Sigma-point kalman filters for probabilistic inference in dynamic state-space models

By Rudolph van der Merwe, Eric A. Wan. 2004

1,222 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/964fb2468999c074def91d9463bc1d4c1203ebb8

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Citations in the corpus

On Unscented Kalman Filtering for State Estimation of Continuous-Time Nonlinear Systems (2007, methodology): “To enhance the numerical stability of the update equations, square root versions [4], [43] of the UKF update step can also be used.”
A Numerical-Integration Perspective on Gaussian Filters (2006, methodology): “Since the UKF3, UKF5, DDF2/CDF1, CDF2, and 3-point GHF are quite similar in accuracy, Fig.”
RSSI-Based Indoor Localization and Tracking Using Sigma-Point Kalman Smoothers (2009, methodology): “Under a pure linear and Gaussian assumption, the Kalman filter provides an efficient and analytical solution for the posterior distribution [29], [37].”
Applying the unscented Kalman filter for nonlinear state estimation (2008, methodology): “where Si is the ith column of the matrix, S 1⁄4 ffiffiffiffiffiffiffiffiffi P k 1 p : In (9) c is a scaling parameter [8], c 1⁄4 ffiffiffiffiffiffiffiffiffiffiffiffi N þ k p ; k 1⁄4 a(2)ðN þ jÞ N ;”
Development of a UAV-LiDAR System with Application to Forest Inventory (2012, methodology): “A quaternion representation of orientation is used to avoid singularities which can occur in alternate representations of orientation, following Shin [23], Van Der Merwe and Wan [33], Crassidis [35].”
Unscented Kalman filtering for nonlinear structural dynamics (2007, methodology): “Various alternative flltering procedures have been recently proposed to improve the EKF: surveys can be found, e.g., in [34,35, 18 ].”
Adaptive sequential Monte Carlo by means of mixture of experts (2011, methodology): “A similar approach based on the unscented Kalman filter was proposed by Van der Merwe et al. (2000) (see also Van der Merwe and Wan, 2003).”
State of charge estimation using an unscented filter for high power lithium ion cells (2010, methodology): “The unscented filter does not require the linearization of the system equations [34] and is hence more suitable for state estimates using the highly non-linear set of equations employed to simulate battery performance at high charge/discharge rates (e.”
A novel multistage Support Vector Machine based approach for Li ion battery remaining useful life estimation (2015, background): “In [18], EKF is used with KF in a dual filtering framework, where KF is used for SOC estimation and EKF for SOH estimation of a lead acid battery.”