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Group and extended object tracking

The problem of tracking point targets moving in a group, or features of an extended object, is formulated via a general two component model. An example involving translation, scaling, rotation and pattern distortion is presented. It is assumed that measurements of the points are unlabelled, which, together with a significant clutter level, leads to measurement association uncertainty. A Bayesian bootstrap filter is used to implement a nonlinear, multiple hypothesis, recursive estimator.