Compact Formulations for Sparse Reconstruction in Fully and Partly Calibrated Sensor Arrays
Sensor array processing is a classical field of signal processing which offers various applications in practice, such as direction of arrival estimation or signal reconstruction, as well as a rich theory, including numerous estimation methods and statistical bounds on the achievable estimation perfo...
| Main Author: | |
|---|---|
| Format: | Others |
| Language: | en |
| Published: |
2018
|
| Online Access: | https://tuprints.ulb.tu-darmstadt.de/7251/1/thesis_steffens.pdf Steffens, Christian <http://tuprints.ulb.tu-darmstadt.de/view/person/Steffens=3AChristian=3A=3A.html> (2018): Compact Formulations for Sparse Reconstruction in Fully and Partly Calibrated Sensor Arrays.Darmstadt, Technische Universität, [Ph.D. Thesis] |
| Summary: | Sensor array processing is a classical field of signal processing which offers various applications in practice, such as direction of arrival estimation or signal reconstruction, as well as a rich theory, including numerous estimation methods and statistical bounds on the achievable estimation performance. A comparably new field in signal processing is given by sparse signal reconstruction (SSR), which has attracted remarkable interest in the research community during the last years and similarly offers plentiful fields of application. This thesis considers the application of SSR in fully calibrated sensor arrays as well as in partly calibrated sensor arrays. The main contributions are a novel SSR method for application in partly calibrated arrays as well as compact formulations for the SSR problem, where special emphasis is given on exploiting specific structure in the signals as well as in the array topologies. |
|---|