Results 81 to 90 of about 9,465 (199)
Sparsity-Based Kalman Filters for Data Assimilation [PDF]
, 2018 Several variations of the Kalman filter algorithm, such as the extended Kalman filter (EKF) and the unscented Kalman filter (UKF), are widely used in science and engineering applications.
Kang, Wei, Xu, Liang
core +1 more source
IET Generation, Transmission &Distribution, Volume 20, Issue 1, January/December 2026.This paper proposes a time‐varying inertia estimation framework based on sensitivity‐guided clustering and aggregation. It can achieve high‐accuracy inertia estimation with limited measurements, reducing the relative error by nearly 10% compared with existing methods, and exhibit strong robustness to noise and disturbances.
Yulong Li +6 more
wiley +1 more source
Adaptive High Manoeuvring Target Tracking Algorithm Based on CNN‐LSTM Fusion Architecture
IET Radar, Sonar &Navigation, Volume 20, Issue 1, January/December 2026.To solve the problems of model switching lag and tracking accuracy decline in interacting multiple model (IMM) algorithm in complex manoeuvring target tracking, an adaptive interacting multiple model unscented Kalman filter (IMM‐UKF) algorithm based on convolutional neural network and long short‐term memory network (CNN‐LSTM) fusion architecture is ...
Yuhan Cui +3 more
wiley +1 more source
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
A Probabilistic Perspective on Gaussian Filtering and Smoothing
, 2010 We present a general probabilistic perspective on Gaussian filtering and smoothing. This allows us to show that common approaches to Gaussian filtering/smoothing can be distinguished solely by their methods of computing/approximating the means and ...
Deisenroth, MP, Ohlsson, H
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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
OCP Based Online Multisensor Data Fusion for Autonomous Ground Vehicle [PDF]
, 2010 In this paper, online multisensor data fusion algorithm using CORBA event channel is proposed, in order to deal with simplifying problem in sensor registration and fusion for vehicle’s state estimation.
Syahroni, Nanang
core
Comparative Analysis to Determine the State of Charge of a Lithium‐Ion Cell
International Journal of Energy Research, Volume 2026, Issue 1, 2026.Accurate state of charge (SOC) estimation remains a challenge in lithium‐ion battery management systems (BMSs) due to the cells’ complex, nonlinear internal dynamics, and their high sensitivity to operating conditions. While most existing data‐driven studies rely on a core input configuration of voltage (V), current (I), and temperature (T), these ...
Hafsa Khayrane +5 more
wiley +1 more source
Szegő Quadrature Kalman Filter for Oscillatory Systems
IEEE Access, 2020 Filtering problems with oscillatory system dynamics commonly appear in real-life. However, the existing Gaussian filters, like the unscented Kalman filter (UKF), cubature Kalman filter CKF, Gauss-Hermite filter (GHF) and cubature quadrature Kalman filter
Abhinoy Kumar Singh
doaj +1 more source
Robust Filtering and Smoothing with Gaussian Processes
, 2012 We propose a principled algorithm for robust Bayesian filtering and smoothing in nonlinear stochastic dynamic systems when both the transition function and the measurement function are described by non-parametric Gaussian process (GP) models.
, +5 more
core +1 more source