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Dynamic Group Tracking

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If you have a question about this talk, please contact Taylan Cemgil.

For many surveillance applications, targets of interest tend to travel in groups; for example, a group of aircraft moving in a tight formation or a convoy of vehicles moving along a road. There are two principal reasons why we wish to model explicitly the behaviour of groups, as opposed to treating all objects independently as in most multiple target tracking approaches. The first is that the joint tracking of (a priori) dependent objects within a group will lead to greater detection and tracking ability in hostile environments with high noise and low detection probabilities. For example, if we know several targets are in a group formation, then we can infer some information of the positions and speed of those targets with missing measurements due to poor detection probability, given those target measurements that we do have. Similarly, if a newly detected target appears close to an existing group, the target can be initialized using the group velocity. Secondly, we may hope to be able to infer automatically which objects are moving in formation as a group, and which are not. Thus we may be able to group objects according to intentionality, behaviour and friend or foe, all highly desirable inference outcomes for the modern tracking application.

In this talk, we will define the problem of dynamic group tracking. We will introduce the group dynamical models from a continuous time setting, the interaction models for closely spaced targets as well as a group structure transition model. We will simultaneously tackle the problem of group structure inference and joint detection and tracking for group and individual targets within a Bayesian filtering framework. We will present some tracking results based on simulations as well as data from an actual GMTI radar.

This talk is part of the Signal Processing and Communications Lab Seminars series.

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