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Showing 1 to 20 of 768 for “"kalman"”.
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Robust credibility and Kalman filtering
… credibility models are presented via robust Kalman filtering. Credibility theory has been shown to be a special case of the Kalman filter (De Jong and Zehnwirth, 1983), thus existing research on the robustification of the Kalman filter, for example, Cipra and Romera (1991), can be applied to …
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Kalman filtering for aided inertial navigation system
This thesis develops a Kalman filter which integrates the inertial navigation system of the Vorticity Control Unmanned Undersea Vehicle (VCUUV) with redundant navigation sensor measurements. The model for the Kalman filter uses redundant measurements in a feedback loop to better estimate navigation …
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The path prediction of cyclones with Kalman filters
The Kalman filter is used to provide estimates of the position and velocity of a storm based upon observation of the storm's longitude and latitude. Nonstationary noise is shown to degrade the performance of the filter and cause tracking divergence. Time varying values for the noise covariance …
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Carbon Data Assimilation Using an Ensemble Kalman Filter
… ratio assimilation capability in an ensemble Kalman filter (EnKF) data assimilation system with the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem). In spite of its global coverage, the CO retrievals from the Measurements Of Pollution In The Troposphere (MOPITT) …
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Uncertain input estimation with application to Kalman tracking
… that account for uncertainty due to noise. The Kalman filter has been chosen in this study because of its ability to estimate tracking positions and to account for uncertainty in the tracked object's position where it is occluded by other stationary or moving objects. An inexpensive algorithm is …
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Techniques in Kalman Filtering for Autonomous Vehicle Navigation
… wheel speed sensors (WSS) using the framework of Kalman filtering (KF). To demonstrate the flexibility of the KF several methods are explored and implemented such as constraints, multi-rate data, and cascading filters to augment the measurement matrix of a main filter. GPS and IMU navigation are …
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Sparse Learning of Nonlinear PDE Dynamics using Kalman Smoothing
… minimization, or Savitzky-Golay filtering. Kalman smoothing, a classical approach for data assimilation with known noise statistics, has recently been incorporated into pysindy alongside hyperparameter optimization to enhance data denoising and improve differential equation discovery for …
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Application of the extended Kalman filter to enzyme reactions
… technique we use is the discrete extended Kalman filter. This method allows the use of an approximate model and partial measurements of process variables. To study the application of the discrete extended Kalman filter to a biological problem, we used two different enzyme reactions as model …
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Fault monitoring in hydraulic systems using unscented Kalman filter
… monitoring scheme based on the Unscented Kalman Filter (UKF) is developed. In simulations, both measurement and process noises are considered. The results show that the algorithm estimates the iii system states with acceptable residual errors. Therefore, the structure is verified to be …
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Anwendung des erweiterten KALMAN-Filters zur Zustandsbeobachtung in Biogasanlagen
… Die Arbeit „Anwendung des erweiterten KALMAN-Filters zur Zustandsbeobachtung in Biogasanlagen“ hat zum Ziel, den Stand der Technik in der Biogaserzeugung dahingehend weiter zu entwickeln, dass mittels einer softwarebasierten Systemlösung die für eine fundierte Einschätzung des …
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Exact Maximum Likelihood Estimation of the Kalman Filter Model
The interpretation of the Kalman filter model (KFM) used in this thesis is one where the transition equation allows the coefficients of a regression equation to follow an autoregressive-moving average process. Thus the KFM is a generalization of the random coefficients model.
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Kalman filtering of IMU sensor for robot balance control
This study explores the use of Kalman filtering of measurements from an inertial measurement unit (IMU) to provide information on the orientation of a robot for balance control. A test bed was created to characterize the random noise and errors inherent to orientation sensing in the MicroStrain …
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The adaptive Kalman filter and micromechanical inertial instrument performance
Thesis (M.S.)--Massachusetts Institute of Technology, Dept. of Aeronautics and Astronautics, 1993.
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Cooperative Decentralized Intersection Collision Avoidance Using Extended Kalman Filtering
… Second, a set of constrained, coupled Extended Kalman Filters (EKF) are used to predict the trajectory of the vehicles approaching an intersection in real-time. The coupled filters support decentralized operation and ensure that the optimization algorithm bases its decisions on good, reliable …
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Robust Kalman Filters Using Generalized Maximum Likelihood-Type Estimators
Estimation methods such as the Kalman filter identify best state estimates based on certain optimality criteria using a model of the system and the observations. A common assumption underlying the estimation is that the noise is Gaussian. In practical systems though, one quite frequently encounters …
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Dynamic OD Estimation with Bluetooth Data Using Kalman Filter
… data while estimating dynamic OD matrices using Kalman filter. We use OD proportions as state variables and travel times, link counts, Bluetooth OD matrix and input and exit volumes as measurements. A simulation experiment is conducted in VISSIM and is designed such that the traffic network …
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Kalman filtering techniques applied to the dynamic ship positioning problem
<p>The dynamic ship positioning problem using Kalman filtering techniques is considered. The main components of the system are discussed. The ship dynamics, based on a linearised model, are represented by state equations. These equations involve low and high frequency subsystems. A simplified …
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