Off-Grid sparse blind sensor calibration
| Autor: | Imam Samil Yetik, Sedat Camlica, Orhan Arikan |
|---|---|
| Přispěvatelé: | Arıkan, Orhan |
| Rok vydání: | 2018 |
| Předmět: |
Discretization
Computer science Calibration (statistics) Monte Carlo method Phase (waves) 020206 networking & telecommunications 02 engineering and technology Grid Signal Off-grid Compressed sensing Compressive Sensing 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Blind calibration Algorithm Degradation (telecommunications) |
| Zdroj: | SIU 2018 26th Signal Processing and Communications Applications Conference (SIU) |
| Popis: | Date of Conference: 2-5 May 2018 Compressive Sensing (CS) based techniques generally discretize the signal space and assume that the signal is sparse and has support only on the discretized grid points. Due to continuous nature of the signals, representing the signal on a discretized grid results in the off-grid problem. Improper calibration is also another issue which can cause performance degradation. In this paper, a CS based blind calibration method is proposed for the multiple off-grid signal case. Proposed method is capable of estimating the off-grid signal parameters and correcting the gain and the phase errors simultaneously. Simulation analysis is performed and comments are drawn. Results show that the proposed method have superior performance in terms of the calculated metrics. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|