A Note on the Reward Function for PHD Filters with Sensor Control

  title={A Note on the Reward Function for PHD Filters with Sensor Control},
  author={Branko Ristic and Ba-Ngu Vo and Daniel E. Clark},
  journal={IEEE Transactions on Aerospace and Electronic Systems},
The context is sensor control for multi-object Bayes filtering in the framework of partially observed Markov decision processes (POMDPs). The current information state is represented by the multi-object probability density function (pdf), while the reward function associated with each sensor control (action) is the information gain measured by the alpha or Rényi divergence. Assuming that both the predicted and updated state can be represented by independent identically distributed (IID… CONTINUE READING
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