Results 51 to 60 of about 3,255 (177)

FILTERING FEATURES FOR TRACKING OF SPIRALING REENTRY VEHICLES

open access: yesДоклады Белорусского государственного университета информатики и радиоэлектроники, 2019
The target dynamics model for tracking of spiraling reentry vehicles is considered. The features of Extended Kalman filter modification and Unscented Kalman filter are listed.
A. S. Solonar, P. A. Khmarski
doaj  

Unscented Kalman Filter Based Attitude Estimation of a Quadrotor

open access: yesHavacılık ve Uzay Teknolojileri Dergisi, 2021
Quadrotors are well - known unmanned aerial vehicle structures that have some advantages such as hovering, vertical take – off and landing, and low – speed flight. On the other hand, quadrotors are subjected to modeling and sensor uncertainties that lead
Aziz Kaba
doaj  

A Neural Network‐Based Self‐Sensing Embedded Position Control System for Shape Memory Alloy Wire Actuators

open access: yesAdvanced Intelligent Systems, Volume 8, Issue 4, April 2026.
Shape memory alloy wires exhibit thermally induced phase changes that generate actuation strain and resistance variations enabling self‐sensing. However, hysteretic electromechanical behavior complicates accurate state estimation. This paper presents an artificial in‐based self‐sensing method to reconstruct SMA actuator position in real time, achieving
Krunal Koshiya   +2 more
wiley   +1 more source

Verification of a Fluid–Structure Interaction Model for Aortic Stenosis Through Comparison With In Vitro Experiments

open access: yesInternational Journal for Numerical Methods in Biomedical Engineering, Volume 42, Issue 4, April 2026.
A patient‐specific Fluid–structure Interaction (FSI) model of aortic stenosis was verified against in vitro experiments using a mock‐loop circulatory system with patient‐specific calcified and non‐calcified valve models under varying flow conditions. The in vitro experiments were replicated in the FSI model.
Sabine Verstraeten   +9 more
wiley   +1 more source

Polynomial Updates for the Unscented Kalman Filter

open access: yesCoRR
38 pages, 9 ...
Chiran Cherian, Simone Servadio
openaire   +2 more sources

Remaining Useful Life (RUL) Prediction Methods for Machine Health Estimation and Fault Diagnosis: A Comprehensive Review of Latest Techniques and Future Prospects

open access: yesEngineering Reports, Volume 8, Issue 4, April 2026.
A comprehensive review of model‐based, data‐driven, and hybrid approaches for Remaining Useful Life (RUL) prediction, emphasizing their role in predictive maintenance, fault diagnosis, and enhancing industrial reliability. ABSTRACT This paper aims to provide a state‐of‐the‐art review of the most recent Remaining Useful Life (RUL) prediction methods ...
Arslan Ahmed Amin   +4 more
wiley   +1 more source

Robust Derivative Unscented Kalman Filter Under Non-Gaussian Noise

open access: yesIEEE Access, 2018
A robust derivative unscented Kalman filter is proposed for a nonlinear system with non-Gaussian noise and outliers based on Huber function. In this paper, the time update process can be performed using a Kalman filter (KF), and measurement update ...
Lijian Yin   +4 more
doaj   +1 more source

An Integrated Deep Ensemble-Unscented Kalman Filter for Sideslip Angle Estimation With Sensor Filtering Network

open access: yesIEEE Access, 2021
An integration scheme for sideslip angle estimation is proposed where a deep neural network and a simple kinematics-based model are combined in an unscented Kalman filter.
Dongchan Kim   +3 more
doaj   +1 more source

Unscented Kalman filter‐aided Gaussian sum filter

open access: yesIET Radar, Sonar & Navigation, 2015
A non‐linear filter is developed for continuous‐time systems with observations/measurements carried out in discrete‐time. The filter developed can approximate the a priori and a posteriori probability density function (pdf) with weighted Gaussian sums inside specific search regions.
Gokce, Murat, Kuzuoglu, Mustafa
openaire   +2 more sources

Unscented Kalman Filtering for Articulated Human Tracking [PDF]

open access: yes, 2011
We present an articulated tracking system working with data from a single narrow baseline stereo camera. The use of stereo data allows for some depth disambiguation, a common issue in articulated tracking, which in turn yields likelihoods that are practically unimodal.
Anders Boesen Lindbo Larsen   +2 more
openaire   +2 more sources

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