Results 11 to 20 of about 75,448 (316)
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 +2 more sources
Predicting Time SeriesUsing an Automatic New Algorithm of the Kalman Filter
Mathematics, 2022 Time series forecasting is one of the main venues followed by researchers in all areas. For this reason, we develop a new Kalman filter approach, which we call the alternative Kalman filter. The search conditions associated with the standard deviation of
Juan D. Borrero, Jesus Mariscal
doaj +1 more source
SN Applied Sciences, 2022 In this paper, a risk sensitive estimator based on cubature quadrature Kalman filter is formulated and applied for tracking a ballistic object during its re-entry phase.
Swati
doaj +1 more source
Student’s t-Kernel-Based Maximum Correntropy Kalman Filter
Sensors, 2022 The state estimation problem is ubiquitous in many fields, and the common state estimation method is the Kalman filter. However, the Kalman filter is based on the mean square error criterion, which can only capture the second-order statistics of the ...
Hongliang Huang, Hai Zhang
doaj +1 more source
Machines, 2023 This paper analyzes the performance of Kalman filter-based estimators for robust filtering and rotor asymmetry detection in wound rotor induction machines (WRIMs) using real-time data. Filter models were designed based on an extended model of WRIMs.
Furzana John Basha, Kumar Somasundaram
doaj +1 more source
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 +1 more source
Filtering performance analyizing for Relative Navigation using Single Difference Carrier-Phase GPS [PDF]
Journal of Astronomy and Space Sciences, 2008 Satellite formation flying can provide the platform for interferometric observation to acquire the precise data and ensure the flexibility for space mission.
In-Kwan Park +4 more
doaj +1 more source
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. More recently, it has been used in some nonengineering applications such as short-term forecasting, time series,
openaire +3 more sources