Cognitive Fusion for Target Tracking

ebook Synthesis Lectures on Algorithms and Software in Engineering

By Ioannis Kyriakides

cover image of Cognitive Fusion for Target Tracking

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The adaptive configuration of nodes in a sensor network has the potential to improve sequential estimation performance by intelligently allocating limited sensor network resources. In addition, the use of heterogeneous sensing nodes provides a diversity of information that also enhances estimation performance. This work reviews cognitive systems and presents a cognitive fusion framework for sequential state estimation using adaptive configuration of heterogeneous sensing nodes and heterogeneous data fusion. This work also provides an application of cognitive fusion to the sequential estimation problem of target tracking using foveal and radar sensors.
Cognitive Fusion for Target Tracking