Results 21 to 30 of about 15,255 (305)
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 New Strategy for Combining Nonlinear Kalman Filters With Smooth Variable Structure Filters
IEEE Access, 2023 Bayesian filters exemplified by the celebrated Kalman Filter (KF), and its non-linear variants rely on a fairly accurate state-space model of the system under study.
Salman Akhtar +3 more
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Multiplicative Kalman filtering [PDF]
TEST, 2010 We study a non-linear hidden Markov model, where the process of interest is the absolute value of a discretely observed Ornstein-Uhlenbeck diffusion, which is observed after a multiplicative perturbation. We obtain explicit formulae for the recursive relations which link the relevant conditional distributions.
Comte, Fabienne +2 more
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Quantitative verification of Kalman filters [PDF]
, 2021 Kalman filters are widely used for estimating the state of a system based on noisy or inaccurate sensor readings, for example in the control and navigation of vehicles or robots. However, numerical instability or modelling errors may lead to divergenceof
Parker, David +3 more
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The New Trend of State Estimation: From Model-Driven to Hybrid-Driven Methods
Sensors, 2021 State estimation is widely used in various automated systems, including IoT systems, unmanned systems, robots, etc. In traditional state estimation, measurement data are instantaneous and processed in real time.
Xue-Bo Jin +4 more
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Friction coefficient estimation using an unscented Kalman filter [PDF]
, 2014 The friction coefficient between a railway wheel and rail surface is a crucial factor in maintaining high acceleration and braking performance of railway vehicles; therefore, monitoring this friction coefficient is important.
Liang, Bo, Zhao, Yunshi, Iwnicki, Simon
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Global Systems for Mobile Position Tracking Using Kalman and Lainiotis Filters
The Scientific World Journal, 2014 We present two time invariant models for Global Systems for Mobile (GSM) position tracking, which describe the movement in x-axis and y-axis simultaneously or separately.
Nicholas Assimakis, Maria Adam
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Non-Linear Filtering for Precise Point Positioning GPS/INS integration [PDF]
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2014 This research investigates the performance of non-linear estimation filtering for GPS-PPP/MEMS-based inertial system. Although integrated GPS/INS system involves nonlinear motion state and measurement models, the most common estimation filter employed ...
M. Abd Rabbou, A. El-Rabbany
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Application of fractional sensor fusion algorithms for inertial mems sensing
Mathematical Modelling and Analysis, 2009 The work presents an extension of the conventional Kalman filtering concept for systems of fractional order (FOS). Modifications are introduced using the Grünwald‐Letnikov (GL) definition of the fractional derivative (FD) and corresponding truncation of ...
Michailas Romanovas +3 more
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Comparisons of nonlinear estimators for wastewater treatment plants
, 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 ...
Villanova, Ramon +2 more
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