Abstract
Phase information of a coherent signal is recorded and preserved as complex data. Although Fourier spectrum has long been proven to be effective, it is sometimes difficult to properly estimate phase information from severely corrupted signals. We present and define two useful parameters: spectral correlation coefficient (SCC) and spectral covariance to mean power ratio (SCR). A simulation test was carried out using a random Gaussian phase noise. The SCC and SCR decrease linearly with extremely low gradients as the noise level increase, and especially the SCC maintains high values larger than 0.9 up to 80% noise corrupted signals. We applied the SCC method to a radar interferometric phase, and demonstrated that it was effective even for severely corrupted signals by noises.
| Original language | English |
|---|---|
| Pages (from-to) | 375-379 |
| Number of pages | 5 |
| Journal | Optik |
| Volume | 115 |
| Issue number | 8 |
| DOIs | |
| Publication status | Published - 2004 Jan 1 |
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All Science Journal Classification (ASJC) codes
- Electronic, Optical and Magnetic Materials
- Atomic and Molecular Physics, and Optics
- Electrical and Electronic Engineering
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Spectral correlation analysis of complex data. / Won, Joong Sun; Kim, Jeong Woo; Min, Kyung Duck.
In: Optik, Vol. 115, No. 8, 01.01.2004, p. 375-379.Research output: Contribution to journal › Article
TY - JOUR
T1 - Spectral correlation analysis of complex data
AU - Won, Joong Sun
AU - Kim, Jeong Woo
AU - Min, Kyung Duck
PY - 2004/1/1
Y1 - 2004/1/1
N2 - Phase information of a coherent signal is recorded and preserved as complex data. Although Fourier spectrum has long been proven to be effective, it is sometimes difficult to properly estimate phase information from severely corrupted signals. We present and define two useful parameters: spectral correlation coefficient (SCC) and spectral covariance to mean power ratio (SCR). A simulation test was carried out using a random Gaussian phase noise. The SCC and SCR decrease linearly with extremely low gradients as the noise level increase, and especially the SCC maintains high values larger than 0.9 up to 80% noise corrupted signals. We applied the SCC method to a radar interferometric phase, and demonstrated that it was effective even for severely corrupted signals by noises.
AB - Phase information of a coherent signal is recorded and preserved as complex data. Although Fourier spectrum has long been proven to be effective, it is sometimes difficult to properly estimate phase information from severely corrupted signals. We present and define two useful parameters: spectral correlation coefficient (SCC) and spectral covariance to mean power ratio (SCR). A simulation test was carried out using a random Gaussian phase noise. The SCC and SCR decrease linearly with extremely low gradients as the noise level increase, and especially the SCC maintains high values larger than 0.9 up to 80% noise corrupted signals. We applied the SCC method to a radar interferometric phase, and demonstrated that it was effective even for severely corrupted signals by noises.
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U2 - 10.1078/0030-4026-00379
DO - 10.1078/0030-4026-00379
M3 - Article
VL - 115
SP - 375
EP - 379
JO - Optik
JF - Optik
SN - 0030-4026
IS - 8
ER -