A note on the reward function for PHD filters with sensor control

Ristic, B, Vo, B and Clark, D 2011, 'A note on the reward function for PHD filters with sensor control', IEEE Transactions on Aerospace and Electronic Systems, vol. 47, no. 2, pp. 1521-1529.

Document type: Journal Article
Collection: Journal Articles

Title A note on the reward function for PHD filters with sensor control
Author(s) Ristic, B
Vo, B
Clark, D
Year 2011
Journal name IEEE Transactions on Aerospace and Electronic Systems
Volume number 47
Issue number 2
Start page 1521
End page 1529
Total pages 9
Publisher Institute of Electrical and Electronics Engineers
Abstract 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) cluster random finite sets (RFSs) or, as a special case, the Poisson RFSs, this work derives the analytic expressions of the corresponding Rényi divergence based information gains. The implementation of Rényi divergence via the sequential Monte Carlo method is presented. The performance of the proposed reward function is demonstrated by a numerical example, where a moving range-only sensor is controlled to estimate the number and the states of several moving objects using the PHD filter.
Subject Aerospace Engineering not elsewhere classified
DOI - identifier 10.1109/TAES.2011.5751278
Copyright notice © 2011 IEEE
ISSN 0018-9251
Version Filter Type
Citation counts: TR Web of Science Citation Count  Cited 70 times in Thomson Reuters Web of Science Article | Citations
Scopus Citation Count Cited 55 times in Scopus Article | Citations
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