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Review

2008

Review

2008

Optimal estimation problems for non-linear non-Gaussian state-space models do not typically admit analytic solutions. Since their… Expand

Highly Cited

2007

Highly Cited

2007

Recently, Rao-Blackwellized particle filters (RBPF) have been introduced as an effective means to solve the simultaneous… Expand

Review

2004

Review

2004

Part I Theoretical concepts: introduction suboptimal nonlinear filters a tutorial on particle filters Cramer-Rao bounds for… Expand

Highly Cited

2004

Highly Cited

2004

The problem of tracking a varying number of non-rigid objects has two major difficulties. First, the observation models and… Expand

Highly Cited

2003

Highly Cited

2003

Abstract Robust real-time tracking of non-rigid objects is a challenging task. Particle filtering has proven very successful for… Expand

Highly Cited

2003

Highly Cited

2003

Sequential Bayesian estimation for nonlinear dynamic state-space models involves recursive estimation of filtering and predictive… Expand

Review

2002

Review

2002

Increasingly, for many application areas, it is becoming important to include elements of nonlinearity and non-Gaussianity in… Expand

Highly Cited

2002

Highly Cited

2002

A framework for positioning, navigation, and tracking problems using particle filters (sequential Monte Carlo methods) is… Expand

Highly Cited

2000

Highly Cited

2000

In this paper, we propose a new particle filter based on sequential importance sampling. The algorithm uses a bank of unscented… Expand

Highly Cited

1999

Highly Cited

1999

This article analyses the recently suggested particle approach to filtering time series. We suggest that the algorithm is not… Expand