A Novel Sub-Nyquist FRI Sampling and Reconstruction Method in Linear Canonical Transform Domain
| Autor: | Hong-Cai Xin, Xia Bai, Bing-Zhao Li |
|---|---|
| Rok vydání: | 2021 |
| Předmět: |
0209 industrial biotechnology
Mean squared error Computer science Applied Mathematics Sampling (statistics) Reconstruction algorithm 02 engineering and technology Filter (signal processing) Domain (software engineering) 020901 industrial engineering & automation Kernel (statistics) Signal Processing Nyquist–Shannon sampling theorem Time domain Algorithm |
| Zdroj: | Circuits, Systems, and Signal Processing. 40:6173-6192 |
| ISSN: | 1531-5878 0278-081X |
| DOI: | 10.1007/s00034-021-01759-w |
| Popis: | The finite-rate-of-innovation (FRI) sampling frame has drawn a great deal of attention in many applications. In this paper, a novel sub-Nyquist FRI-based sampling and reconstruction method in linear canonical transform (LCT) domain is proposed. First, a new, compact-support sampling kernel is designed to acquire sub-Nyquist samples in time domain, which can be viewed as anti-aliasing prefilter in LCT domain. Then, the corresponding sampling theorem is derived and the reconstruction algorithm is summarized based on annihilating filter and least square method. Moreover, compared with other representative sub-Nyquist sampling methods, the experiment results demonstrate the superior reconstruction performance of the proposed method. The reconstruction ability in noisy environment is also measured by mean square error. Finally, the proposed method is applied to time delay estimation and can obtain super-resolution results. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|
Full text from SpringerLink