This work proposes a frequency and amplitude estimator tailored for noise corrupted signals that have been clipped. Formulated as a sparse reconstruction problem, the proposed algorithm estimates the signal parameters by solving an atomic norm minimization problem. The estimator also exploits the waveform information provided by the clipped samples, incorporated in the form of linear constraints that have been augmented by slack variables as to provide robustness to noise. Numerical examples indicate that the algorithm offers preferable performance as compared to methods not exploiting the saturated samples.
|Titel på värdpublikation||2017 51st Asilomar Conference on Signals, Systems, and Computers|
|Förlag||IEEE - Institute of Electrical and Electronics Engineers Inc.|
|Status||Published - 2017|
|Evenemang||51st Asilomar Conferenec on Signals, Systems, and Computers (ASILOMAR 2017) - Asilomar, Pacific Grove, USA|
Varaktighet: 2017 okt. 29 → 2017 nov. 1
|Konferens||51st Asilomar Conferenec on Signals, Systems, and Computers (ASILOMAR 2017)|
|Period||2017/10/29 → 2017/11/01|