A fuzzy logic-based multisensor data fusion for Maritime Surveillance — real data testing

Multisensor data fusion is the most important technique employed to support Maritime Surveillance thus improving the quality of target tracking system. One of the major problems is that the surveillance area is generally large, hence making it difficult to arrive at a feasible data fusion architecture. The latter arises due to timing, accuracy, and different types of sensors and sensor platforms. In this paper, an efficient fuzzy logic-based data fusion technique is employed to support the maritime surveillance process. A real data set is used to evaluate the performance of the proposed data fusion algorithm which interacts with data fusion processes at different information levels. The results have proven that the proposed technique has an acceptable performance and computation complexity which is vital in real-time applications.