19 August 1993 Automated radar behavior analysis using neural network architectures
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In this paper the application and performance of Artificial Neural Networks (ANN) to the problem of sensor data fusion is reported for an experimental system, Tracker. The task of sensor data fusion involves integrating numerous data streams, originating from disparate sensors, into a consistent model that represents the pertinent higher level features of the environment as well as presenting an assessment of their significance. In the case of the modern naval environment, the problem central to many tactical data fusion systems is the need for rapid acquisition and interpretation of the information. In a potentially hostile situation the time taken to perform such an assessment is severely limited and a rapid and accurate response is vital. This paper describes the application of ANN to tactical sensor data fusion and the automated processing of the radar behaviors for various vehicle types. In particular the tasks of target and behavioral identification for both automated surveillance and support tasks are highlighted as important in the modern naval environment. The experimental research program divided the analysis of the radar tracks into three distinct categories. These were (1) target identification, (2) behavioral analysis (target task identification), and (3) threat assessment.
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Gary Whittington, Gary Whittington, C. Tim Spracklen, C. Tim Spracklen, J. M. Haugh, J. M. Haugh, Helen Faulkner, Helen Faulkner, } "Automated radar behavior analysis using neural network architectures", Proc. SPIE 1966, Science of Artificial Neural Networks II, (19 August 1993); doi: 10.1117/12.152615; https://doi.org/10.1117/12.152615

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