Open Access. Powered by Scholars. Published by Universities.®
- Institution
- Publication Year
- Publication
-
- Theses and Dissertations (23)
- Electrical and Computer Engineering Faculty Publications (5)
- Electrical and Computer Engineering Faculty Publications and Presentations (4)
- Dissertations and Theses (2)
- ETD Archive (2)
-
- All Graduate Theses and Dissertations, Spring 1920 to Summer 2023 (1)
- Chee-Ming Ting (1)
- Electrical & Computer Engineering Faculty Research (1)
- Electrical & Computer Engineering Theses & Dissertations (1)
- Electrical and Computer Engineering Faculty Research and Publications (1)
- Electronic Thesis and Dissertation Repository (1)
- Turkish Journal of Electrical Engineering and Computer Sciences (1)
- Publication Type
Articles 1 - 30 of 43
Full-Text Articles in Engineering
Framework For Implementing Advanced Radar Plotting Aid Capability For Small Maritime Vessels, Jason Stark Harris
Framework For Implementing Advanced Radar Plotting Aid Capability For Small Maritime Vessels, Jason Stark Harris
Electrical & Computer Engineering Theses & Dissertations
Every year in the United States many people are killed or injured when maritime vessels collide with other vessels or fixed objects. According to the United States Coast Guard, the top contributing factors to these collisions are operator inattention, operator inexperience and an improper lookout. Larger commercial vessels are required to have RADAR systems which support Automatic RADAR Plotting Aid (ARPA) which can automatically detect collisions and alert an operator to change course. These systems can be very expensive which put them out of reach of the average recreational boater. It is however possible to implement a low cost ARPA …
Methods For Object Tracking With Machine Vision, Zachary Simon Stamler
Methods For Object Tracking With Machine Vision, Zachary Simon Stamler
Dissertations and Theses
As machine learning and deep learning systems continue to find applications in science and engineering, the problem of providing these systems with high-quality data continues to increase in importance. Many of these systems utilize machine vision as their primary source of information, and in order to maximally leverage their abilities it is important to be able to provide them with high quality, accurate data. Unfortunately, many sets of tracking data extracted from video suffer from the problem of missing frames, which can arise from a multitude of causes depending on the system. These missing frames can result in confusion between …
Constrained Discrete-Time Optimal Control Of Uncertain Systems With Adaptivelyapunov Redesign, Oğuz Han Altintaş, Ali̇ Emre Turgut
Constrained Discrete-Time Optimal Control Of Uncertain Systems With Adaptivelyapunov Redesign, Oğuz Han Altintaş, Ali̇ Emre Turgut
Turkish Journal of Electrical Engineering and Computer Sciences
In this paper, the conventional estimation-based receding horizon control paradigm is enhanced by using functional approximation, the adaptive modifications on state estimation and convex projection notion from optimization theory. The mathematical formalism of parameter adaptation and uncertainty estimation procedure are based on the redesign of optimal state estimation in discrete-time. By using Lyapunov stability theory, it is shown that the online approximation of uncertainties acting on both physical system and state estimator can be obtained. Moreover, the convergence criteria for online parameter adaptation with fully matched and partially matched cases are presented and shown. In addition, it is shown that …
A Framework For Tumor Localization In Robot-Assisted Minimally Invasive Surgery, Nikita Chopra
A Framework For Tumor Localization In Robot-Assisted Minimally Invasive Surgery, Nikita Chopra
Electronic Thesis and Dissertation Repository
Manual palpation of tissue is frequently used in open surgery, e.g., for localization of tumors and buried vessels and for tissue characterization. The overall objective of this work is to explore how tissue palpation can be performed in Robot-Assisted Minimally Invasive Surgery (RAMIS) using laparoscopic instruments conventionally used in RAMIS. This thesis presents a framework where a surgical tool is moved teleoperatively in a manner analogous to the repetitive pressing motion of a finger during manual palpation. We interpret the changes in parameters due to this motion such as the applied force and the resulting indentation depth to accurately determine …
