Tracking targets in the presence of clutter is inevitable, and presents many challenges. Additionally, rapid, drastic changes in clutter density between different environments or scenarios can make it even more difficult for tracking algorithms to adapt. A novel approach to target tracking in such dynamic clutter environments is proposed using a particle filter (PF) integrated with Interacting Multiple Models (IMMs) to compensate and adapt to the transition between different clutter densities.
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- Partial requirement for: M.S., Arizona State University, 2015Note typethesis
- Includes bibliographical references (pages 56-59)Note typebibliography
- Field of study: Electrical engineering