Journal ArticleDOI
Recursive Bayesian estimation using piece-wise constant approximations
S. C. Kramer,H. W. Sorenson +1 more
Reads0
Chats0
TLDR
The numerical solution proposed here is obtained by modifying the recursion and using a simple piece-wise constant approximation to the density functions, yielding a bound on the maximum error growth, and a characterization of the situations with potential for large errors.About:
This article is published in Automatica.The article was published on 1988-11-01. It has received 146 citations till now. The article focuses on the topics: Recursive Bayesian estimation & Estimation theory.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.
Journal ArticleDOI
Improved particle filter for nonlinear 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.
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.
Journal Article
Particle filtering
Petar M. Djuric,J.H. Kotecha,Jianqui Zhang,Yufei Huang,Tadesse Ghirmai,Monica F. Bugallo,Joaquín Míguez +6 more
TL;DR: This work presents a brief review of particle filtering theory and shows how it can be used for resolving many problems in wireless communications, and demonstrates its application to blind equalization, blind detection over flat fading channels, multiuser detection, and estimation and detection of space-time codes in fading channels.
Journal ArticleDOI
Particle filter theory and practice with positioning applications
TL;DR: This tutorial serves two purposes: to survey the part of the theory that is most important for applications and to survey a number of illustrative positioning applications from which conclusions relevant for the theory can be drawn.
References
More filters
Journal ArticleDOI
Recursive bayesian estimation using gaussian sums
H. W. Sorenson,D. L. Alspach +1 more
TL;DR: A density approximation involving convex combinations of gaussian density functions is introduced and proposed as a meaningful way of circumventing the difficulties encountered in evaluating these relations and in using the resulting densities to determine specific estimation policies.
Book
Fast Algorithms for Digital Signal Processing
TL;DR: Fast algorithms for digital signal processing, Fast algorithms fordigital signal processing , and so on.
Journal ArticleDOI
A Bayesian approach to problems in stochastic estimation and control
Yu-Chi Ho,R. Lee +1 more
TL;DR: In this paper, a general class of stochastic estimation and control problems is formulated from the Bayesian Decision-Theoretic viewpoint, and a discussion as to how these problems can be solved step by step in principle and practice from this approach is presented.