TY  - GEN
N2  - To sail safely, an autonomous vessel should be able to keep track of the position and motion of other vessels&lt;br&gt;
and obstacles, which refers to the multi-target tracking problem. Furthermore, RADAR and automatic identification&lt;br&gt;
system (AIS) are two sensors commonly used onboard for tracking maritime targets. The fusion of these two&lt;br&gt;
sensors, utilizing complementary information and handling the conflicting data, gets increasingly important during&lt;br&gt;
autonomous sailing. However, due to the immaturity of multi-target tracking methods, the fusion was hardly&lt;br&gt;
systematically discussed, when there are missed detections from certain single sensors and conflicts between two&lt;br&gt;
sensors. As the new multi-target tracking methods have been proposed, this paper first presents a sequential&lt;br&gt;
measurement-level fusion approach of RADAR and AIS based on the newest random finite set (RFS)-based filter&lt;br&gt;
&amp;mdash; Poisson multi-Bernoulli mixture (PMBM) filter. The comparison of the performance both using sequential&lt;br&gt;
fusion and using the sensor information individually is presented in this article. Then the proposed sequential&lt;br&gt;
fusion of RADAR and AIS based on PMBM filter was applied to a real maritime case. The tracking results are&lt;br&gt;
given and the performance is analyzed.
AB  - To sail safely, an autonomous vessel should be able to keep track of the position and motion of other vessels&lt;br&gt;
and obstacles, which refers to the multi-target tracking problem. Furthermore, RADAR and automatic identification&lt;br&gt;
system (AIS) are two sensors commonly used onboard for tracking maritime targets. The fusion of these two&lt;br&gt;
sensors, utilizing complementary information and handling the conflicting data, gets increasingly important during&lt;br&gt;
autonomous sailing. However, due to the immaturity of multi-target tracking methods, the fusion was hardly&lt;br&gt;
systematically discussed, when there are missed detections from certain single sensors and conflicts between two&lt;br&gt;
sensors. As the new multi-target tracking methods have been proposed, this paper first presents a sequential&lt;br&gt;
measurement-level fusion approach of RADAR and AIS based on the newest random finite set (RFS)-based filter&lt;br&gt;
&amp;mdash; Poisson multi-Bernoulli mixture (PMBM) filter. The comparison of the performance both using sequential&lt;br&gt;
fusion and using the sensor information individually is presented in this article. Then the proposed sequential&lt;br&gt;
fusion of RADAR and AIS based on PMBM filter was applied to a real maritime case. The tracking results are&lt;br&gt;
given and the performance is analyzed.
AD  - KU Leuven, Belgium
AD  - RH Marine Netherlands B.V., the Netherlands
AD  - KU Leuven, Belgium
AD  - KU Leuven, Belgium
T1  - Multi-Target Tracking and Detection, fusing RADAR and AIS Signals using Poisson Multi-Bernoulli Mixture Tracking, in support of Autonomous Sailing
DA  - 2020-10-05
AU  - Miao, T
AU  - El Amam, E
AU  - Slaets, P
AU  - Pissoort, D
L1  - https://library.imarest.org/record/7710/files/INEC_2020_Paper_107.pdf
JF  - Conference Proceedings of INEC
VL  - INEC 2020
PY  - 2020-10-05
ID  - 7710
L4  - https://library.imarest.org/record/7710/files/INEC_2020_Paper_107.pdf
KW  - RADAR and AIS fusion
KW  - sensor fusion
KW  - multi-target tracking
KW  - PMBM tracker
KW  - data association
TI  - Multi-Target Tracking and Detection, fusing RADAR and AIS Signals using Poisson Multi-Bernoulli Mixture Tracking, in support of Autonomous Sailing
Y1  - 2020-10-05
L2  - https://library.imarest.org/record/7710/files/INEC_2020_Paper_107.pdf
LK  - https://www.imarest.org/events/inec-2020
LK  - https://library.imarest.org/record/7710/files/INEC_2020_Paper_107.pdf
UR  - https://www.imarest.org/events/inec-2020
UR  - https://library.imarest.org/record/7710/files/INEC_2020_Paper_107.pdf
ER  -