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An algorithm for scheduling and control of passive sensors is proposed. This algorithm is based on a partially observed Markov decision process and an expected short- or long-term reward given by the sum of Renyi information divergences between Gaussian densities. This allows effective and efficient implementations and is demonstrated on simulations of situation scenarios of practical interest. The...
This paper presents algorithms for consistent joint localisation and tracking of multiple targets in wireless sensor networks under the decentralised data fusion (DDF) paradigm where particle representations of the state posteriors are communicated. This work differs from previous work as more generalised methods have been developed to account for correlated estimation errors that arise due to common...
Tracking multiple targets in a cluttered environment is a challenging task. Probabilistic multiple hypothesis tracking (PMHT) is an efficient approach for dealing with it. Essentially, PMHT is based on expectation-maximization for handling association conflicts. Linearity in the number of targets and measurements is the main motivation for a further development and extension of this methodology. However,...
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