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A novel marine radar targets extraction approach based on sequential images and Bayesian Network

Ma, F, Chen, Y-W, Yan, X-P, Chu, X-M and Wang, J (2016) A novel marine radar targets extraction approach based on sequential images and Bayesian Network. OCEAN ENGINEERING, 120. pp. 64-77. ISSN 0029-8018

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This research proposes a Bayesian Network-based methodology to extract moving vessels from a plethora of blips captured in frame-by-frame radar images. First, the inter-frame differences or graph characteristics of blips, such as velocity, direction, and shape, are quantified and selected as nodes to construct a Directed Acyclic Graph (DAG), which is used for reasoning the probability of a blip being a moving vessel. Particularly, an unequal-distance discretisation method is proposed to reduce the intervals of a blip’s characteristics for avoiding the combinatorial explosion problem. Then, the undetermined DAG structure and parameters are learned from manually verified data samples. Finally, based on the probabilities reasoned by the DAG, judgments on blips being moving vessels are determined by an appropriate threshold on a Receiver Operating Characteristic (ROC) curve. The unique strength of the proposed methodology includes laying the foundation of targets extraction on original radar images and verified records without making any unrealistic assumptions on objects' states. A real case study has been conducted to validate the effectiveness and accuracy of the proposed methodology.

Item Type: Article
Uncontrolled Keywords: 0905 Civil Engineering, 0911 Maritime Engineering
Subjects: V Naval Science > VM Naval architecture. Shipbuilding. Marine engineering
Divisions: Maritime & Mechanical Engineering (merged with Engineering 10 Aug 20)
Publisher: Elsevier
Related URLs:
Date Deposited: 30 Aug 2016 09:55
Last Modified: 04 Sep 2021 04:12
DOI or ID number: 10.1016/j.oceaneng.2016.04.030
URI: https://researchonline.ljmu.ac.uk/id/eprint/4056
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