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  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
311

Decentralized Data Fusion and Target Tracking using Improved Particle Filter

Tsai, Shin-Hung 01 August 2008 (has links)
In decentralized data fusion system, if the probability model of the noise is Gaussian and the innovation informations from the sensors are uncorrlated,the information filtering technique can be the best method to fuse the information from different sensors. However, in the realistic environments, information filter cannot provide the best solution of state estimation and data integration when the noises are non-Gaussian and correlated. Since particle filter are capable of dealing with non-linear and non-Gaussian problems, it is an intuitive approach to replace the information filter by particle filter with some suitable data fusion techniques.In this thesis, we investigate a decentralized data fusion system with improved particle filters for target tracking. In order to achieve better tracking performance, the Iterated Extended Kalman Filter framework is used to incorporate the newest observations into the proposal distribution of the particle filter. In our proposed architecture, each sensor consists of one particle filter, which is used in generating the local statistics of the system state. Gaussian mixture model (GMM) is adopted to approximate the posterior distribution of the weighted particles in the filters, thereby more compact representations of the distribution for transmmision can be obtained. To achieve information sharing and integration, the GMM-Covariance Intersection algorithm is used in formulating the decentralized fusion solutions. Simulation resluts of target tracking cases in a sensor system with two sensor nodes are given to show the effectiveness and superiorty of the proposed architecture.
312

Dual-IMM System for Target Tracking and Data Fusion

Shiu, Jia-yu 30 August 2009 (has links)
In solving target tracking problems, the Kalman filter (KF) is one of the most widely used estimators. Whether the state of target movement adapts to the changes in the observations depends on the model assumptions. The interacting multiple model (IMM) algorithm uses interaction of a bank of parallel Kalman filters to solve the hypothetical model of tracking maneuvering target. Based on the function of soft switching, the IMM algorithm, with parallel Kalman filters of different dimensions, can perform well by adjusting the model weights. Nonetheless, the uncertainty in measured data and the types of sensing systems used for target tracking may still hinder the signal processing in the IMM. In order to improve the performance of target tracking and signal estimation, the concept of data fusion can be adapted in the IMM-based structures. Multiple IMM based estimators can be used in the structure of multi-sensor data fusion. In this thesis, we propose a dual-IMM estimator structure, in which data fusion of the two IMM estimators is achieved by updating associated model probabilities. Suppose that two sensors for measuring the moving target is affected by the different degrees of noise, the measured data can be processed first through two separate IMM estimators. Then, the IMM-based estimators exchange with each other the estimates, model probabilities and model transition probabilities. The dual-IMM estimator will integrate the shared data based on the proposed dual-IMM algorithm. The dual-IMM estimator can be used to avoid degraded performance of single IMM with insufficient data or undesirable environmental effects. The simulation results show that a single IMM estimator with smaller measurement noise level can be used to compensate the other IMM, which is affected by larger measurement noise. Improved overall performance from the dual-IMM estimator is obtained. Generally speaking, the two IMM estimators in the proposed structure achieve better performance when same level of measurement noise is assumed. The proposed dual-IMM estimator structure can be easily extended to multiple-IMM structure for estimation and data fusion.
313

Improved Particle Filter for Target Tracking in Decentralized Data Fusion System

Lin, Yu-Tsen 06 September 2009 (has links)
In this thesis, we investigate a decentralized data fusion system with improved particle filters for target tracking. In many application areas, it becomes essential to use nonlinear and non-Gaussian elements to accurately model the underlying dynamics of a physical system. Particle filters have a great potential for solving highly nonlinear and non-Gaussian estimation problems, in which the traditional Kalman filter and extended Kalman filter may generally fail. To improve the tracking performance of particle filters, initialization of the particles is studied. We construct an initial state distribution by using least square estimation. In addition, to enhance the tracking capability of particle filters, representation of target velocity by another set of particles is considered. We include another layer of particle filter inside the original particle filter for updating the velocity. In our proposed architecture, we assume that each sensor node contain a particle filter and there is no fusion center in the sensor network. Approximated a posteriori distribution at the sensor is obtained by using the local particle filters with the Gaussian mixture model (GMM), so that more compact representations of the distribution for transmission can be obtained. To achieve information sharing and integration, the GMM-covariance intersection algorithm is used in formulating the decentralized fusion solutions. Simulation results are presented to illustrate that the performance of the improved particle filter is better than standard particle filter. In addition, simulation results of target tracking in the sensor system with three sensor nodes are given to show the effectiveness and superiority of the proposed architecture.
314

The potential of using log biometrics to track sawmill flow /

Peterson, Matthew G. January 1900 (has links)
Thesis (M.S.)--Oregon State University, 2010. / Printout. Includes bibliographical references (leaves 76-78). Also available on the World Wide Web.
315

