under two fusion framework categories of optimization and filtering.