A Novel Particle Filtering Method For Estimation Of Pulse Pressure Variation During Spontaneous Breathing, Sunghan Kim, Fouzia Noor, Mateo Aboy, James Mcnames
A Novel Particle Filtering Method For Estimation Of Pulse Pressure Variation During Spontaneous Breathing, Sunghan Kim, Fouzia Noor, Mateo Aboy, James Mcnames
Electrical and Computer Engineering Faculty Publications and Presentations
Background: We describe the first automatic algorithm designed to estimate the pulse pressure variation ([Formula: see text]) from arterial blood pressure (ABP) signals under spontaneous breathing conditions. While currently there are a few publicly available algorithms to automatically estimate [Formula: see text] accurately and reliably in mechanically ventilated subjects, at the moment there is no automatic algorithm for estimating [Formula: see text] on spontaneously breathing subjects. The algorithm utilizes our recently developed sequential Monte Carlo method (SMCM), which is called a maximum a-posteriori adaptive marginalized particle filter (MAM-PF). We report the performance assessment results of the proposed algorithm on …
Initial Implementation And Testing Of A Tightly-Coupled Imu/Pseudolite System, James E. C. Kawecki
Initial Implementation And Testing Of A Tightly-Coupled Imu/Pseudolite System, James E. C. Kawecki
Theses and Dissertations
Currently, the 746th Test Squadrons (746th TS) Central Inertial and GPS Test Facility (CIGTF) operates one of the most accurate truth reference systems, called the CIGTF Reference System (CRS). CIGTF will be replacing the CRS with a new references system called UHARS (Ultra High Accuracy Reference System). UHARS will differ from CRS by adding the ability to use a non-GPS pseudolite system, as a new measurement source. This research effort describes the design of the extended Kalman filter which is developed in AFIT's SPIDER filter framework which implements a tightly-coupled pseudolite/INS filter.
Air-To-Air Missile Enhanced Scoring With Kalman Smoothing, Jonathon S. Gipson
Air-To-Air Missile Enhanced Scoring With Kalman Smoothing, Jonathon S. Gipson
Theses and Dissertations
A correct estimate of a missile's flight path is essential to USAF test and evaluation efforts. The USAF air-to-air Weapons System Evaluation Program (WSEP) targets unmanned aerial drones in hundreds of live-fire missile tests each year. The current QF-4 drone inventory is expected to be depleted by 2015. The QF-16 Full Scale Aerial Target (FSAT) contract has been awarded to convert usable early model F-16s into remote-controlled drones. The QF-16 will provide a highly-maneuverable, realistic testing environment for 5th generation fighters. To accomplish their mission, WSEP requires a scoring system capable of estimating the trajectory of a missile relative to …
All Source Sensor Integration Using An Extended Kalman Filter, Timothy R. Penn
All Source Sensor Integration Using An Extended Kalman Filter, Timothy R. Penn
Theses and Dissertations
The global positioning system (GPS) has become an ubiquitous source for navigation in the modern age, especially since the removal of selective availability at the beginning of this century. The utility of the GPS is unmatched, however GPS is not available in all environments. Heavy reliance on GPS for navigation makes the warfighter increasingly vulnerability as modern warfare continues to evolve. This research provides a method for incorporating measurements from a massive variety of sensors to mitigate GPS dependence. The result is the integration of sensor sets that encompass those examined in recent literature as well as some custom navigation …
Linear-Quadratic Control Of A Mems Micromirror Using Kalman Filtering, Jamie P. Schnapp
Linear-Quadratic Control Of A Mems Micromirror Using Kalman Filtering, Jamie P. Schnapp
Theses and Dissertations
The deflection limitations of electrostatic flexure-beam actuators are well known. Specifically, as the beam is actuated and the gap traversed, the restoring force necessary for equilibrium increases proportionally with the displacement to first order, while the electrostatic actuating force increases with the inverse square of the gap. Equilibrium, and thus stable open-loop voltage control, ceases at one-third the total gap distance, leading to actuator snap-in. A Kalman Filter is designed with an appropriately complex state dynamics model to accurately estimate actuator deflection given voltage input and capacitance measurements, which are then used by a Linear Quadratic controller to generate a …