Time blanking for GBT data with RADAR RFI /

Dong, Weizhen, January 2004 (has links) (PDF)
Thesis (M.S.)--Brigham Young University. Dept. of Electrical and Computer Engineering, 2004. / Includes bibliographical references (p. 77-79).
316

Visual hull construction, alignment and refinement for human kinematic modeling, motion tracking and rendering /

Cheung, Kong Man (German) January 1900 (has links)
Thesis (Ph. D.)--Carnegie Mellon University, 2003. / "October 2003." Includes bibliographical references.
317

Source/receiver motion-induced Doppler influence on the bandwidth of sinusoidal signals /

Pistacchio, David J. January 2003 (has links) (PDF)
Thesis (M.S. in Engineering Acoustics)--Naval Postgraduate School, December 2003. / Thesis advisor(s): Kevin Smith, Roy Streit. Includes bibliographical references (p. 95-100). Also available online.
318

The implementation of a heterogeneous multi-agent swarm with autonomous target tracking capabilities

Szmuk, Michael 04 April 2014 (has links)
This thesis details the development of a custom autopilot system designed specifically for multi-agent robotic missions. The project was motivated by the need for a flexible autopilot system architecture that could be easily adapted to a variety of future multi-vehicle experiments. The development efforts can be split into three categories: algorithm and software development, hardware development, and testing and integration. Over 12,000 lines of C++ code were written in this project, resulting in custom flight and ground control software. The flight software was designed to run on a Gumstix Overo Fire(STORM) computer on module (COM) using a Linux Angstrom operating system. The flight software was designed to support the onboard GN&C algorithms. The ground control station and its graphical user interface were developed in the Qt C++ framework. The ground control software has been proven to operate safely during multi-vehicle tests, and will be an asset in future work. Two TSH GAUI 500X quad-rotors and one Gears Educational Systems SMP rover were integrated into an autonomous swarm. Each vehicle used the Gumstix Overo COM. The C-DUS Pilot board was designed as a custom interface circuit board for the Overo COM and its expansion board, the Gumstix Pinto-TH. While the built-in WiFi capability of the Overo COM served as a communication link to a central wireless router, the C-DUS Pilot board allowed for the compact and reliable integration of sensors and actuators. The sensors used in this project were limited to accelerometers, gyroscopes, magnetometers, and GPS. All of the components underwent extensive testing. A series of ground and flight tests were conducted to safely and gradually prove system capabilities. The work presented in this thesis culminated with a successful three-vehicle autonomous demonstration comprised of two quad-rotors executing a standoff tracking trajectory around a moving rover, while simultaneously performing GPS-based collision avoidance. / text
319

Video-based people counting and crowd segmentation

Hou, Yali, 侯亚丽 January 2011 (has links)
published_or_final_version / Electrical and Electronic Engineering / Doctoral / Doctor of Philosophy
320

Less information, more thinking : How attentional behavior predicts learning in mathematics

Qwillbard, Tony January 2014 (has links)
It has been shown in experiments that a method of teaching where students are encouraged to create their own solution methods to mathematical problems (creative mathematically founded reasoning, CMR) results in better learning and proficiency than one where students are provided with solution methods for them to practice by repetition (algorithmic reasoning, AR). The present study investigated whether students in an AR practice condition pay less attention to information relevant for mathematical problem solving than students in a CMR condition. To test this, attentional behavior during practice was measured using eye-tracking equipment. These measurements were then associated with task proficiency in a follow-up test one week after the practice session. The findings support the theory and confirm previous studies in that CMR leads to better task performance in the follow-up test. The findings also suggest that students within the CMR condition whom focus less on extraneous information perform better. / Experiment har visat att en undervisningsmetod i vilken elever uppmuntras att själva komma på lösningsmetoder till matematiska problem (creative mathematically founded reasoning, CMR) resulterar i bättre inlärning och färdighet än en metod i vilken eleverna ges en färdig en lösningsmetod att öva på genom repetition (algorithmic reasoning, AR). Denna studie undersöker om elever under en AR-träningsbetingelse ägnar mindre uppmärksamhet åt information som är relevant för matematisk problemlösning än vad elever under en CMR-träningsbetingelse gör. För att testa detta mättes elevernas uppmärksamhetsbeteende under träning med hjälp av ögonrörelsekamera. Måtten ställdes sedan i relation till uppgiftsfärdighet i ett uppföljningstest en vecka efter träningssessionen. Resultaten stödjer teorin och bekräftar tidigare studier som visat att CMR leder till bättre prestation i uppföljningstestet. Resultaten tyder även på att de elever under CMR-betingelsen som fokuserar minst på ovidkommande information presterar bättre.

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