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Filters for Spatial Point Processes

S. S. Singh ; B. N. Vo ; A. Baddeley ; Sergei Zuyev (Institutionen för matematiska vetenskaper, matematisk statistik)
SIAM Journal on Control and Optimization (0363-0129). Vol. 48 (2009), 4, p. 2275-2295.
[Artikel, refereegranskad vetenskaplig]

We study the general problem of estimating a "hidden" point process X, given the realization of an "observed" point process Y (possibly defined in different spaces) with known joint distribution. We characterize the posterior distribution of X under marginal Poisson and Gauss-Poisson priors and when the transformation from X to Y includes thinning, displacement, and augmentation with extra points. These results are then applied in a filtering context when the hidden process evolves in discrete time in a Markovian fashion. The dynamics of X considered are general enough for many target tracking applications.

Nyckelord: PHD filter, target tracking, hidden point process inference, online, filtering, Poisson point process prior, Gauss-Poisson point process, tracking

Denna post skapades 2010-02-26.
CPL Pubid: 115485


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Institutioner (Chalmers)

Institutionen för matematiska vetenskaper, matematisk statistik (2005-2016)



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