Extraction Of Small Boat Harmonic Signatures From Passive Sonar, George Lloyd Ogden, Lisa M. Zurk, M. E. Jones, M. E. Peterson
Extraction Of Small Boat Harmonic Signatures From Passive Sonar, George Lloyd Ogden, Lisa M. Zurk, M. E. Jones, M. E. Peterson
Electrical and Computer Engineering Faculty Publications and Presentations
This paper investigates the extraction of acoustic signatures from small boats using a passive sonar system. Noise radiated from a small boats consists of broadband noise and harmonically related tones that correspond to engine and propeller specifications. A signal processing method to automatically extract the harmonic structure of noise radiated from small boats is developed. The Harmonic Extraction and Analysis Tool (HEAT) estimates the instantaneous fundamental frequency of the harmonic tones, refines the fundamental frequency estimate using a Kalman filter, and automatically extracts the amplitudes of the harmonic tonals to generate a harmonic signature for the boat. Results are presented …
Experimental Observations Of Active Invariance Striations In A Tank Environment, Jorge E. Quijano, Richard L. Campbell, Tobias G. Oesterlein, Lisa M. Zurk
Experimental Observations Of Active Invariance Striations In A Tank Environment, Jorge E. Quijano, Richard L. Campbell, Tobias G. Oesterlein, Lisa M. Zurk
Electrical and Computer Engineering Faculty Publications and Presentations
The waveguide invariant in shallow water environments has been widely studied in the context of passive sonar. The invariant provides a relationship between the frequency content of a moving broadband source and the distance to the receiver, and this relationship is not strongly affected by small perturbations in environment parameters such as sound speed or bottom features. Recent experiments in shallow water suggest that a similar range-frequency structure manifested as striations in the spectrogram exists for active sonar, and this property has the potential to enhance the performance of target tracking algorithms. Nevertheless, field experiments with active sonar have not …
Ecg Based Personal Identification Using Extended Kalman Filter, Chee-Ming Ting Phd, Sh-Hussain Salleh
Ecg Based Personal Identification Using Extended Kalman Filter, Chee-Ming Ting Phd, Sh-Hussain Salleh
Chee-Ming Ting
This paper proposes a new approach for electrocardiogram (ECG) based personal identification based on extended Kalman filtering (EKF) framework. The framework uses nonlinear ECG dynamic models formulated to represent noisy ECG signal. The advantage of the models is the ability to capture distinct ECG features used for biometric recognition such as temporal and amplitude distances between PQRST points. Moreover the inherent modeling of additive noise provides robust recognition. Log-likelihood scoring is proposed for classification. The algorithm is evaluated on identification task on 13 subjects of MIT-BIH Arrhythmia Database using single lead data. Identification rate of 87.50% is achieved on 30s …
Multiharmonic Frequency Tracking Method Using The Sigma-Point Kalman Smoother, Sunghan Kim, Anindya S. Paul, Eric A. Wan, James Mcnames
Multiharmonic Frequency Tracking Method Using The Sigma-Point Kalman Smoother, Sunghan Kim, Anindya S. Paul, Eric A. Wan, James Mcnames
Electrical and Computer Engineering Faculty Publications and Presentations
Several groups have proposed the state-space approach to tracking time-varying frequencies of multiharmonic quasiperiodic signals. The extended Kalman filter/smoother (EKF/EKS) is one of the common frequency tracking approaches seen in the literature. We introduce a multiharmonic frequency tracker based on the forward-backward statistical linearized Sigma-Point Kalman smoother (FBSL-SPKS) and compare its performance to that of the extended Kalman smoother (EKS). In all cases the FBSL-SPKS tracker outperformed the EKS tracker over a wide range of signal-to-noise (SNR) ratios. We also demonstrate its superior performance on real signals.
