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The paper addresses distributed multitarget tracking over a network of heterogeneous and geographically dispersed nodes with sensing, communication and processing capabilities. The contribution has been to develop a novel consensus Gaussian Mixture-Cardinalized Probability Hypothesis Density (GM-CPHD) filter that provides a fully distributed, scalable and computationally efficient solution to the problem. The effectiveness of the proposed approach is demonstrated via simulation experiments on realistic scenarios.
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Giorgio Battistelli
University of Florence
Luigi Chisci
University of Florence
Claudio Fantacci
Vrije Universiteit Brussel
IEEE Journal of Selected Topics in Signal Processing
University of Florence
SELEX Sistemi Integrati
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Battistelli et al. (Thu,) studied this question.
synapsesocial.com/papers/6a0620462a787637a7bdd763 — DOI: https://doi.org/10.1109/jstsp.2013.2250911