Results 31 to 40 of about 1,778,758 (298)
Comparisons of nonlinear estimators for wastewater treatment plants [PDF]
, 2012 This paper deals with five existing nonlinear estimators (filters), which include Extended Kalman Filter (EKF), Extended H-infinity Filter (EHF), State Dependent Filter (SDF), State Dependent H-Infinity Filter (SDHF) and Unscented Kalman Filter (UKF ...
Abdul Wahab, Hamimi Fadziati Binti +2 more
core +1 more source
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 +2 more
doaj +1 more source
Optimized Design of 3D Spatial Images Based on Kalman Filter Equation
Advances in Mathematical Physics, 2021 This paper takes the advantageous ability of Kalman filter equation as a means to jointly realize the accurate and reliable extraction of 3D spatial information and carries out the research work from the extraction of 3D spatial position information from
Wei Shan
doaj +1 more source
Kalman Filters on Differentiable Manifolds [PDF]
arXiv, 2021 Kalman filter is presumably one of the most important and extensively used filtering techniques in modern control systems. Yet, nearly all current variants of Kalman filters are formulated in the Euclidean space $\mathbb{R}^n$, while many real-world systems (e.g., robotic systems) are really evolving on manifolds.
arxiv
Adaptive adjustment of noise covariance in Kalman filter for dynamic state estimation [PDF]
IEEE Power & Energy Society General Meeting, 2017 Accurate estimation of the dynamic states of a synchronous machine (e.g., rotor's angle and speed) is essential in monitoring and controlling transient stability of a power system.
S. Akhlaghi, N. Zhou, Zhenyu Huang
semanticscholar +1 more source
Improvement of ECG Signal Noise Removal Using Recursive Kalman Filter [PDF]
Journal of Intelligent Procedures in Electrical Technology, 2011 Nowadays, Kalman filter has been wildly used for solving the problem of real world. Kalman filter is a recursive filter that estimates the state of a linear dynamic system from a series of noisy measurements.
Sara Moein, Zahra Beheshti
doaj
IET Radar, Sonar & Navigation, 2023 The existing adaptive Kalman filters for tracking manoeuvring targets by wireless sensor networks can easily lose robustness when both the measurement and process noises are unknown and timeâvarying, resulting in large positioning errors.
Xuming Fang, Dandan Huang
doaj +1 more source
Eye Tracking Algorithm Based on Multi Model Kalman Filter
HighTech and Innovation Journal, 2022 One of the most important pieces of Human Machine Interface (HMI) equipment is an eye tracking system that is used for many different applications. This paper aims to present an algorithm in order to improve the efficiency of eye tracking in the image by
S. H. Ziafati Bagherzadeh, S. Toosizadeh
doaj +1 more source
Exactly Decoupled Kalman Filtering for Multitarget State Estimation with Sensor Bias [PDF]
IEEE Transactions on Aerospace and Electronic Systems, 2019, 2018 The problem of multisensor multitarget state estimation in the presence of constant but unknown sensor biases is investigated. The classical approach to this problem is to augment the state vector to include the states of all the targets and the sensor biases, and then implement an augmented state Kalman filter (ASKF). In this paper, we propose a novel
arxiv +1 more source
A comparison of assimilation results from the ensemble Kalman Filter and a reduced-rank extended Kalman Filter [PDF]
Nonlinear Processes in Geophysics, 2003 The goal of this study is to compare the performances of the ensemble Kalman filter and a reduced-rank extended Kalman filter when applied to different dynamic regimes.
X. Zang, P. Malanotte-Rizzoli
doaj