Abstract
Spectrum analysis is a significant process for many measurement applications which is usually implemented by fast Fourier transform (FFT). Nevertheless, FFT is not suitable to deal with big data because of extra burden of computation. Moreover, FFT fails to provide enough accuracy for signals with a very sparse and broadband spectral distribution. In this letter, we propose a combination approach called FFT-segmented chirp-Z transform that allows to analyze a long-time signal, while the data are received, achieving faster speed, better resolution with only small memory size which shows great potential in real-time performance. With the help of this approach, zoom bands are detected, and optimal parameters are established to guarantee peaks in a broadband spectrum can be found in short time with high precision. We implement this approach in a high spatial resolution optical frequency-domain reflectometry to realize high speed and high precision of components localization in optical fiber. The experimental result shows that 2-mm spatial resolution is achieved at a distance of 54 m and the processing time was less than 2 s for 10-7 data points.
Original language | English |
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Article number | 7346430 |
Pages (from-to) | 657-660 |
Number of pages | 4 |
Journal | IEEE Photonics Technology Letters |
Volume | 28 |
Issue number | 6 |
DOIs | |
Publication status | Published - 15 Mar 2016 |
Externally published | Yes |
Keywords
- Optical communication
- Optical fiber measurements
- Parallel algorithms
- Signal processing
- Spectral analysis