Open AccessJournal Article
Bayes Theorem and Digital Realizations for Non-Linear Filters
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This article is published in Journal of The Astronautical Sciences.The article was published on 1969-09-01 and is currently open access. It has received 49 citations till now. The article focuses on the topics: Bayes' theorem.read more
Citations
More filters
Journal ArticleDOI
Novel approach to nonlinear/non-Gaussian Bayesian state estimation
TL;DR: An algorithm, the bootstrap filter, is proposed for implementing recursive Bayesian filters, represented as a set of random samples, which are updated and propagated by the algorithm.
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C ONDENSATION —Conditional Density Propagation forVisual Tracking
Michael Isard,Andrew Blake +1 more
TL;DR: The Condensation algorithm uses “factored sampling”, previously applied to the interpretation of static images, in which the probability distribution of possible interpretations is represented by a randomly generated set.
Proceedings ArticleDOI
Monte Carlo localization for mobile robots
TL;DR: The Monte Carlo localization method is introduced, where the probability density is represented by maintaining a set of samples that are randomly drawn from it, and it is shown that the resulting method is able to efficiently localize a mobile robot without knowledge of its starting location.
Journal ArticleDOI
Gaussian particle filtering
J.H. Kotecha,Petar M. Djuric +1 more
TL;DR: It is shown that under theGaussianity assumption, the Gaussian particle filter is asymptotically optimal in the number of particles and, hence, has much-improved performance and versatility over other Gaussian filters, especially when nontrivial nonlinearities are present.
An improved particle filter for non-linear problems
TL;DR: In this article, a method of monitoring the efficiency of particle filters is introduced which provides a simple quantitative assessment of sample impoverishment and the authors show how to construct improved particle filters that are both structurally efficient in terms of preventing the collapse of the particle system and computationally efficient in their implementation.