Results 11 to 20 of about 402,870 (201)
Robust INS/GPS sensor fusion for UAV localization using SDRE nonlinear filtering [PDF]
, 2009 For publication in IEEE Sensors JournalThe aim of this paper is to present a new INS/GPS sensor fusion scheme, based on State-Dependent Riccati Equation (SDRE) nonlinear filtering, for Unmanned Aerial Vehicle (UAV) localization problem.
Aouf, Nabil, Nemra, A.
core +5 more sources
Physica D: Nonlinear Phenomena, 2001 The Kalman filter combines forecasts and new observations to obtain an estimation which is optimal in the sense of a minimum average quadratic error. The Kalman filter has two main restrictions: (i) the dynamical system is assumed linear and (ii) forecasting errors and observational noises are taken Gaussian.
Sornette, D., Ide, K.
openaire +4 more sources
The Salted Kalman Filter: Kalman filtering on hybrid dynamical systems
Automatica, 2021 Many state estimation and control algorithms require knowledge of how probability distributions propagate through dynamical systems. However, despite hybrid dynamical systems becoming increasingly important in many fields, there has been little work on utilizing the knowledge of how probability distributions map through hybrid transitions.
Nathan J. Kong +3 more
openaire +3 more sources
IEEE Signal Processing Letters, 2021 In this paper, a new filter in the nonlinear Kalman filtering framework is proposed. The new filter is referred to as the lattice Kalman filter (LKF) and is based on a class of quasi-Monte Carlo (QMC) methods known as lattice rules. The proposed LKF method uses the Korobov type lattice rule to deterministically generate sample points that are randomly ...
Abolfazl Rahimnejad +2 more
openaire +2 more sources
Multimodal Kalman filtering [PDF]
2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2016 A difficult aspect of multimodal estimation is the possible discrepancy between the sampling rates and/or the noise levels of the considered data. Many algorithms cope with these dissimilarities empirically. In this paper, we propose a conceptual analysis of multimodality where we try to find the "optimal" way of combining modalities. More specifically,
Bourrier, Anthony +3 more
openaire +3 more sources
Annual Review of Control, Robotics, and Autonomous Systems, 2018 The Kalman filter—or, more precisely, the extended Kalman filter (EKF)—is a fundamental engineering tool that is pervasively used in control and robotics and for various estimation tasks in autonomous systems. The recently developed field of invariant extended Kalman filtering uses the geometric structure of the state space and the dynamics to improve ...
Barrau, Axel, Bonnabel, Silvère
openaire +3 more sources
IEEE Transactions on Automatic Control, 2009 In this paper, we present a new nonlinear filter for high-dimensional state estimation, which we have named the cubature Kalman filter (CKF). The heart of the CKF is a spherical-radial cubature rule, which makes it possible to numerically compute multivariate moment integrals encountered in the nonlinear Bayesian filter. Specifically, we derive a third-
Ienkaran Arasaratnam, Simon Haykin 0001
openaire +2 more sources
Proceedings of the National Academy of Sciences, 2001 The Kalman Filter commonly employed by control engineers and other physical scientists has been successfully used in such diverse areas as the processing of signals in aerospace tracking and underwater sonar, and statistical quality control.
openaire +3 more sources
Journal of Research of the National Bureau of Standards, 1985 The increased power of small computers makes the use of parameter estimation methods attractive. Such methods have a number of uses in analytical chemistry. When valid models are available, many methods work well, but when models used in the estimation are in error, most methods fail.
Brown, Steven D., Rutan, Sarah C.
openaire +3 more sources