@article{GENERAL,
      author = {Miao, T and El Amam, E and Slaets, P and Pissoort, D},
      url = {http://library.imarest.org/record/7710},
      journal = {Conference Proceedings of INEC},
      title = {Multi-Target Tracking and Detection, fusing RADAR and AIS  Signals using Poisson Multi-Bernoulli Mixture Tracking, in  support of Autonomous Sailing},
      abstract = {To sail safely, an autonomous vessel should be able to  keep track of the position and motion of other  vessels<br>
and obstacles, which refers to the multi-target  tracking problem. Furthermore, RADAR and automatic  identification<br>
system (AIS) are two sensors commonly  used onboard for tracking maritime targets. The fusion of  these two<br>
sensors, utilizing complementary information  and handling the conflicting data, gets increasingly  important during<br>
autonomous sailing. However, due to  the immaturity of multi-target tracking methods, the fusion  was hardly<br>
systematically discussed, when there are  missed detections from certain single sensors and conflicts  between two<br>
sensors. As the new multi-target tracking  methods have been proposed, this paper first presents a  sequential<br>
measurement-level fusion approach of RADAR  and AIS based on the newest random finite set (RFS)-based  filter<br>
— Poisson multi-Bernoulli mixture (PMBM)  filter. The comparison of the performance both using  sequential<br>
fusion and using the sensor information  individually is presented in this article. Then the  proposed sequential<br>
fusion of RADAR and AIS based on  PMBM filter was applied to a real maritime case. The  tracking results are<br>
given and the performance is  analyzed.},
      number = {GENERAL},
      recid = {7710},
      address = {2020-10-05},
}