Sensing And Control Of Mems Accelerometers Using Kalman Filter, Kai Zhang
Sensing And Control Of Mems Accelerometers Using Kalman Filter, Kai Zhang
ETD Archive
Surface micromachined low-capacitance MEMS capacitive accelerometers which integrated CMOS readout circuit generally have a noise above 0.02g. Force-to-rebalance feedback control that is commonly used in MEMS accelerometers can improve the performances of accelerometers such as increasing their stability, bandwidth and dynamic range. However, the controller also increases the noise floor. There are two major sources of the noise in MEMS accelerometer. They are electronic noise from the CMOS readout circuit and thermal-mechanical Brownian noise caused by damping. Kalman filter is an effective solution to the problem of reducing the effects of the noises through estimating and canceling the states contaminated …
Native Earth Electric Field Measurements Using Small Spacecraft In Low Earth Orbit, John A. Pratt
Native Earth Electric Field Measurements Using Small Spacecraft In Low Earth Orbit, John A. Pratt
All Graduate Theses and Dissertations, Spring 1920 to Summer 2023
The use of small satellites to measure the native electric field of the earth has historically presented many problems as a result of the generally modest pointing capabilities of small satellites. In spite of this, the cost of small satellites makes them ideal for just such scientific missions. This thesis details many of the constraints of electric field measuring missions as well as the requirements on any spacecraft designed to accomplish such. The data from a small sounding rocket mission is then analyzed and its usefulness discussed. Possible other methods for use are also discussed.
The Navigation Potential Of Ground Feature Tracking, Guner Mutlu
The Navigation Potential Of Ground Feature Tracking, Guner Mutlu
Theses and Dissertations
This research effort examines the reduction of error in inertial navigation aided by vision. This is part of an effort focused on navigation in a GPS denied environment. The navigation concept examined here consists of two main steps. First, extract the position of a tracked ground object using vision and geo-locate it in 3 dimensional navigation frame. In this first step multiple positions of the UAV are assumed known; think of a synthetic aperture. The only information about the tracked ground objects/features is the unit vector that points to the objects from the center of the camera. Two such vectors …
Fusion Of Inertial Sensors And Orthogonal Frequency Division Multiplexed (Ofdm) Signals Of Opportunity For Unassisted Navigation, Jason G. Crosby
Fusion Of Inertial Sensors And Orthogonal Frequency Division Multiplexed (Ofdm) Signals Of Opportunity For Unassisted Navigation, Jason G. Crosby
Theses and Dissertations
The advent of the global positioning system (GPS) has provided worldwide high-accuracy position measurements. However, GPS may be rendered unavailable by jamming, disruption of satellites, or simply by signal shadowing in urban environments. Thus, this thesis considers fusion of Inertial Navigation Systems (INS) and Orthogonal Frequency Division Multiplexed (OFDM) signals of opportunity (SOOP) for navigation. Typical signal of opportunity navigation involves the use of a reference receiver and uses time difference of arrival (TDOA) measurements. However, by exploiting the block structure of OFDM communication signals, the need for the reference receiver is reduced or possibly removed entirely. This research uses …
Model-Based Control Using Model And Mechanization Fusion Techniques For Image-Aided Navigation, Constance D. Hendrix
Model-Based Control Using Model And Mechanization Fusion Techniques For Image-Aided Navigation, Constance D. Hendrix
Theses and Dissertations
Unmanned aerial vehicles are no longer used for just reconnaissance. Current requirements call for smaller autonomous vehicles that replace the human in high-risk activities. Many times these activities are performed in GPS-degraded environments. Without GPS providing today's most accurate navigation solution, autonomous navigation in tight areas is more difficult. Today, image-aided navigation is used and other methods are explored to more accurately navigate in such areas (e.g., indoors). This thesis explores the use of inertial measurements and navigation solution updates using cameras with a model-based Linear Quadratic Gaussian controller. To demonstrate the methods behind this research, the controller will provide …
Biogeography-Based Optimization: Synergies With Evolutionary Strategies, Immigration Refusal, And Kalman Filters, Dawei Du
ETD Archive
Biogeography-based optimization (BBO) is a recently developed heuristic algorithm which has shown impressive performance on many well known benchmarks. The aim of this thesis is to modify BBO in different ways. First, in order to improve BBO, this thesis incorporates distinctive techniques from other successful heuristic algorithms into BBO. The techniques from evolutionary strategy (ES) are used for BBO modification. Second, the traveling salesman problem (TSP) is a widely used benchmark in heuristic algorithms, and it is considered as a standard benchmark in heuristic computations. Therefore the main task in this part of the thesis is to modify BBO to …
