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Journal of the Royal Statistical Society Series B: Statistical Methodology, 2000 Summary In treating dynamic systems, sequential Monte Carlo methods use discrete samples to represent a complicated probability distribution and use rejection sampling, importance sampling and weighted resampling to complete the on-line ‘filtering’ task. We propose a special sequential Monte Carlo method, the mixture Kalman filter, which
Chen, Rong, Liu, Jun S.
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A review: state estimation based on hybrid models of Kalman filter and neural network
Systems Science & Control Engineering, 2023 In this paper, hybrid models of Kalman filter and neural network for state estimation are reviewed of their corresponding academic achievements, the creation of which is a noteworthy development in state estimation.
Shuo Feng +5 more
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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
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Application of H∞ Filter on the Angular Rate Matching in the Transfer Alignment
Discrete Dynamics in Nature and Society, 2016 The transfer alignment (TA) scheme is used for the initial alignment of Inertial Navigation System (INS) on dynamical base. The Kalman filter is often used in TA to improve the precision of TA.
Lijun Song, Zhongxing Duan, Jiwu Sun
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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
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Steady state Kalman filter design for cases and deaths prediction of Covid-19 in Greece
Results in Physics, 2021 In this work we study the applicability of the steady state Kalman filter in order to predict new cases and deaths of Covid-19. We use the actual observations of new cases and deaths. First, we deal with short term prediction, namely daily prediction. We
N. Assimakis +3 more
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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
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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 time‐varying, resulting in large positioning errors.
Xuming Fang, Dandan Huang
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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
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, 2000 As already pointed out in Hardle, Klinke, and Muller (2000, Chapter 10), state-space models are very useful and flexible in the sense that various recursive methods for time-dependent situations can be formulated as general solutions of filtering, smoothing and prediction problems in state-space models.
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