Results 11 to 20 of about 25,371 (266)

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

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, Amblard, Pierre-Olivier, Michel, Olivier, Jutten, Christian   +3 more
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Sample Regenerating Particle Filter Combined With Unequal Weight Ensemble Kalman Filter for Nonlinear Systems

IEEE Access, 2021
We present an approach which combines the sample regenerating particle filter (SRGPF) and unequal weight ensemble Kalman filter (UwEnKF) to obtain a more accurate forecast for nonlinear dynamic systems.
Xiao Li, Ai Jie Cheng, Hai Xiang Lin
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Nonlinear robust estimation for tracking of ballistic target using risk sensitive cubature quadrature Kalman filter

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
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Rotor Asymmetry Detection in Wound Rotor Induction Motor Using Kalman Filter Variants and Investigations on Their Robustness: An Experimental Implementation

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
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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
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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, Sang-Young Park, Kyu-Hong Choi, Sungki Cho, Jong-Uk Park   +4 more
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Graph Kalman Filters

CoRR, 2023
Added empirical ...
Cesare Alippi, Daniele Zambon
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A note on Kalman Filter [PDF]

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

Auto‐calibration Kalman filters for non‐linear systems with direct feedthrough

IET Control Theory & Applications, 2021
The problem of state estimation for non‐linear systems with unknown inputs is discussed. The objective is to construct a non‐linear filter where the unknown input affects both the state equation and measurement equation. An auto‐calibration Kalman filter
Yi Cui, Zhihua Wang
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