Distributed Object Tracking Using A Cluster-Based Kalman Filter In Wireless Camera Networks, Henry Medeiros, Johnny Park, Avinash Kak
Distributed Object Tracking Using A Cluster-Based Kalman Filter In Wireless Camera Networks, Henry Medeiros, Johnny Park, Avinash Kak
Electrical and Computer Engineering Faculty Research and Publications
Local data aggregation is an effective means to save sensor node energy and prolong the lifespan of wireless sensor networks. However, when a sensor network is used to track moving objects, the task of local data aggregation in the network presents a new set of challenges, such as the necessity to estimate, usually in real time, the constantly changing state of the target based on information acquired by the nodes at different time instants. To address these issues, we propose a distributed object tracking system which employs a cluster-based Kalman filter in a network of wireless cameras. When a target …
Characterization And Implementation Of A Real-World Target Tracking Algorithm On Field Programmable Gate Arrays With Kalman Filter Test Case, Benjamin D. Hancey
Characterization And Implementation Of A Real-World Target Tracking Algorithm On Field Programmable Gate Arrays With Kalman Filter Test Case, Benjamin D. Hancey
Theses and Dissertations
A one dimensional Kalman Filter algorithm provided in Matlab is used as the basis for a Very High Speed Integrated Circuit Hardware Description Language (VHDL) model. The JAVA programming language is used to create the VHDL code that describes the Kalman filter in hardware which allows for maximum flexibility. A one-dimensional behavioral model of the Kalman Filter is described, as well as a one-dimensional and synthesizable register transfer level (RTL) model with optimizations for speed, area, and power. These optimizations are achieved by a focus on parallelization as well as careful Kalman filter sub-module algorithm selection. Newton-Raphson reciprocal is the …
Sampled-Data Kalman Filtering And Multiple Model Adaptive Estimation For Infinite-Dimensional Continuous-Time Systems, Scott A. Sallberg
Sampled-Data Kalman Filtering And Multiple Model Adaptive Estimation For Infinite-Dimensional Continuous-Time Systems, Scott A. Sallberg
Theses and Dissertations
Kalman filtering and multiple model adaptive estimation (MMAE) methods have been applied by researchers in several engineering disciplines to a multitude of problems featuring a linear (or mildly nonlinear) model based on finite-dimensional differential (or difference) equations perturbed by random inputs. However, many real-world systems are more naturally modeled using an infinite-dimensional continuous-time linear systems model, such as those most naturally modeled as partial differential equations or time-delayed differential equations along with a possibly infinite-dimensional measurement model. The Kalman filtering technique was extended to encompass infinite-dimensional continuous-time systems with sampled-data measurements and a technique to approximate an infinite-dimensional continuous-time system …
Stochastic Estimation And Control Of Queues Within A Computer Network, Nathan C. Stuckey
Stochastic Estimation And Control Of Queues Within A Computer Network, Nathan C. Stuckey
Theses and Dissertations
An extended Kalman filter is used to estimate size and packet arrival rate of network queues. These estimates are used by a LQG steady state linear perturbation PI controller to regulate queue size within a computer network. This paper presents the derivation of the transient queue behavior for a system with Poisson traffic and exponential service times. This result is then validated for ideal traffic using a network simulated in OPNET. A more complex OPNET model is then used to test the adequacy of the transient queue size model when non-Poisson traffic is combined. The extended Kalman filter theory is …
Fusion Of Imaging And Inertial Sensors For Navigation, Michael J. Veth
Fusion Of Imaging And Inertial Sensors For Navigation, Michael J. Veth
Theses and Dissertations
The motivation of this research is to address the limitations of satellite-based navigation by fusing imaging and inertial systems. The research begins by rigorously describing the imaging and navigation problem and developing practical models of the sensors, then presenting a transformation technique to detect features within an image. Given a set of features, a statistical feature projection technique is developed which utilizes inertial measurements to predict vectors in the feature space between images. This coupling of the imaging and inertial sensors at a deep level is then used to aid the statistical feature matching function. The feature matches and inertial …
Kalman Filtering With Inequality Constraints For Turbofan Engine Health Estimation, Daniel J. Simon, Donald L. Simon
