Current Search: Kalman Filter (x)
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- Title
- RR INTERVAL ESTIMATION FROM AN ECG USING A LINEAR DISCRETE KALMAN FILTER.
- Creator
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Janapala, Arun, WEEKS, ARTHUR, University of Central Florida
- Abstract / Description
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An electrocardiogram (ECG) is used to monitor the activity of the heart. The human heart beats seventy times on an average per minute. The rate at which a human heart beats can exhibit a periodic variation. This is known as heart rate variability (HRV). Heart rate variability is an important measurement that can predict the survival after a heart attack. Studies have shown that reduced HRV predicts sudden death in patients with Myocardial Infarction (MI). The time interval between each beat...
Show moreAn electrocardiogram (ECG) is used to monitor the activity of the heart. The human heart beats seventy times on an average per minute. The rate at which a human heart beats can exhibit a periodic variation. This is known as heart rate variability (HRV). Heart rate variability is an important measurement that can predict the survival after a heart attack. Studies have shown that reduced HRV predicts sudden death in patients with Myocardial Infarction (MI). The time interval between each beat is called an RR interval, where the heart rate is given by the reciprocal of the RR interval expressed in beats per minute. For a deeper insight into the dynamics underlying the beat to beat RR variations and for understanding the overall variance in HRV, an accurate method of estimating the RR interval must be obtained. Before an HRV computation can be obtained the quality of the RR interval data obtained must be good and reliable. Most QRS detection algorithms can easily miss a QRS pulse producing unreliable RR interval values. Therefore it is necessary to estimate the RR interval in the presence of missing QRS beats. The approach in this thesis is to apply KALMAN estimation algorithm to the RR interval data calculated from the ECG. The goal is to improve the RR interval values obtained from missed beats of ECG data.
Show less - Date Issued
- 2005
- Identifier
- CFE0000340, ucf:46279
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0000340
- Title
- Vehicle Tracking and Classification via 3D Geometries for Intelligent Transportation Systems.
- Creator
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Mcdowell, William, Mikhael, Wasfy, Jones, W Linwood, Haralambous, Michael, Atia, George, Mahalanobis, Abhijit, Muise, Robert, University of Central Florida
- Abstract / Description
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In this dissertation, we present generalized techniques which allow for the tracking and classification of vehicles by tracking various Point(s) of Interest (PoI) on a vehicle. Tracking the various PoI allows for the composition of those points into 3D geometries which are unique to a given vehicle type. We demonstrate this technique using passive, simulated image based sensor measurements and three separate inertial track formulations. We demonstrate the capability to classify the 3D...
Show moreIn this dissertation, we present generalized techniques which allow for the tracking and classification of vehicles by tracking various Point(s) of Interest (PoI) on a vehicle. Tracking the various PoI allows for the composition of those points into 3D geometries which are unique to a given vehicle type. We demonstrate this technique using passive, simulated image based sensor measurements and three separate inertial track formulations. We demonstrate the capability to classify the 3D geometries in multiple transform domains (PCA (&) LDA) using Minimum Euclidean Distance, Maximum Likelihood and Artificial Neural Networks. Additionally, we demonstrate the ability to fuse separate classifiers from multiple domains via Bayesian Networks to achieve ensemble classification.
Show less - Date Issued
- 2015
- Identifier
- CFE0005976, ucf:50790
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0005976
- Title
- INDOOR GEO-LOCATION AND TRACKING OF MOBILE AUTONOMOUS ROBOT.
- Creator
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Ramamurthy, Mahesh, Schiavone, Guy, University of Central Florida
- Abstract / Description
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The field of robotics has always been one of fascination right from the day of Terminator. Even though we still do not have robots that can actually replicate human action and intelligence, progress is being made in the right direction. Robotic applications range from defense to civilian, in public safety and fire fighting. With the increase in urban-warfare robot tracking inside buildings and in cities form a very important application. The numerous applications range from munitions tracking...
Show moreThe field of robotics has always been one of fascination right from the day of Terminator. Even though we still do not have robots that can actually replicate human action and intelligence, progress is being made in the right direction. Robotic applications range from defense to civilian, in public safety and fire fighting. With the increase in urban-warfare robot tracking inside buildings and in cities form a very important application. The numerous applications range from munitions tracking to replacing soldiers for reconnaissance information. Fire fighters use robots for survey of the affected area. Tracking robots has been limited to the local area under consideration. Decision making is inhibited due to limited local knowledge and approximations have to be made. An effective decision making would involve tracking the robot in earth co-ordinates such as latitude and longitude. GPS signal provides us sufficient and reliable data for such decision making. The main drawback of using GPS is that it is unavailable indoors and also there is signal attenuation outdoors. Indoor geolocation forms the basis of tracking robots inside buildings and other places where GPS signals are unavailable. Indoor geolocation has traditionally been the field of wireless networks using techniques such as low frequency RF signals and ultra-wideband antennas. In this thesis we propose a novel method for achieving geolocation and enable tracking. Geolocation and tracking are achieved by a combination of Gyroscope and encoders together referred to as the Inertial Navigation System (INS). Gyroscopes have been widely used in aerospace applications for stabilizing aircrafts. In our case we use gyroscope as means of determining the heading of the robot. Further, commands can be sent to the robot when it is off balance or off-track. Sensors are inherently error prone; hence the process of geolocation is complicated and limited by the imperfect mathematical modeling of input noise. We make use of Kalman Filter for processing erroneous sensor data, as it provides us a robust and stable algorithm. The error characteristics of the sensors are input to the Kalman Filter and filtered data is obtained. We have performed a large set of experiments, both indoors and outdoors to test the reliability of the system. In outdoors we have used the GPS signal to aid the INS measurements. When indoors we utilize the last known position and extrapolate to obtain the GPS co-ordinates.
