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) |
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| 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 |
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| 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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