Filters for spatial point processes

S.S. Singh, B. Vo, Adrian Baddeley, S. Zuyev

    Research output: Contribution to journalArticlepeer-review

    39 Citations (Scopus)


    We study the general problem of estimating a “hidden” point process X, giventhe realization of an “observed” point process Y (possibly defined in different spaces) with knownjoint distribution. We characterize the posterior distribution of X under marginal Poisson andGauss–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 thehidden process evolves in discrete time in a Markovian fashion. The dynamics of X considered aregeneral enough for many target tracking applications.
    Original languageEnglish
    Pages (from-to)2275-2295
    JournalSIAM Journal on Control and Optimization
    Issue number4
    Publication statusPublished - 2009


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