Results 41 to 50 of about 35,356 (190)

Adaptive Metropolis algorithm using variational Bayesian adaptive Kalman filter [PDF]

Computational Statistics & Data Analysis, 2015
Research paper: 30 pages, 10 ...
Mbalawata, Isambi S., Särkkä, Simo, Vihola, Matti, Haario, Heikki   +4 more
openaire   +6 more sources

Sequential linear filtering with non‐linear position and Doppler measurements for target tracking

IET Radar, Sonar & Navigation, 2022
For radar target tracking with non‐linear measurements, a sequential linear filtering method is proposed in this study, which includes a linear filter based on the position measurements and a linear sequential filter based on the range rate measurement ...
Ting Cheng, Lifu Li
doaj   +1 more source

Self-adaptive Kalman filter

Electronics Letters, 1979
It is shown how the refined instrumental variable (r.i.v.) method of recursive parameter estimation can be modified simply so that it functions as an optimal adaptive filter and state-estimation algorithm.
openaire   +1 more source

An Adaptive Kalman Filter for ECG Signal Enhancement [PDF]

IEEE Transactions on Biomedical Engineering, 2011
The ongoing trend of ECG monitoring techniques to become more ambulatory and less obtrusive generally comes at the expense of decreased signal quality. To enhance this quality, consecutive ECG complexes can be averaged triggered on the heartbeat, exploiting the quasi-periodicity of the ECG.
Vullings, R., Vries, de, B., Bergmans, J.W.M.   +2 more
openaire   +2 more sources

Improving the performance of GNSS precise point positioning by developed robust adaptive Kalman filter

Egyptian Journal of Remote Sensing and Space Sciences, 2022
Global Navigation Satellite Systems (GNSS) Precise Point Positioning (PPP) is a great precision positioning method based on GNSS. PPP based on multi-constellation GNSS uses the extended Kalman filter (EKF).
Ahmed Lotfy, Mohamed Abdelfatah, Gamal El-Fiky   +2 more
doaj   +1 more source

A Nonparametric Adaptive Nonlinear Statistical Filter

, 2014
We use statistical learning methods to construct an adaptive state estimator for nonlinear stochastic systems. Optimal state estimation, in the form of a Kalman filter, requires knowledge of the system's process and measurement uncertainty.
Busch, Michael, Moehlis, Jeff
core   +1 more source

Adaptive polynomial Kalman filter for nonlinear state estimation in modified AR time series with fixed coefficients

IET Control Theory & Applications
This article presents a novel approach for adaptive nonlinear state estimation in a modified autoregressive time series with fixed coefficients, leveraging an adaptive polynomial Kalman filter (APKF).
Dileep Sivaraman, Songpol Ongwattanakul, Branesh M. Pillai, Jackrit Suthakorn   +3 more
doaj   +1 more source

A Robust Hierarchical Estimation Scheme for Vehicle State Based on Maximum Correntropy Square-Root Cubature Kalman Filter

Entropy, 2023
Accurate acquisition of vehicle dynamics state information is essential for vehicle active safety control systems. However, these states cannot be easily measured, and the measurement is expensive.
Dengliang Qi, Jingan Feng, Yongbin Li, Lei Wang, Bao Song   +4 more
doaj   +1 more source

The Ensemble Kalman Filter: A Signal Processing Perspective

, 2017
The ensemble Kalman filter (EnKF) is a Monte Carlo based implementation of the Kalman filter (KF) for extremely high-dimensional, possibly nonlinear and non-Gaussian state estimation problems.
Fritsche, Carsten, Gustafsson, Fredrik, Hendeby, Gustaf, Roth, Michael   +3 more
core   +1 more source

Multi-Sensor Optimal Data Fusion Based on the Adaptive Fading Unscented Kalman Filter

Sensors, 2018
This paper presents a new optimal data fusion methodology based on the adaptive fading unscented Kalman filter for multi-sensor nonlinear stochastic systems.
Bingbing Gao, Gaoge Hu, Shesheng Gao, Yongmin Zhong, Chengfan Gu   +4 more
doaj   +1 more source