A review on Kalman filter models
Kalman Filter (KF) that is also known as linear quadratic estimation filter estimates current
states of a system through time as recursive using input measurements in mathematical …
states of a system through time as recursive using input measurements in mathematical …
[HTML][HTML] Evaluation of Advances in Battery Health Prediction for Electric Vehicles from Traditional Linear Filters to Latest Machine Learning Approaches
A Dineva - Batteries, 2024 - mdpi.com
In recent years, there has been growing interest in Li-ion battery State-of-Health (SOH)
estimation due to its critical role in ensuring the safe and reliable operation of Electric …
estimation due to its critical role in ensuring the safe and reliable operation of Electric …
Cubature Kalman filter with both adaptability and robustness for tightly-coupled GNSS/INS integration
Tightly-coupled GNSS/INS (Global Navigation Satellite System/Inertial Navigation System)
integration is of importance to vehicle positioning. However, this integration technology has …
integration is of importance to vehicle positioning. However, this integration technology has …
Cubature rule-based distributed optimal fusion with identification and prediction of kinematic model error for integrated UAV navigation
Abstract Integrated MIMU/GNSS/CNS (micro-electro-mechanical system-based inertial
measurement unit/global navigation satellite system/celestial navigation system) is a …
measurement unit/global navigation satellite system/celestial navigation system) is a …
Maximum likelihood principle and moving horizon estimation based adaptive unscented Kalman filter
The classical unscented Kalman filter (UKF) requires prior knowledge on statistical
characteristics of system noises for state estimation of a nonlinear dynamic system. If the …
characteristics of system noises for state estimation of a nonlinear dynamic system. If the …
A modified federated Student's t-based variational adaptive Kalman filter for multi-sensor information fusion
S Qiao, Y Fan, G Wang, H Zhang - Measurement, 2023 - Elsevier
To overcome the problem of poor performance of multi-sensor fusion algorithm in linear
systems with time-varying noise and outliers, a modified federated Student's t-based …
systems with time-varying noise and outliers, a modified federated Student's t-based …
Multi-sensor optimal data fusion for INS/GNSS/CNS integration based on unscented Kalman filter
This paper presents an unscented Kalman filter (UKF) based multi-sensor optimal data
fusion methodology for INS/GNSS/CNS (inertial navigation system/global navigation satellite …
fusion methodology for INS/GNSS/CNS (inertial navigation system/global navigation satellite …
Multi-sensor optimal data fusion based on the adaptive fading unscented Kalman filter
This paper presents a new optimal data fusion methodology based on the adaptive fading
unscented Kalman filter for multi-sensor nonlinear stochastic systems. This methodology has …
unscented Kalman filter for multi-sensor nonlinear stochastic systems. This methodology has …
Enhancing misbehavior detection in 5G vehicle-to-vehicle communications
Next-generation advanced driver-assistance systems (ADAS) and cooperative adaptive
cruise control (CACC) for advanced/autonomous driving are expected to increasingly use …
cruise control (CACC) for advanced/autonomous driving are expected to increasingly use …
Variational Bayesian-based robust cubature Kalman filter with application on SINS/GPS integrated navigation system
X Liu, X Liu, Y Yang, Y Guo, W Zhang - IEEE Sensors Journal, 2021 - ieeexplore.ieee.org
In this article, we focus on addressing the nonlinear filtering problem with unknown
measurement noise covariance and measurement outliers, which may be encountered in …
measurement noise covariance and measurement outliers, which may be encountered in …