Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 11 of 11 for “"probabilistic data association"”.
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Ballistic missile tracking using the interacting multiple model joint probabilistic data association filter
… of the interacting multiple model joint probabilistic data association filter to effectively track a ballistic missile and detect decoys and maneuvers is the focus of this thesis. Model development and data association schemes are discussed along with optimized values for selected …
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Radar and LiDAR Fusion for Scaled Vehicle Sensing
… an extended Kalman filter (EKF) and the joint probabilistic data association (JPDA). Second, a 1/5th scaled vehicle performed the same vehicle maneuvers but scaled to approximately 1/5th the distance and speed. When taking the scaling factor into consideration, the RTS' positional error at …
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Terrain-relative navigation for autonomous underwater vehicles
… represented through a covariance matrix. A probabilistic data association filter with amplitude information (PDAFAI), grounded in the Kalman Filter framework, probabilistically weights each good match that lies within the validation gate. Weights are a function of both the match quality and …
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Multichannel source separation and tracking with phase differences by random sample consensus
… IPD features compose a noisy circular-linear dataset. This data is clustered with the RANdom SAmple Consensus (RANSAC) algorithm in the presence of strong reverberation to simultaneously localize and separate speakers. The remarkable performance of RANSAC is due to its natural tendency to …
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Best Linear Unbiased Estimation Fusion with Constraints
<p>Estimation fusion, or data fusion for estimation, is the problem of how to best utilize useful information contained in multiple data sets for the purpose of estimating an unknown quantity — a parameter or a process. Estimation fusion with constraints gives rise to challenging theoretical …
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Passive Acoustic Localization and Tracking with Mobile Robots
… merged measurement model into a nonlinear joint probabilistic data association filter (JDPAF). We demonstrate the ability to track multiple targets through merging events. Furthermore, we propose a novel planning algorithm that incorporates the merged measurement model into the planning process. …
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Visual Object Tracking in Challenging Situations using a Bayesian Perspective = Seguimiento visual de objetos en situaciones complejas mediante un enfoque bayesiano
… handle false and missing detections through a probabilistic data association stage. Excellent results have been obtained using publicly available databases, proving the efficiency of the developed Bayesian tracking models. La creciente disponibilidad de potentes ordenadores y cámaras de alta …
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Feedback particle filter and its applications
… to extract useful information from noisy sensor data. It finds applications in all disciplines of science and engineering, including tracking and navigation, traffic surveillance, financial engineering, neuroscience, biology, robotics, computer vision, weather forecasting, geophysical survey and …
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Mobile robot navigation in dynamic environments
… motion patterns <br>of people from sensor data using the EM algorithm. Furthermore, we <br>describe how the learned patterns can be used to predict future <br>movements of the people. Afterward, we explain how this knowledge can <br>be integrated into the path planning process of a mobile …