Exploiting Sparse Structures in Source Localization and Tracking (2022)
Abstract / truncated to 115 words
This thesis deals with the modeling of structured signals under different sparsity constraints. Many phenomena exhibit an inherent structure that may be exploited when setting up models, examples include audio waves, radar, sonar, and image objects. These structures allow us to model, identify, and classify the processes, enabling parameter estimation for, e.g., identification, localisation, and tracking. In this work, such structures are exploited, with the goal to achieve efficient localisation and tracking of a structured source signal. Specifically, two scenarios are considered. In papers A and B, the aim is to find a sparse subset of a structured signal such that the signal parameters and source locations may be estimated in an optimal way. For ...
source localization and tracking – cramér-rao lower bounds – convex optimization
Information
- Author
- Juhlin, Maria
- Institution
- Lund University
- Supervisor
- Publication Year
- 2022
- Upload Date
- Dec. 1, 2022
The current layout is optimized for mobile phones. Page previews, thumbnails, and full abstracts will remain hidden until the browser window grows in width.
The current layout is optimized for tablet devices. Page previews and some thumbnails will remain hidden until the browser window grows in width.