Date of Award

Fall 2023

Document Type


Degree Name

Doctor of Philosophy (PhD)


Electrical & Computer Engineering


Electrical and Computer Engineering

Committee Director

Dimitrie C. Popescu

Committee Member

Lee Belfore

Committee Member

Otilia Popescu

Committee Member

Chungsheng Xin


Every year in the United States many people are killed or injured when maritime vessels collide with other vessels or fixed objects. According to the United States Coast Guard, the top contributing factors to these collisions are operator inattention, operator inexperience and an improper lookout. Larger commercial vessels are required to have RADAR systems which support Automatic RADAR Plotting Aid (ARPA) which can automatically detect collisions and alert an operator to change course. These systems can be very expensive which put them out of reach of the average recreational boater. It is however possible to implement a low cost ARPA like system which is enabled by commercial marine RADAR and open source software. This dissertation presents a framework which can be used to develop an ARPA like system. There are two main problems that would be encountered that this dissertation addresses. The first problem is automatically extracting the targets from a standard commercial RADAR. Most modern RADAR systems are network enabled and send data back to a display using a standard Ethernet interface. All of the main vendors transfer the data using proprietary formats. Some vendors offer software developer kits and some open source projects, such as OpenCPN, have the ability to communicate with the RADAR systems and decode the data streams. Once the data is received from the RADAR, open source computer vision software such as OpenCV can be used to perform the target extraction. A discussion about instrumentation needed to make sure that those targets are appropriately converted to geographic coordinates is also performed. The second main problem is how to implement the tracking algorithm. The state of the art for general purpose tracking is the Multiple Hypothesis Tracking (MHT) algorithm. The MHT algorithm requires a state estimator so that it can predict where a target will be in the future. The predominate state estimator used by MHT has been the Kalman filter. This dissertation explores the use of a Particle Filter along with the Kalman Filter. A scenario where two boats pass by an observer vessel is conducted and results are analyzed and discussed.


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