Show less - Date Issued
- 2005
- Identifier
- CFE0000506, ucf:46451
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0000506
- Title
- ROBUST ESTIMATION AND ADAPTIVE GUIDANCE FOR MULTIPLE UAVS' COOPERATION.
- Creator
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Allen, Randal, Xu, Chengying, University of Central Florida
- Abstract / Description
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In this paper, an innovative cooperative navigation method is proposed for multiple Unmanned Air Vehicles (UAVs) based on online target position measurements. These noisy position measurement signals are used to estimate the target's velocity for non-maneuvering targets or the target's velocity and acceleration for maneuvering targets. The estimator's tracking capability is physically constrained due to the target's kinematic limitations and therefore is potentially improvable...
Show moreIn this paper, an innovative cooperative navigation method is proposed for multiple Unmanned Air Vehicles (UAVs) based on online target position measurements. These noisy position measurement signals are used to estimate the target's velocity for non-maneuvering targets or the target's velocity and acceleration for maneuvering targets. The estimator's tracking capability is physically constrained due to the target's kinematic limitations and therefore is potentially improvable by designing a higher performance estimator. An H-infinity filter is implemented to increase the robustness of the estimation accuracy. The performance of the robust estimator is compared to a Kalman filter and the results illustrate more precise estimation of the target's motion in compensating for surrounding noises and disturbances. Furthermore, an adaptive guidance algorithm, based on the seeker's field-of-view and linear region, is used to deliver the pursuer to the maneuvering target. The initial guidance algorithm utilizes the velocity pursuit guidance law because of its insensitivity to target motion; while the terminal guidance algorithm leverages the acceleration estimates (from the H-infinity filter) to augment the proportional navigation guidance law for increased accuracy in engaging maneuvering targets. The main objective of this work is to develop a robust estimator/tracker and an adaptive guidance algorithm which are directly applicable UAVs.
Show less - Date Issued
- 2009
- Identifier
- CFE0002535, ucf:47650
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0002535
- Title
- Approximated Control Affine Dynamics Mode For an Agricultural Field Robot Considering Wheel Terrain Interaction.
- Creator
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Menendez-Aponte, Pablo, Xu, Yunjun, Lin, Kuo-Chi, Moslehy, Faissal, University of Central Florida
- Abstract / Description
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As populations and the demand for higher crop yields grow, so to does the need forefficient agricultural wheeled mobile robots. To achieve precise navigation through a fieldit is desirable that the control system is designed based on an accurate dynamic model. Inthis paper a control affine model for a custom designed skid-steer differential drive wheeledmobile robot is found. The Terramechanic wheel terrain interaction is adopted and modifiedto consider wheels with a torus geometry. Varying...
Show moreAs populations and the demand for higher crop yields grow, so to does the need forefficient agricultural wheeled mobile robots. To achieve precise navigation through a fieldit is desirable that the control system is designed based on an accurate dynamic model. Inthis paper a control affine model for a custom designed skid-steer differential drive wheeledmobile robot is found. The Terramechanic wheel terrain interaction is adopted and modifiedto consider wheels with a torus geometry. Varying slip ratios and slip angles are consideredin the terrain reaction forces, which is curve-fitted using a nonlinear least squares approachsuch that the achieved model is control affine. The parameters in the proposed model isidentified through an extended Kalman filter so that the state variables in the model arematched. Both simulation and experiments in a commercial farm validated the proposedmodel and the identification approach.
Show less - Date Issued
- 2016
- Identifier
- CFE0006480, ucf:51410
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0006480
- Title
- Geolocation of Diseased Leaves in Strawberry Orchards for a Custom-Designed Octorotor.
- Creator
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Garcia, Christian, Xu, Yunjun, Lin, Kuo-Chi, Kauffman, Jeffrey, University of Central Florida
- Abstract / Description
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In recent years, technological advances have shown a strive for more automated processes in agriculture, as seem with the use of unmanned aerial vehicles (UAVs) with onboard sensors in many applications, including disease detection and yield prediction. In this thesis, an octorotor UAV is presented that was designed, built, and flight tested, with features that are custom-designed for strawberry orchard disease detection. To further automate the disease scouting operation, geolocation, or the...
