Results 231 to 240 of about 95,986 (277)

Smoothly Constrained Extended Kalman Filter

2020 15th IEEE International Conference on Signal Processing (ICSP), 2020
For nonlinear state estimate, the EKF is an effective technique the base point error should be noted. The paper proposes a smoothly constrained extended Kalman filter for the nonlinear Gaussian mode. The statistical noise of the system is modeled as a constrained mathematical model, the objective function is established based on the maximum posterior ...
Hongwei Zhang, Xiaohu Zhang, Weixin Xie, Jinliang Du   +3 more
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Bayesian filtering techniques: Kalman and extended Kalman filter basics

2009 19th International Conference Radioelektronika, 2009
Bayesian filters provide a statistical tool for dealing with measurement uncertainty. Bayesian filters estimate a state of dynamic system from noisy observations. These filters represent the state by random variable and in each time step probability distribution over random variable represents the uncertainty.
Jan Mochnac, Stanislav Marchevsky, Pavol Kocan   +2 more
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Terahertz Extended Kalman Filtering Method

2022 Photonics North (PN), 2022
Terahertz time domain spectroscopy (THz-TDS) is a well-established spectroscopy technique that can investigate modes of molecules, particularly in vapour. However, maximum detectable absorption is often low and depends on the dynamic range of the THz-TDS system and the thickness of the sample.
Spotts I, Brodie CH, Leclerc CA, Jahed N, Saeedkia D, Gadsden SA, Al-Shabi M, Collier CM   +7 more
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Synchronization through extended kalman filtering

2007
We study the synchronization problem in discrete-time via an extended Kalman filter (EKF). That is, synchronization is obtained of transmitter and receiver dynamics in case the receiver is given via an extended Kalman filter that is driven by a noisy drive signal from the transmitter.
Cruz, César, Nijmeijer, Henk
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The quadratic extended Kalman filter

Processing Workshop Proceedings, 2004 Sensor Array and Multichannel Signal, 2005
This paper extends the extended Kalman filter (EKF) to cover those scenarios in which the input signal is unknown and quadratic processing is required to estimate and track some parameters of interest. The optimal quadratic tracker is found to incorporate the fourth-order statistical knowledge about the excitation signal.
J. Villares, G. Vazquez
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A Factorized Extended Kalman Filter

SPIE Proceedings, 1986
Kalman filtering represents formidable computational linear algebra requirements for each new input measurement vector. The air-to-air missile guidance problem is addressed for which an extended Kalman filter (EKF) is required because the measurements are nonlinear in Cartesian coordinates. An explicit formulation is used.
James L. Fisher, David P. Casasent, Charles P. Neuman   +2 more
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Stable Robust Extended Kalman Filter

Journal of Aerospace Engineering, 2017
AbstractIn this paper, a stable and robust filter is proposed for structural identification. This filter resolves the instability problems of the traditional extended Kalman filter (EKF). Instead of ad hoc assignment of the noise covariance matrices in the EKF, the proposed stable robust extended Kalman filter (SREKF) provides real-time updating of the
He-Qing Mu, Sin-Chi Kuok, Ka-Veng Yuen
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The consistent extended Kalman filter

Proceedings of the 33rd Chinese Control Conference, 2014
This paper studies the consistency of the extended Kalman filter(EKF) for a general class of nonlinear systems. Based on the EKF algorithm, we propose the CEKF as well as the tuning law for its parameters. The consistency of CEKF is proved. Finally, the feasibility and consistency are illustrated by the numerical simulation for an example system.
Yanguang Jiang, Wenchao Xue, Yi Huang, Haitao Fang   +3 more
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Extended Kalman filter for extended object tracking

2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2017
In this work, we present a novel method for tracking an elliptical shape approximation of an extended object based on a varying number of spatially distributed measurements. For this purpose, an explicit nonlinear measurement equation is formulated that relates the kinematic and shape parameters to a measurement by means of a multiplicative noise term.
Shishan Yang, Marcus Baum
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2010
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