Name
Abstract | ||
|---|---|---|
This paper studies sensor calibration in spectral estimation where the true frequencies are located on a continuous domain. We consider a uniform array of sensors that collects measurements whose spectrum is composed of a finite number of frequencies, where each sensor has an unknown calibration parameter. Our goal is to recover the spectrum and the calibration parameters simultaneously from multiple snapshots of the measurements. In the noiseless case with an infinite number of snapshots, we prove uniqueness of this problem up to certain trivial, inevitable ambiguities based on an algebraic method, as long as there are more sensors than frequencies. We then analyze the sensitivity of this algebraic technique with respect to the number of snapshots and noise. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1016/j.acha.2018.08.003 | Applied and Computational Harmonic Analysis |
Keywords | Field | DocType |
Sensor calibration,Spectral estimation,Frequencies on a continuous domain,Uniqueness,Stability,Algebraic methods and an optimization approach | Uniqueness,Gradient descent,Spectral density estimation,Mathematical optimization,Algebraic number,Matrix (mathematics),Algorithm,Toeplitz matrix,Covariance matrix,Mathematics,Calibration | Journal |
Volume | Issue | ISSN |
48 | 2 | 1063-5203 |
Citations | PageRank | References |
4 | 0.39 | 22 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Y. C. Eldar | 1 | 6399 | 458.37 |
| Wenjing Liao | 2 | 10 | 3.53 |
| Sui Tang | 3 | 7 | 2.16 |