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Urban Terrain Multiple Target Tracking Using the Probability Hypothesis Density Particle Filter


Abstract The tracking of multiple targets becomes more challenging in complex environments due to the additional degrees of nonlinearity in the measurement model. In urban terrain, for example, there are multiple reflection path measurements that need to be exploited since line-of-sight observations are not always available. Multiple target tracking in urban terrain environments is traditionally implemented using sequential Monte Carlo filtering algorithms and data association techniques. However, data association techniques can be computationally intensive and require very strict conditions for efficient performance. This thesis investigates the probability hypothesis density (PHD) method for tracking multiple targets in urban environments. Th... (more)
Created Date 2011
Contributor Zhou, Meng (Author) / Papandreou-Suppappola, Antonia (Advisor) / Tepedelenlioglu, Cihan (Committee member) / Kovvali, Narayan (Committee member) / Arizona State University (Publisher)
Subject Electrical Engineering / Urban Terrain Multiple Target Tracking
Type Masters Thesis
Extent 74 pages
Language English
Copyright
Reuse Permissions All Rights Reserved
Note M.S. Electrical Engineering 2011
Collaborating Institutions Graduate College / ASU Library
Additional Formats MODS / OAI Dublin Core / RIS


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Description Dissertation/Thesis