Results 31 to 40 of about 3,255 (177)

Two-Step Adaptive Augmented Unscented Kalman Filter for Roll Angles of Spinning Missiles Based on Magnetometer Measurements

Measurement + Control, 2018
It is critical to measure the roll angle of a spinning missile quickly and accurately. Magnetometers are commonly used to implement these measurements.
Xiaolong Yan, Guoguang Chen, Xiaoli Tian
doaj   +1 more source

Neural Tractography Using an Unscented Kalman Filter [PDF]

, 2009
We describe a technique to simultaneously estimate a local neural fiber model and trace out its path. Existing techniques estimate the local fiber orientation at each voxel independently so there is no running knowledge of confidence in the estimated fiber model.
James G. Malcolm, Martha Elizabeth Shenton, Yogesh Rathi   +2 more
openaire   +4 more sources

A Widely Linear Complex Unscented Kalman Filter [PDF]

IEEE Signal Processing Letters, 2011
Conventional complex valued signal processing algorithms assume rotation invariant (circular) signal distributions, and are thus suboptimal for real world processes which exhibit rotation dependent distributions (noncircular). In nonlinear sequential state space estimation, noncircularity can arise from the data, state transition model, and state and ...
Dahir H. Dini, Danilo P. Mandic, Simon J. Julier   +2 more
openaire   +1 more source

A Simple Attitude Unscented Kalman Filter: Theory and Evaluation in a Magnetometer-Only Spacecraft Scenario

IEEE Access, 2016
A quaternion-based attitude unscented Kalman filter is formulated with quaternion errors parameterized by small angle approximations and is applied to a filter with a state vector consisting of the attitude quaternion and the gyro bias vector. The filter
Murty S. Challa, Jay G. Moore, Daniel J. Rogers   +2 more
doaj   +1 more source

UKF-Based Parameter Estimation and Identification for Permanent Magnet Synchronous Motor

Frontiers in Energy Research, 2022
The accuracy of rotor position estimation determines the performance of the sensorless control system of a permanent magnet synchronous motor. In order to realize the accurate control of rotor position and speed, it is necessary to identify the motor ...
Zhiwei Wang, Xin Liu, Wenzhuo Wang, Yunling Lv, Bo Yuan, Wujing Li, Qiufang Li, Shijie Wang, Qianchang Chen, Yi Zhang   +9 more
doaj   +1 more source

Inverse Unscented Kalman Filter

IEEE Transactions on Signal Processing
Rapid advances in designing cognitive and counter-adversarial systems have motivated the development of inverse Bayesian filters. In this setting, a cognitive 'adversary' tracks its target of interest via a stochastic framework such as a Kalman filter (KF).
Himali Singh, Kumar Vijay Mishra, Arpan Chattopadhyay   +2 more
openaire   +2 more sources

Construction and Method Study of the State of Charge Model for Lithium-Ion Packs in Electric Vehicles Using Ternary Lithium Packs as an Example

World Electric Vehicle Journal
Accurate and real-time estimation of pack system-level chips is essential for the performance and reliability of future electric vehicles. Firstly, this study constructed a model of a nickel manganese cobalt cell on the ground of the electrochemical ...
Yinquan Hu, Heping Liu, Hu Huang
doaj   +1 more source

A Novel Extended Unscented Kalman Filter Is Designed Using the Higher-Order Statistical Property of the Approximate Error of the System Model

Actuators
In the actual working environment, most equipment models present nonlinear characteristics. For nonlinear system filtering, filtering methods such as the Extended Kalman Filter (EKF), Unscented Kalman Filter (UKF), and Cubature Kalman Filter (CKF) have ...
Chengyi Li, Chenglin Wen
doaj   +1 more source

A comprehensive approach to predict a rocket's impact with stochastic estimators and artificial neural networks

IET Signal Processing, 2021
One of the current ways to continue space research is to launch ballistic rockets that carry scientific payloads. To improve the accuracy of the instantaneous evolution of the payload impact on the Earths surface, it is necessary to estimate indirect ...
Jose Abreu, Roberto L. Oliveira, Joao V. Fonseca Neto   +2 more
doaj   +1 more source

Multi‐Objective Bayesian Co‐Optimization of Parameterized Moving Horizon Estimation and Model Predictive Control

International Journal of Robust and Nonlinear Control, EarlyView.
ABSTRACT This paper proposes a Machine Learning (ML)‐enabled estimator‐controller design framework, in which a parameterized Model Predictive Controller (MPC) and a parameterized Moving Horizon Estimator (MHE) are jointly refined using Bayesian Optimization (BO).
Hossein Nejatbakhsh Esfahani, Javad Mohammadpour Velni   +1 more
wiley   +1 more source