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Kalman filtering in extended noise environments
IEEE Transactions on Automatic Control, 2005This note introduces an extended environment for Kalman filtering that considers also the presence of additive noise on input observations in order to solve the problem of optimal (minimal variance) estimation of noise-corrupted input and output sequences.
DIVERSI, ROBERTO +2 more
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On designing consistent extended Kalman filter
Journal of Systems Science and Complexity, 2017zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Yanguang Jiang +3 more
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An extended Kalman filter for mouse tracking
Medical & Biological Engineering & Computing, 2018Animal tracking is an important tool for observing behavior, which is useful in various research areas. Animal specimens can be tracked using dynamic models and observation models that require several types of data. Tracking mouse has several barriers due to the physical characteristics of the mouse, their unpredictable movement, and cluttered ...
Hongjun Choi, Mingi Kim, Onseok Lee
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Stability of distributed extended Kalman filters
2017 22nd International Conference on Digital Signal Processing (DSP), 2017The need for faster and more robust parameter estimates in the smart grid, together with the growth in multi-sensor distributed measurements has motivated the development of distributed extended Kalman filtering (EKF) algorithms. However, fundamental theoretical insights about the convergence and stability of these distributed extended Kalman filtering
Sithan Kanna, Danilo P. Mandic
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Bayesian filtering techniques: Kalman and extended Kalman filter basics
2009 19th International Conference Radioelektronika, 2009Bayesian 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 +2 more
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Performance evaluation of the Extended Kalman Filter and Unscented Kalman Filter
2015 International Conference on Unmanned Aircraft Systems (ICUAS), 2015The Extended Kalman Filter (EKF) and Unscented Kalman Filter (UKF) are methods usually applied in the sensor fusion for Unmanned Aerial Vehicles due to its nonlinear navigation equations. This paper presents a comparison between the two filters considering the position, velocity and attitude of the vehicle and the IMU bias.
Natassya B. F. da Silva +2 more
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Evaluation of Unscented Kalman Filter and Extended Kalman Filter for Radar Tracking Data Filtering
2014 European Modelling Symposium, 2014This paper focuses on the issue of nonlinear data filtering in radar tracking. Through the analysis on the extended Kalman filter (EKF) and the unscented Kalman filter (UKF), which are both nonlinear filters, we find that the accuracy of the extended Kalman filtered data image was not ideal for radar tracking data filtering, while UKF can achieve ...
Jihong Shen +3 more
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A MODULAR IMPLEMENTATION OF THE EXTENDED KALMAN FILTER
IFAC Proceedings Volumes, 1988Abstract A number of dynamic simulation packages offer the possibilty to build up large systems by connecting smaller modules together. Each module then contains the algebraic and difference or differential equations for a part of the system. For the extended Kalman filter the partial derivatives of the process model equations are needed for the ...
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Synchronization through extended kalman filtering
2007We 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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International Journal of Dynamics and Control, 2019
In this paper, based on Modal series, a new filter is proposed for a nonlinear system state estimation. Modal series is a new method to obtain a closed-form approximate solution of a nonlinear differential equation. Up to now, this series is only obtained in the neighborhood of an equilibrium point.
Gh. Mohammaddadi, N. Pariz, A. Karimpour
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In this paper, based on Modal series, a new filter is proposed for a nonlinear system state estimation. Modal series is a new method to obtain a closed-form approximate solution of a nonlinear differential equation. Up to now, this series is only obtained in the neighborhood of an equilibrium point.
Gh. Mohammaddadi, N. Pariz, A. Karimpour
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