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But we have some results in other catalogs.Search results for: PARTICLE KALMAN FILTER
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Designing Particle Kalman Filter for Dynamic Positioning
PublicationThe article presents a comparative analysis of two variants of the Particle Kalman Filter designed by using two different ship motion models. The first filter bases only on the kinematic model of the ship and can be used in many types of vehicles, regardless of the vehicle dynamics model. The input value to the filter is the noisy position of the ship. The second filter makes use of the kinematic and dynamic models of the moving...
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Data fusion of GPS sensors using Particle Kalman Filter for ship dynamic positioning system
PublicationDepending on standards and class, dynamically positioned ships make use of different numbers of redundant sensors to determine current ship position. The paper presents a multi-sensor data fusion algorithm for the dynamic positioning system which allows it to record the proper signal from a number of sensors (GPS receivers). In the research, the Particle Kalman Filter with data fusion was used to estimate the position of the vessel....
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Particle Filter Modification using Kalman Optimal Filtering Method as Applied to Road Detection from Satellite Images
PublicationIn the paper recursive state estimation approach is presented as applied to satellite images. Especially, a model of dynamic systems of the non-linear and non-Gaussian systems is presented, and finally the Kalman filter and particle filter and an integration of both is figured out. Special attention is paid to the application for satellite image analysis.
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Estimation of a Stochastic Burgers' Equation Using an Ensemble Kalman Filter
PublicationIn this work, we consider a difficult problem of state estimation of nonlinear stochastic partial differential equations (SPDE) based on uncertain measurements. The presented solution uses the method of lines (MoL), which allows us to discretize a stochastic partial differential equation in a spatial dimension and represent it as a system of coupled continuous-time ordinary stochastic differential equations (SDE). For such a system...
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Decoupled Kalman filter based identification of time-varying FIR systems
PublicationWhen system parameters vary at a fast rate, identification schemes based on model-free local estimation approaches do not yield satisfactory results. In cases like this, more sophisticated parameter tracking procedures must be used, based on explicit models of parameter variation (often referred to as hypermodels), either deterministic or stochastic. Kalman filter trackers, which belong to the second category, are seldom used in...
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Tracking Moving Objects in Video Surveillance Systems with Kalman and Particle Filters – A Practical Approach
PublicationThis Chapter focuses on the first type of object tracking algorithms, namely on Kalman and particle filters. A theory of these algorithms may be found in many publications, there are also reports on implementation of these approaches to object tracking in video. However, developers of VCA systems still face two important problems. The first one is related to obtaining accurate measurements of positions and sizes of the tracked...
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Autonomous Ship Utility Model Parameter Estimation Utilising Extended Kalman Filter
PublicationIn this paper, a problem of autonomous ship utility model identification for control purposes is considered. In particular, the problem is formulated in terms of model parameter estimation (one-step-ahead prediction). This is a complex task due to lack of measurements of the parameter values, their time-variability and structural uncertainty introduced by the available models. In this work, authors consider and compare two utility...
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Multilevel inverter neutral-point voltage sensor diagnostic based on the Extended Kalman Filter
PublicationA new algorithm for neutral point voltage imbalance estimation in DC link of the three-level (3L) neutral point clamped (NPC) voltage source inverter (VSI) is proposed. Application of the proposed algorithm does not require any additional sensors. The unbalanced voltage calculation is based on the information derived from the inverter output measured currents and from the knowledge of the load model parameters. In order to estimate...
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An adaptive-noise Augmented Kalman Filter approach for input-state estimation in structural dynamics
PublicationThe establishment of a Digital Twin of an operating engineered system can increase the potency of Structural Health Monitoring (SHM) tools, which are then bestowed with enhanced predictive capabilities. This is particularly relevant for wind energy infrastructures, where the definition of remaining useful life is a main driver for assessing the efficacy of these systems. In order to ensure a proper representation of the physical...
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Performance evaluation of the parallel object tracking algorithm employing the particle filter
PublicationAn algorithm based on particle filters is employed to track moving objects in video streams from fixed and non-fixed cameras. Particle weighting is based on color histograms computed in the iHLS color space. Particle computations are parallelized with CUDA framework. The algorithm was tested on various GPU devices: a desktop GPU card, a mobile chipset and two embedded GPU platforms. The processing speed depending on the number...