Results 51 to 60 of about 3,341 (138)

A Tightly Coupled Fusion Positioning Method Based on Particle Filtering With Effective Particle Neighbourhood Attraction Optimisation

IET Radar, Sonar &Navigation, Volume 20, Issue 1, January/December 2026.
To address the limitations of existing wireless and inertial navigation systems, this paper proposes a high‐precision integrated positioning scheme based on particle filtering. The method introduces a high‐weight particle neighbourhood attraction mechanism to solve the common issue of particle degeneracy.
Yanbiao Gao, Zhongliang Deng
wiley   +1 more source

Student’s t‐Kernel‐Based Graph Signals Maximum Correntropy Unscented Kalman Filter Under Hybrid Cyberattacks

IET Signal Processing, Volume 2026, Issue 1, 2026.
The implementation of Kalman filter (KF) in tracking high‐dimensional, strongly correlated graph structured data is often complex and unstable. Meanwhile, in practical applications, the system may be subject to interference from non‐Gaussian noise and various cyberattacks.
Bingyu Yin, Xinmin Song, Wenling Li
wiley   +1 more source

Vision‐Based Aircraft Localization During the End Stage of Landing Approach via Runway Mark Determination

International Journal of Aerospace Engineering, Volume 2026, Issue 1, 2026.
Autonomous landing of aircraft during the approaching stage is a crucial part of the autonomous driving of aircraft. This paper mainly investigates the localization problem of aircraft during the end stage of the approaching process via a visual technique.
Chenglong Han, Zhuoyao He, Botao Duan, Hansong Xu, Jun Wu, Yuxiao Luo   +5 more
wiley   +1 more source

Model Predictive Torque Control of PMSM Based on Dynamic Forgetting Factor: Robustness and Dynamic Performance Improving

Journal of Engineering, Volume 2026, Issue 1, 2026.
In this paper, a model predictive torque control (MPTC) method based on dynamic forgetting factor (DFF) parameter recognition (DFF‐MPTC) is proposed to reduce the impact of time delay, nonlinearity and parameter mismatch on the performance of permanent magnet synchronous motor (PMSM) control system.
Jiajun Ruan, Yong Guo, Wei Zhang, Shikha Binwal   +3 more
wiley   +1 more source

Intelligent Vehicle Sideslip Angle Observation Strategy Based on Steady‐State Model and SCKF With Nonlinear Compensation

Journal of Engineering, Volume 2026, Issue 1, 2026.
Vehicle sideslip angle is one of the irreplaceable variable indicators for evaluating vehicle stability. However, it is difficult to directly measure vehicle sideslip angle with onboard sensors. In order to obtain precise vehicle sideslip angle using onboard sensors, a novel observation strategy based on fusion of steady‐state model method and square ...
Zhendong Zhu, Qiangqiang Yao, Yiheng Shi, Abdullah A. Kendoush   +3 more
wiley   +1 more source

A New Perspective and Extension of the Gaussian Filter

, 2015
The Gaussian Filter (GF) is one of the most widely used filtering algorithms; instances are the Extended Kalman Filter, the Unscented Kalman Filter and the Divided Difference Filter.
Kappler, Daniel, Schaal, Stefan, Trimpe, Sebastian, Wüthrich, Manuel   +3 more
core   +1 more source

Simulation‐Based Approaches to Thermal Estimation in Electric Vehicle Battery Cells

Modelling and Simulation in Engineering, Volume 2026, Issue 1, 2026.
This study presents a simulation‐based evaluation of a hybrid fiber Bragg grating (FBG) temperature estimation framework combining the extended Kalman filter (EKF) and unscented Kalman filter (UKF) for electric vehicle (EV) lithium‐ion battery cells. The work addresses key gaps in nonlinear thermal observability, robustness under high C‐rate excitation,
Kritzman P. Jooste, Ali Almaktoof, Mohamed T. Kahn, Marco Bonopera   +3 more
wiley   +1 more source

State-Space Inference and Learning with Gaussian Processes

, 2010
State-space inference and learning with Gaussian processes (GPs) is an unsolved problem. We propose a new, general methodology for inference and learning in nonlinear state-space models that are described probabilistically by non-parametric GP models. We
Deisenroth, MP, Rasmussen, CE, Turner, R
core  

Sequential Bayesian inference for static parameters in dynamic state space models [PDF]

, 2017
A method for sequential Bayesian inference of the static parameters of a dynamic state space model is proposed. The method is based on the observation that many dynamic state space models have a relatively small number of static parameters (or hyper ...
Bhattacharya, Arnab, Wilson, Simon
core  

A Novel Weighted Unscented Kalman Filter for Dynamic Load Identification

Structural Control and Health Monitoring, Volume 2026, Issue 1, 2026.
To address the limitations of traditional unscented Kalman filter (UKF)‐based algorithms—which typically require either additional displacement measurements or iterative optimization for load identification—this study proposes a fast and convenient load excitation identification algorithm.
Yanzhe Zhang, Bowen Zheng, Xiaoming Sun, Lina Guo, Yoshiki Ikeda   +4 more
wiley   +1 more source