To sail safely, an autonomous vessel should be able to keep track of the position and motion of other vessels
and obstacles, which refers to the multi-target tracking problem. Furthermore, RADAR and automatic identification
system (AIS) are two sensors commonly used onboard for tracking maritime targets. The fusion of these two
sensors, utilizing complementary information and handling the conflicting data, gets increasingly important during
autonomous sailing. However, due to the immaturity of multi-target tracking methods, the fusion was hardly
systematically discussed, when there are missed detections from certain single sensors and conflicts between two
sensors. As the new multi-target tracking methods have been proposed, this paper first presents a sequential
measurement-level fusion approach of RADAR and AIS based on the newest random finite set (RFS)-based filter
— Poisson multi-Bernoulli mixture (PMBM) filter. The comparison of the performance both using sequential
fusion and using the sensor information individually is presented in this article. Then the proposed sequential
fusion of RADAR and AIS based on PMBM filter was applied to a real maritime case. The tracking results are
given and the performance is analyzed.