Journal ArticleDOI
Brief paper: Adaptive divided difference filtering for simultaneous state and parameter estimation
TLDR
A novel adaptive version of the divided difference filter applicable to non-linear systems with a linear output equation is presented in this work, which demonstrates the superior performance of the proposed filter as compared to the standard DDF.About:
This article is published in Automatica.The article was published on 2009-07-01. It has received 62 citations till now. The article focuses on the topics: Adaptive filter & Kernel adaptive filter.read more
Citations
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Journal ArticleDOI
Gaussian Smoothers for Nonlinear Systems With One-Step Randomly Delayed Measurements
TL;DR: This technical note is concerned with the nonlinear state smoothing problem in the case that the measurements are randomly delayed by one sampling time, and two general Gaussian approximation and Gaussian mixture approximation smoothers are proposed in minimum mean square error (MMSE) sense.
Journal ArticleDOI
A Gaussian approximation recursive filter for nonlinear systems with correlated noises
TL;DR: A general GASF framework in the minimum mean square error (MMSE) sense is derived and the implementation is transformed into computing the multi-dimensional integrals, which is solved by developing a new divided difference filter (DDF) with correlated noises.
Journal ArticleDOI
Kalman filter with both adaptivity and robustness
TL;DR: A heuristic method of recursively choosing among the adaptive, the robust, and the standard Kalman filter approaches in the occurrence of abnormal innovations is proposed through incorporating the observations at the next instance.
Journal ArticleDOI
Multisensor Nonlinear Fusion Methods Based on Adaptive Ensemble Fifth-Degree Iterated Cubature Information Filter for Biomechatronics
TL;DR: The results show some basic conclusions existed in linear fusion theory are no longer valid for nonlinear systems and the conclusions based on the EKF are still available for more complex nonlinear filters.
Journal ArticleDOI
Adaptive robust Kalman filter for relative navigation using global position system
TL;DR: In this article, an adaptive robust Kalman filter algorithm is derived to account for both process noise and measurement noise uncertainty, which is successfully implemented in relative navigation using global position system for spacecraft formation flying in low earth orbit, with real-orbit perturbations and non-Gaussian random measurement errors.
References
More filters
Journal ArticleDOI
Unscented filtering and nonlinear estimation
Simon Julier,Jeffrey Uhlmann +1 more
TL;DR: The motivation, development, use, and implications of the UT are reviewed, which show it to be more accurate, easier to implement, and uses the same order of calculations as linearization.
Book
Optimal State Estimation: Kalman, H Infinity, and Nonlinear Approaches
TL;DR: With its expert blend of theory and practice, coupled with its presentation of recent research results, Optimal State Estimation is strongly recommended for undergraduate and graduate-level courses in optimal control and state estimation theory.
Journal ArticleDOI
On the identification of variances and adaptive Kalman filtering
TL;DR: In this paper, it was shown that the steady-state optimal Kalman filter gain depends only on n \times r linear functionals of the covariance matrix and the number of unknown elements in the matrix.
Journal ArticleDOI
Asymptotic behavior of the extended Kalman filter as a parameter estimator for linear systems
TL;DR: In this paper, a convergence analysis of the extended Kalman filter for nonlinear systems with unknown parameters is given, and it is shown that in general the estimates may be biased or divergent and the causes for this are displayed.