Show moreIn recent years, technological advances have shown a strive for more automated processes in agriculture, as seem with the use of unmanned aerial vehicles (UAVs) with onboard sensors in many applications, including disease detection and yield prediction. In this thesis, an octorotor UAV is presented that was designed, built, and flight tested, with features that are custom-designed for strawberry orchard disease detection. To further automate the disease scouting operation, geolocation, or the process of determining global position coordinates of identified diseased regions based on images taken, is investigated. A Kalman filter is designed, based on a linear measurement model derived from an orthographic projection method, to estimate the target position. Simulation, as well as an ad-hoc experiment using flight data, is performed to compare this filter to the extended Kalman filter (EKF), which is based on the commonly used perspective projection method. The filter is embedded onto a CPU board for real-time use aboard the octorotor UAV, and the algorithm structure for this process is presented. In the later part of the thesis, a probabilistic data association method is used, jointly with a proposed logic-based measurement-to-target correlation method, to analyze measurements of different target sources and is incorporated into the Kalman filter. A simulation and an ad-hoc experiment, using video and flight data acquired aboard the octorotor UAV with a gimballed camera in hover flight, are performed to demonstrate the effectiveness of the algorithm and UAV platform.
Show less - Date Issued
- 2016
- Identifier
- CFE0006305, ucf:51597
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0006305
- Title
- State (Hydrodynamics) Identification in the Lower St. Johns River using the Ensemble Kalman filter.
- Creator
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Tamura, Hitoshi, Hagen, Scott, Wang, Dingbao, Bacopoulos, Peter, University of Central Florida
- Abstract / Description
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This thesis presents a method, Ensemble Kalman Filter (EnKF), applied to a high-resolution, shallow water equations model (DG ADCIRC-2DDI) of the Lower St. Johns River with observation data at four gauging stations. EnKF, a sequential data assimilation method for non-linear problems, is developed for tidal flow simulation for estimation of state variables, i.e., water levels and depth-integrated currents for overland unstructured finite element meshes. The shallow water equations model is...
Show moreThis thesis presents a method, Ensemble Kalman Filter (EnKF), applied to a high-resolution, shallow water equations model (DG ADCIRC-2DDI) of the Lower St. Johns River with observation data at four gauging stations. EnKF, a sequential data assimilation method for non-linear problems, is developed for tidal flow simulation for estimation of state variables, i.e., water levels and depth-integrated currents for overland unstructured finite element meshes. The shallow water equations model is combined with observation data, which provides the basis of the EnKF applications. In this thesis, EnKF is incorporated into DG ADCIRC-2DDI code to estimate the state variables.Upon its development, DG ADCIRC-2DDI with EnKF is first validated by implementing to a low-resolution, shallow water equations model of a quarter annular harbor with synthetic observation data at six gauging stations. Second, DG ADCIRC-2DDI with EnKF is implemented to a high-resolution, shallow water equations model of the Lower St. Johns River with real observation data at four gauging stations. Third, four different experiments are performed by applying DG ADCIRC-2DDI with EnKF to the Lower St. Johns River.
Show less - Date Issued
- 2012
- Identifier
- CFE0004331, ucf:49455
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0004331
- Title
- DESIGN AND OPERATION OF STATIONARY DISTRIBUTED BATTERY MICRO-STORAGE SYSTEMS.
- Creator
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Al-Haj Hussein, Ala, Batarseh, Issa, University of Central Florida
- Abstract / Description
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Due to some technical and environmental constraints, expanding the current electric power generation and transmission system is being challenged by even increasing the deployment of distributed renewable generation and storage systems. Energy storage can be used to store energy from utility during low-demand (off-peak) hours and deliver this energy back to the utility during high-demand (on-peak) hours. Furthermore, energy storage can be used with renewable sources to overcome some of their...
Show moreDue to some technical and environmental constraints, expanding the current electric power generation and transmission system is being challenged by even increasing the deployment of distributed renewable generation and storage systems. Energy storage can be used to store energy from utility during low-demand (off-peak) hours and deliver this energy back to the utility during high-demand (on-peak) hours. Furthermore, energy storage can be used with renewable sources to overcome some of their limitations such as their strong dependence on the weather conditions, which cannot be perfectly predicted, and their unmatched or out-of-synchronization generation peaks with the demand peaks. Generally, energy storage enhances the performance of distributed renewable sources and increases the efficiency of the entire power system. Moreover, energy storage allows for leveling the load, shaving peak demands, and furthermore, transacting power with the utility grid. This research proposes an energy management system (EMS) to manage the operation of distributed grid-tied battery micro-storage systems for stationary applications when operated with and without renewable sources. The term "micro" refers to the capacity of the energy storage compared to the grid capacity. The proposed management system employs four dynamic models; economic model, battery model, and load and weather forecasting models. These models, which are the main contribution of this research, are used in order to optimally control the operation of the micro-storage system (MSS) to maximize the economic return for the end-user when operated in an electricity spot market system.
Show less - Date Issued
- 2011
- Identifier
- CFE0003964, ucf:48712
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0003964