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Optimal estimation problems for non-linear non-Gaussian state-space models do not typically admit analytic solutions. Since their… Expand Recently, Rao-Blackwellized particle filters (RBPF) have been introduced as an effective means to solve the simultaneous… Expand Part I Theoretical concepts: introduction suboptimal nonlinear filters a tutorial on particle filters Cramer-Rao bounds for… Expand The problem of tracking a varying number of non-rigid objects has two major difficulties. First, the observation models and… Expand Abstract Robust real-time tracking of non-rigid objects is a challenging task. Particle filtering has proven very successful for… Expand Sequential Bayesian estimation for nonlinear dynamic state-space models involves recursive estimation of filtering and predictive… Expand Increasingly, for many application areas, it is becoming important to include elements of nonlinearity and non-Gaussianity in… Expand A framework for positioning, navigation, and tracking problems using particle filters (sequential Monte Carlo methods) is… Expand In this paper, we propose a new particle filter based on sequential importance sampling. The algorithm uses a bank of unscented… Expand This article analyses the recently suggested particle approach to filtering time series. We suggest that the algorithm is not… Expand