Kalman Filtering With Inequality Constraints For Turbofan Engine Health Estimation, Daniel J. Simon, Donald L. Simon
Electrical and Computer Engineering Faculty Publications
Kalman filters are often used to estimate the state variables of a dynamic system. However, in the application of Kalman filters some known signal information is often either ignored or dealt with heuristically. For instance, state-variable constraints (which may be based on physical considerations) are often neglected because they do not fit easily into the structure of the Kalman filter. Thus, two analytical methods to incorporate state-variable inequality constraints into the Kalman filter are now derived. The first method is a general technique that uses hard constraints to enforce inequalities on the state-variable estimates. The resultant filter is a combination …
Multiple Model Methods For Cost Function Based Multiple Hypothesis Trackers, Matthew C. Kozak
Multiple Model Methods For Cost Function Based Multiple Hypothesis Trackers, Matthew C. Kozak
Theses and Dissertations
Multiple hypothesis trackers (MHTs) are widely accepted as the best means of tracking targets in clutter. This research seeks to incorporate multiple model Kalman filters into an Integral Square Error (ISE) cost-function-based MHT to increase the fidelity of target state estimation. Results indicate that the proposed multiple model methods can properly identify the maneuver mode of a target in dense clutter and ensure that an appropriately tuned filter is used. During benign portions of flight, this causes significant reductions in position and velocity RMS errors compared to a single-filter MHT. During portions of flight when the mixture mean deviates significantly …
H-Infinity Estimation For Fuzzy Membership Function Optimization, Daniel J. Simon
H-Infinity Estimation For Fuzzy Membership Function Optimization, Daniel J. Simon
Electrical and Computer Engineering Faculty Publications
Given a fuzzy logic system, how can we determine the membership functions that will result in the best performance? If we constrain the membership functions to a specific shape (e.g., triangles or trapezoids) then each membership function can be parameterized by a few variables and the membership optimization problem can be reduced to a parameter optimization problem. The parameter optimization problem can then be formulated as a nonlinear filtering problem. In this paper we solve the nonlinear filtering problem using H∞ state estimation theory. However, the membership functions that result from this approach are not (in general) sum normal. …
Multiple Model Adaptive Estimator Target Tracker For Maneuvering Targets In Clutter, Brian D. Smith
Multiple Model Adaptive Estimator Target Tracker For Maneuvering Targets In Clutter, Brian D. Smith
Theses and Dissertations
The task of tracking a target in the presence of measurement clutter is a two-fold problem: one of handling measurement association uncertainty (due to clutter), and poorly known or significantly varying target dynamics. Measurement association uncertainty does not allow conventional tracking algorithms (such as Kalman filters) to be implemented directly. Poorly known or varying target dynamics complicate the design of any tracking filter, and filters using only a single dynamics model can rarely handle anything beyond the most benign target maneuvers. In recent years, the Multiple Hypothesis Tracker (MHT) has gained acceptance as a means of handling targets in a …
Kalman Filtering With Uncertain Noise Covariances, Srikiran Kosanam, Daniel J. Simon
Kalman Filtering With Uncertain Noise Covariances, Srikiran Kosanam, Daniel J. Simon
Electrical and Computer Engineering Faculty Publications
In this paper the robustness of Kalman filtering against uncertainties in process and measurement noise covariances is discussed. It is shown that a standard Kalman filter may not be robust enough if the process and measurement noise covariances are changed. A new filter is proposed which addresses the uncertainties in process and measurement noise covariances and gives better results than the standard Kalman filter. This new filter is used in simulation to estimate the health parameters of an aircraft gas turbine engine.
Optimal Design Of Generalized Multiple Model Adaptive Controllers, Thomas E. Brehm
Optimal Design Of Generalized Multiple Model Adaptive Controllers, Thomas E. Brehm
Theses and Dissertations
Advanced analysis and optimal design techniques that achieve performance improvement for multiple model adaptive control (MMAC) and multiple model adaptive estimation (MMAE) based control are developed and tested for this dissertation research. An adjunct area of research yielded modified linear quadratic Gaussian (LQG) control design techniques that also can be applied to nonadaptive control. For the Modified LQG (MLQG) controller, the proposed designs remove the assumption that the Kalman filter as the observer and the controller gain matrix design are necessarily based on the same model as the best system model. The filter and controller gain matrices are both determined …