Results 91 to 100 of about 18,908 (211)
Comparisons on Kalman-Filter-Based Dynamic State Estimation Algorithms of Power Systems
IEEE Access, 2020 The Kalman-filter-based algorithms as the mainstream algorithms of dynamic state estimation of power systems have been extensively used to provide accurate data for power system applications. However, few comparisons are made to show their advantages and
Hui Liu +4 more
doaj +1 more source
Robust Filtering and Smoothing with Gaussian Processes
, 2012 We propose a principled algorithm for robust Bayesian filtering and smoothing in nonlinear stochastic dynamic systems when both the transition function and the measurement function are described by non-parametric Gaussian process (GP) models.
, +5 more
core +1 more source
Mixture truncated unscented Kalman filtering [PDF]
, 2012 This paper proposes a computationally efficient nonlinear filter that approximates the posterior probability density function (PDF) as a Gaussian mixture. The novelty of this filter lies in the update step. If the likelihood has a bounded support made up of different regions, we can use a modified prior PDF, which is a mixture, that meets Bayes' rule ...
García-Fernández, AF +2 more
openaire
Unscented Kalman filter for SINS alignment
Journal of Systems Engineering and Electronics, 2007 In order to improve the filter accuracy for the nonlinear error model of strapdown inertial navigation system (SINS) alignment, Unscented Kalman Filter (UKF) is presented for simulation with stationary base and moving base of SINS alignment. Simulation results show the superior performance of this approach when compared with classical suboptimal ...
Zhou Zhanxin, Gao Yanan, Chen Liabin
openaire +1 more source
, 2018 Kalman filters and observers are two main classes of dynamic state estimation (DSE) routines. Power system DSE has been implemented by various Kalman filters, such as the extended Kalman filter (EKF) and the unscented Kalman filter (UKF).
Qi, Junjian +2 more
core
On Approximate Nonlinear Gaussian Message Passing On Factor Graphs
, 2019 Factor graphs have recently gained increasing attention as a unified framework for representing and constructing algorithms for signal processing, estimation, and control. One capability that does not seem to be well explored within the factor graph tool
Hoffmann, Christian +2 more
core +1 more source
Journal of Aerospace Technology and Management, 2016 The non-linear estimators are certainly the most important algorithms applied to real problems, especially those involving the attitude estimation of spacecraft.
Roberta Veloso Garcia +2 more
doaj
Научный вестник МГТУ ГА, 2016 The paper contains algorithms for solving the problem of nonlinear filtering. The nonlinear approximate filters presented are: the extended Kalman filter (EKF), the uncented Kalman filter (UKF) and unscented Particle Filter (UPF). The flow-charts for the listed algorithms are presented and a corresponding software complex based on these algorithms is ...
openaire +1 more source
Research on a mixed prediction method to vehicle integrated navigation systems
International Journal of Advanced Robotic Systems, 2019 Aiming to improve the positioning accuracy of vehicle integrated navigation system (strapdown inertial navigation system/Global Positioning System) when Global Positioning System signal is blocked, a mixed prediction method combined with radial basis ...
Di Zhao, Huaming Qian, Dingjie Xu
doaj +1 more source
A Bayesian Filtering Algorithm for Gaussian Mixture Models
, 2017 A Bayesian filtering algorithm is developed for a class of state-space systems that can be modelled via Gaussian mixtures. In general, the exact solution to this filtering problem involves an exponential growth in the number of mixture terms and this is ...
Hendriks, Johannes +3 more
core