Dr. Eric Lefebvre Profile

Dr. Eric Lefebvre

at Lockheed Martin Canada

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Proceedings Article | 17 March 2008 Paper

The use of a multidimensional space for fusion candidate representation in a maritime domain awareness application

Eric Lefebvre, Christopher Helleur, Nathan Kashyap

Proceedings Volume 6974, 69740J (2008) https://doi.org/10.1117/12.778045

KEYWORDS: Automatic tracking, Space operations, Surveillance, Information fusion, Visualization, Radar, Artificial intelligence, Control systems, Data fusion, Data modeling

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Maritime surveillance of coastal regions requires operational staff to integrate a large amount of information from a variety of military and civilian sources. The diverse nature of the information sources makes complete automation difficult. The volume of vessels tracked and the number of sources makes it difficult for the limited operation centre staff to fuse all the information manually within a reasonable timeframe. In this paper, a conceptual decision space is proposed to provide a framework for automating the process of operators integrating the sources needed to maintain Maritime Domain Awareness. The decision space contains all potential pairs of ship tracks that are candidates for fusion. The location of the candidate pairs in this defined space depends on the value of the parameters used to make a decision. In the application presented, three independent parameters are used: the source detection efficiency, the geo-feasibility, and the track quality. One of three decisions is applied to each candidate track pair based on these three parameters: 1. to accept the fusion, in which case tracks are fused in one track, 2. to reject the fusion, in which case the candidate track pair is removed from the list of potential fusion, and 3. to defer the fusion, in which case no fusion occurs but the candidate track pair remains in the list of potential fusion until sufficient information is provided. This paper demonstrates in an operational setting how a proposed conceptual space is used to optimize the different thresholds for automatic fusion decision while minimizing the list of unresolved cases when the decision is left to the operator.

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